diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json new file mode 100644 index 000000000..f687072fe --- /dev/null +++ b/.devcontainer/devcontainer.json @@ -0,0 +1,27 @@ +{ + "name": "Frigate Dev", + "dockerComposeFile": "../docker-compose.yml", + "service": "dev", + "workspaceFolder": "/lab/frigate", + "extensions": [ + "ms-python.python", + "visualstudioexptteam.vscodeintellicode", + "mhutchie.git-graph", + "ms-azuretools.vscode-docker", + "streetsidesoftware.code-spell-checker", + "eamodio.gitlens", + "esbenp.prettier-vscode", + "ms-python.vscode-pylance" + ], + "settings": { + "python.pythonPath": "/usr/bin/python3", + "python.linting.pylintEnabled": true, + "python.linting.enabled": true, + "python.formatting.provider": "black", + "editor.formatOnPaste": false, + "editor.formatOnSave": true, + "editor.formatOnType": true, + "files.trimTrailingWhitespace": true, + "terminal.integrated.shell.linux": "/bin/bash" + } +} diff --git a/.dockerignore b/.dockerignore index c6f4105f3..5cad5e7d4 100644 --- a/.dockerignore +++ b/.dockerignore @@ -4,4 +4,7 @@ docs/ debug config/ *.pyc -.git \ No newline at end of file +.git +core +*.mp4 +*.db \ No newline at end of file diff --git a/.github/workflows/push.yml b/.github/workflows/push.yml deleted file mode 100644 index 9a340c4fb..000000000 --- a/.github/workflows/push.yml +++ /dev/null @@ -1,28 +0,0 @@ -name: On push - -on: - push: - branches: - - master - - release-0.8.0 - -jobs: - deploy-docs: - name: Deploy docs - runs-on: ubuntu-latest - defaults: - run: - working-directory: ./docs - steps: - - uses: actions/checkout@master - - uses: actions/setup-node@master - with: - node-version: 12.x - - run: npm install - - name: Build docs - run: npm run build - - name: Deploy documentation - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/build diff --git a/.gitignore b/.gitignore index a1dc92a01..85caded13 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,6 @@ .DS_Store *.pyc +*.swp debug .vscode config/config.yml @@ -10,3 +11,4 @@ frigate/version.py web/build web/node_modules web/coverage +core diff --git a/.pylintrc b/.pylintrc new file mode 100644 index 000000000..bf205daa6 --- /dev/null +++ b/.pylintrc @@ -0,0 +1,588 @@ +[MASTER] + +# A comma-separated list of package or module names from where C extensions may +# be loaded. Extensions are loading into the active Python interpreter and may +# run arbitrary code. +extension-pkg-whitelist= + +# Specify a score threshold to be exceeded before program exits with error. +fail-under=10.0 + +# Add files or directories to the blacklist. They should be base names, not +# paths. +ignore=CVS + +# Add files or directories matching the regex patterns to the blacklist. The +# regex matches against base names, not paths. +ignore-patterns= + +# Python code to execute, usually for sys.path manipulation such as +# pygtk.require(). +#init-hook= + +# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the +# number of processors available to use. +jobs=1 + +# Control the amount of potential inferred values when inferring a single +# object. This can help the performance when dealing with large functions or +# complex, nested conditions. +limit-inference-results=100 + +# List of plugins (as comma separated values of python module names) to load, +# usually to register additional checkers. +load-plugins= + +# Pickle collected data for later comparisons. +persistent=yes + +# When enabled, pylint would attempt to guess common misconfiguration and emit +# user-friendly hints instead of false-positive error messages. +suggestion-mode=yes + +# Allow loading of arbitrary C extensions. Extensions are imported into the +# active Python interpreter and may run arbitrary code. +unsafe-load-any-extension=no + + +[MESSAGES CONTROL] + +# Only show warnings with the listed confidence levels. Leave empty to show +# all. Valid levels: HIGH, INFERENCE, INFERENCE_FAILURE, UNDEFINED. +confidence= + +# Disable the message, report, category or checker with the given id(s). You +# can either give multiple identifiers separated by comma (,) or put this +# option multiple times (only on the command line, not in the configuration +# file where it should appear only once). You can also use "--disable=all" to +# disable everything first and then reenable specific checks. For example, if +# you want to run only the similarities checker, you can use "--disable=all +# --enable=similarities". If you want to run only the classes checker, but have +# no Warning level messages displayed, use "--disable=all --enable=classes +# --disable=W". +disable=print-statement, + parameter-unpacking, + unpacking-in-except, + old-raise-syntax, + backtick, + long-suffix, + old-ne-operator, + old-octal-literal, + import-star-module-level, + non-ascii-bytes-literal, + raw-checker-failed, + bad-inline-option, + locally-disabled, + file-ignored, + suppressed-message, + useless-suppression, + deprecated-pragma, + use-symbolic-message-instead, + apply-builtin, + basestring-builtin, + buffer-builtin, + cmp-builtin, + coerce-builtin, + execfile-builtin, + file-builtin, + long-builtin, + raw_input-builtin, + reduce-builtin, + standarderror-builtin, + unicode-builtin, + xrange-builtin, + coerce-method, + delslice-method, + getslice-method, + setslice-method, + no-absolute-import, + old-division, + dict-iter-method, + dict-view-method, + next-method-called, + metaclass-assignment, + indexing-exception, + raising-string, + reload-builtin, + oct-method, + hex-method, + nonzero-method, + cmp-method, + input-builtin, + round-builtin, + intern-builtin, + unichr-builtin, + map-builtin-not-iterating, + zip-builtin-not-iterating, + range-builtin-not-iterating, + filter-builtin-not-iterating, + using-cmp-argument, + eq-without-hash, + div-method, + idiv-method, + rdiv-method, + exception-message-attribute, + invalid-str-codec, + sys-max-int, + bad-python3-import, + deprecated-string-function, + deprecated-str-translate-call, + deprecated-itertools-function, + deprecated-types-field, + next-method-defined, + dict-items-not-iterating, + dict-keys-not-iterating, + dict-values-not-iterating, + deprecated-operator-function, + deprecated-urllib-function, + xreadlines-attribute, + deprecated-sys-function, + exception-escape, + comprehension-escape + +# Enable the message, report, category or checker with the given id(s). You can +# either give multiple identifier separated by comma (,) or put this option +# multiple time (only on the command line, not in the configuration file where +# it should appear only once). See also the "--disable" option for examples. +enable=c-extension-no-member + + +[REPORTS] + +# Python expression which should return a score less than or equal to 10. You +# have access to the variables 'error', 'warning', 'refactor', and 'convention' +# which contain the number of messages in each category, as well as 'statement' +# which is the total number of statements analyzed. This score is used by the +# global evaluation report (RP0004). +evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10) + +# Template used to display messages. This is a python new-style format string +# used to format the message information. See doc for all details. +#msg-template= + +# Set the output format. Available formats are text, parseable, colorized, json +# and msvs (visual studio). You can also give a reporter class, e.g. +# mypackage.mymodule.MyReporterClass. +output-format=text + +# Tells whether to display a full report or only the messages. +reports=no + +# Activate the evaluation score. +score=yes + + +[REFACTORING] + +# Maximum number of nested blocks for function / method body +max-nested-blocks=5 + +# Complete name of functions that never returns. When checking for +# inconsistent-return-statements if a never returning function is called then +# it will be considered as an explicit return statement and no message will be +# printed. +never-returning-functions=sys.exit + + +[SPELLING] + +# Limits count of emitted suggestions for spelling mistakes. +max-spelling-suggestions=4 + +# Spelling dictionary name. Available dictionaries: none. To make it work, +# install the python-enchant package. +spelling-dict= + +# List of comma separated words that should not be checked. +spelling-ignore-words= + +# A path to a file that contains the private dictionary; one word per line. +spelling-private-dict-file= + +# Tells whether to store unknown words to the private dictionary (see the +# --spelling-private-dict-file option) instead of raising a message. +spelling-store-unknown-words=no + + +[TYPECHECK] + +# List of decorators that produce context managers, such as +# contextlib.contextmanager. Add to this list to register other decorators that +# produce valid context managers. +contextmanager-decorators=contextlib.contextmanager + +# List of members which are set dynamically and missed by pylint inference +# system, and so shouldn't trigger E1101 when accessed. Python regular +# expressions are accepted. +generated-members= + +# Tells whether missing members accessed in mixin class should be ignored. A +# mixin class is detected if its name ends with "mixin" (case insensitive). +ignore-mixin-members=yes + +# Tells whether to warn about missing members when the owner of the attribute +# is inferred to be None. +ignore-none=yes + +# This flag controls whether pylint should warn about no-member and similar +# checks whenever an opaque object is returned when inferring. The inference +# can return multiple potential results while evaluating a Python object, but +# some branches might not be evaluated, which results in partial inference. In +# that case, it might be useful to still emit no-member and other checks for +# the rest of the inferred objects. +ignore-on-opaque-inference=yes + +# List of class names for which member attributes should not be checked (useful +# for classes with dynamically set attributes). This supports the use of +# qualified names. +ignored-classes=optparse.Values,thread._local,_thread._local + +# List of module names for which member attributes should not be checked +# (useful for modules/projects where namespaces are manipulated during runtime +# and thus existing member attributes cannot be deduced by static analysis). It +# supports qualified module names, as well as Unix pattern matching. +ignored-modules= + +# Show a hint with possible names when a member name was not found. The aspect +# of finding the hint is based on edit distance. +missing-member-hint=yes + +# The minimum edit distance a name should have in order to be considered a +# similar match for a missing member name. +missing-member-hint-distance=1 + +# The total number of similar names that should be taken in consideration when +# showing a hint for a missing member. +missing-member-max-choices=1 + +# List of decorators that change the signature of a decorated function. +signature-mutators= + + +[STRING] + +# This flag controls whether inconsistent-quotes generates a warning when the +# character used as a quote delimiter is used inconsistently within a module. +check-quote-consistency=no + +# This flag controls whether the implicit-str-concat should generate a warning +# on implicit string concatenation in sequences defined over several lines. +check-str-concat-over-line-jumps=no + + +[FORMAT] + +# Expected format of line ending, e.g. empty (any line ending), LF or CRLF. +expected-line-ending-format= + +# Regexp for a line that is allowed to be longer than the limit. +ignore-long-lines=^\s*(# )??$ + +# Number of spaces of indent required inside a hanging or continued line. +indent-after-paren=4 + +# String used as indentation unit. This is usually " " (4 spaces) or "\t" (1 +# tab). +indent-string=' ' + +# Maximum number of characters on a single line. +max-line-length=100 + +# Maximum number of lines in a module. +max-module-lines=1000 + +# Allow the body of a class to be on the same line as the declaration if body +# contains single statement. +single-line-class-stmt=no + +# Allow the body of an if to be on the same line as the test if there is no +# else. +single-line-if-stmt=no + + +[SIMILARITIES] + +# Ignore comments when computing similarities. +ignore-comments=yes + +# Ignore docstrings when computing similarities. +ignore-docstrings=yes + +# Ignore imports when computing similarities. +ignore-imports=no + +# Minimum lines number of a similarity. +min-similarity-lines=4 + + +[MISCELLANEOUS] + +# List of note tags to take in consideration, separated by a comma. +notes=FIXME, + XXX, + TODO + +# Regular expression of note tags to take in consideration. +#notes-rgx= + + +[BASIC] + +# Naming style matching correct argument names. +argument-naming-style=snake_case + +# Regular expression matching correct argument names. Overrides argument- +# naming-style. +#argument-rgx= + +# Naming style matching correct attribute names. +attr-naming-style=snake_case + +# Regular expression matching correct attribute names. Overrides attr-naming- +# style. +#attr-rgx= + +# Bad variable names which should always be refused, separated by a comma. +bad-names=foo, + bar, + baz, + toto, + tutu, + tata + +# Bad variable names regexes, separated by a comma. If names match any regex, +# they will always be refused +bad-names-rgxs= + +# Naming style matching correct class attribute names. +class-attribute-naming-style=any + +# Regular expression matching correct class attribute names. Overrides class- +# attribute-naming-style. +#class-attribute-rgx= + +# Naming style matching correct class names. +class-naming-style=PascalCase + +# Regular expression matching correct class names. Overrides class-naming- +# style. +#class-rgx= + +# Naming style matching correct constant names. +const-naming-style=UPPER_CASE + +# Regular expression matching correct constant names. Overrides const-naming- +# style. +#const-rgx= + +# Minimum line length for functions/classes that require docstrings, shorter +# ones are exempt. +docstring-min-length=-1 + +# Naming style matching correct function names. +function-naming-style=snake_case + +# Regular expression matching correct function names. Overrides function- +# naming-style. +#function-rgx= + +# Good variable names which should always be accepted, separated by a comma. +good-names=i, + j, + k, + ex, + Run, + _ + +# Good variable names regexes, separated by a comma. If names match any regex, +# they will always be accepted +good-names-rgxs= + +# Include a hint for the correct naming format with invalid-name. +include-naming-hint=no + +# Naming style matching correct inline iteration names. +inlinevar-naming-style=any + +# Regular expression matching correct inline iteration names. Overrides +# inlinevar-naming-style. +#inlinevar-rgx= + +# Naming style matching correct method names. +method-naming-style=snake_case + +# Regular expression matching correct method names. Overrides method-naming- +# style. +#method-rgx= + +# Naming style matching correct module names. +module-naming-style=snake_case + +# Regular expression matching correct module names. Overrides module-naming- +# style. +#module-rgx= + +# Colon-delimited sets of names that determine each other's naming style when +# the name regexes allow several styles. +name-group= + +# Regular expression which should only match function or class names that do +# not require a docstring. +no-docstring-rgx=^_ + +# List of decorators that produce properties, such as abc.abstractproperty. Add +# to this list to register other decorators that produce valid properties. +# These decorators are taken in consideration only for invalid-name. +property-classes=abc.abstractproperty + +# Naming style matching correct variable names. +variable-naming-style=snake_case + +# Regular expression matching correct variable names. Overrides variable- +# naming-style. +#variable-rgx= + + +[VARIABLES] + +# List of additional names supposed to be defined in builtins. Remember that +# you should avoid defining new builtins when possible. +additional-builtins= + +# Tells whether unused global variables should be treated as a violation. +allow-global-unused-variables=yes + +# List of strings which can identify a callback function by name. A callback +# name must start or end with one of those strings. +callbacks=cb_, + _cb + +# A regular expression matching the name of dummy variables (i.e. expected to +# not be used). +dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_ + +# Argument names that match this expression will be ignored. Default to name +# with leading underscore. +ignored-argument-names=_.*|^ignored_|^unused_ + +# Tells whether we should check for unused import in __init__ files. +init-import=no + +# List of qualified module names which can have objects that can redefine +# builtins. +redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io + + +[LOGGING] + +# The type of string formatting that logging methods do. `old` means using % +# formatting, `new` is for `{}` formatting. +logging-format-style=fstr + +# Logging modules to check that the string format arguments are in logging +# function parameter format. +logging-modules=logging + + +[DESIGN] + +# Maximum number of arguments for function / method. +max-args=5 + +# Maximum number of attributes for a class (see R0902). +max-attributes=7 + +# Maximum number of boolean expressions in an if statement (see R0916). +max-bool-expr=5 + +# Maximum number of branch for function / method body. +max-branches=12 + +# Maximum number of locals for function / method body. +max-locals=15 + +# Maximum number of parents for a class (see R0901). +max-parents=7 + +# Maximum number of public methods for a class (see R0904). +max-public-methods=20 + +# Maximum number of return / yield for function / method body. +max-returns=6 + +# Maximum number of statements in function / method body. +max-statements=50 + +# Minimum number of public methods for a class (see R0903). +min-public-methods=2 + + +[CLASSES] + +# List of method names used to declare (i.e. assign) instance attributes. +defining-attr-methods=__init__, + __new__, + setUp, + __post_init__ + +# List of member names, which should be excluded from the protected access +# warning. +exclude-protected=_asdict, + _fields, + _replace, + _source, + _make + +# List of valid names for the first argument in a class method. +valid-classmethod-first-arg=cls + +# List of valid names for the first argument in a metaclass class method. +valid-metaclass-classmethod-first-arg=cls + + +[IMPORTS] + +# List of modules that can be imported at any level, not just the top level +# one. +allow-any-import-level= + +# Allow wildcard imports from modules that define __all__. +allow-wildcard-with-all=no + +# Analyse import fallback blocks. This can be used to support both Python 2 and +# 3 compatible code, which means that the block might have code that exists +# only in one or another interpreter, leading to false positives when analysed. +analyse-fallback-blocks=no + +# Deprecated modules which should not be used, separated by a comma. +deprecated-modules=optparse,tkinter.tix + +# Create a graph of external dependencies in the given file (report RP0402 must +# not be disabled). +ext-import-graph= + +# Create a graph of every (i.e. internal and external) dependencies in the +# given file (report RP0402 must not be disabled). +import-graph= + +# Create a graph of internal dependencies in the given file (report RP0402 must +# not be disabled). +int-import-graph= + +# Force import order to recognize a module as part of the standard +# compatibility libraries. +known-standard-library= + +# Force import order to recognize a module as part of a third party library. +known-third-party=enchant + +# Couples of modules and preferred modules, separated by a comma. +preferred-modules= + + +[EXCEPTIONS] + +# Exceptions that will emit a warning when being caught. Defaults to +# "BaseException, Exception". +overgeneral-exceptions=BaseException, + Exception diff --git a/Makefile b/Makefile index eb6e9b49a..0bf2ab4d7 100644 --- a/Makefile +++ b/Makefile @@ -3,7 +3,7 @@ default_target: amd64_frigate COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1) version: - echo "VERSION='0.8.4-$(COMMIT_HASH)'" > frigate/version.py + echo "VERSION='0.9.0-$(COMMIT_HASH)'" > frigate/version.py web: docker build --tag frigate-web --file docker/Dockerfile.web web/ @@ -12,11 +12,14 @@ amd64_wheels: docker build --tag blakeblackshear/frigate-wheels:1.0.3-amd64 --file docker/Dockerfile.wheels . amd64_ffmpeg: - docker build --tag blakeblackshear/frigate-ffmpeg:1.1.0-amd64 --file docker/Dockerfile.ffmpeg.amd64 . + docker build --no-cache --pull --tag blakeblackshear/frigate-ffmpeg:1.2.0-amd64 --file docker/Dockerfile.ffmpeg.amd64 . + +nginx_frigate: + docker buildx build --push --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --tag blakeblackshear/frigate-nginx:1.0.2 --file docker/Dockerfile.nginx . amd64_frigate: version web - docker build --tag frigate-base --build-arg ARCH=amd64 --build-arg FFMPEG_VERSION=1.1.0 --build-arg WHEELS_VERSION=1.0.3 --file docker/Dockerfile.base . - docker build --tag frigate --file docker/Dockerfile.amd64 . + docker build --no-cache --tag frigate-base --build-arg ARCH=amd64 --build-arg FFMPEG_VERSION=1.1.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base . + docker build --no-cache --tag frigate --file docker/Dockerfile.amd64 . amd64_all: amd64_wheels amd64_ffmpeg amd64_frigate @@ -24,11 +27,11 @@ amd64nvidia_wheels: docker build --tag blakeblackshear/frigate-wheels:1.0.3-amd64nvidia --file docker/Dockerfile.wheels . amd64nvidia_ffmpeg: - docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-amd64nvidia --file docker/Dockerfile.ffmpeg.amd64nvidia . + docker build --no-cache --pull --tag blakeblackshear/frigate-ffmpeg:1.2.0-amd64nvidia --file docker/Dockerfile.ffmpeg.amd64nvidia . amd64nvidia_frigate: version web - docker build --tag frigate-base --build-arg ARCH=amd64nvidia --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --file docker/Dockerfile.base . - docker build --tag frigate --file docker/Dockerfile.amd64nvidia . + docker build --no-cache --tag frigate-base --build-arg ARCH=amd64nvidia --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base . + docker build --no-cache --tag frigate --file docker/Dockerfile.amd64nvidia . amd64nvidia_all: amd64nvidia_wheels amd64nvidia_ffmpeg amd64nvidia_frigate @@ -36,23 +39,23 @@ aarch64_wheels: docker build --tag blakeblackshear/frigate-wheels:1.0.3-aarch64 --file docker/Dockerfile.wheels . aarch64_ffmpeg: - docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-aarch64 --file docker/Dockerfile.ffmpeg.aarch64 . + docker build --no-cache --pull --tag blakeblackshear/frigate-ffmpeg:1.3.0-aarch64 --file docker/Dockerfile.ffmpeg.aarch64 . aarch64_frigate: version web - docker build --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --file docker/Dockerfile.base . - docker build --tag frigate --file docker/Dockerfile.aarch64 . + docker build --no-cache --tag frigate-base --build-arg ARCH=aarch64 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base . + docker build --no-cache --tag frigate --file docker/Dockerfile.aarch64 . -armv7_all: armv7_wheels armv7_ffmpeg armv7_frigate +aarch64_all: aarch64_wheels aarch64_ffmpeg aarch64_frigate armv7_wheels: docker build --tag blakeblackshear/frigate-wheels:1.0.3-armv7 --file docker/Dockerfile.wheels . armv7_ffmpeg: - docker build --tag blakeblackshear/frigate-ffmpeg:1.0.0-armv7 --file docker/Dockerfile.ffmpeg.armv7 . + docker build --no-cache --pull --tag blakeblackshear/frigate-ffmpeg:1.2.0-armv7 --file docker/Dockerfile.ffmpeg.armv7 . armv7_frigate: version web - docker build --tag frigate-base --build-arg ARCH=armv7 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --file docker/Dockerfile.base . - docker build --tag frigate --file docker/Dockerfile.armv7 . + docker build --no-cache --tag frigate-base --build-arg ARCH=armv7 --build-arg FFMPEG_VERSION=1.0.0 --build-arg WHEELS_VERSION=1.0.3 --build-arg NGINX_VERSION=1.0.2 --file docker/Dockerfile.base . + docker build --no-cache --tag frigate --file docker/Dockerfile.armv7 . armv7_all: armv7_wheels armv7_ffmpeg armv7_frigate diff --git a/README.md b/README.md index 012a856af..009e945cb 100644 --- a/README.md +++ b/README.md @@ -14,25 +14,29 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but - Uses a very low overhead motion detection to determine where to run object detection - Object detection with TensorFlow runs in separate processes for maximum FPS - Communicates over MQTT for easy integration into other systems -- Records video clips of detected objects +- Records video with retention settings based on detected objects - 24/7 recording - Re-streaming via RTMP to reduce the number of connections to your camera ## Documentation -View the documentation at https://blakeblackshear.github.io/frigate +View the documentation at https://docs.frigate.video ## Donations + If you would like to make a donation to support development, please use [Github Sponsors](https://github.com/sponsors/blakeblackshear). ## Screenshots + Integration into Home Assistant +
Also comes with a builtin UI: +
diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 000000000..197d9e11e --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,29 @@ +version: "3" +services: + dev: + container_name: frigate-dev + user: vscode + privileged: true + shm_size: "256mb" + build: + context: . + dockerfile: docker/Dockerfile.dev + volumes: + - /etc/localtime:/etc/localtime:ro + - .:/lab/frigate:cached + - ./config/config.yml:/config/config.yml:ro + - ./debug:/media/frigate + - /dev/bus/usb:/dev/bus/usb + - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware + ports: + - "1935:1935" + - "5000:5000" + - "5001:5001" + - "8080:8080" + entrypoint: ["sudo", "/init"] + command: /bin/sh -c "while sleep 1000; do :; done" + mqtt: + container_name: mqtt + image: eclipse-mosquitto:1.6 + ports: + - "1883:1883" diff --git a/docker/Dockerfile.aarch64 b/docker/Dockerfile.aarch64 index 5ce548f2d..30d69fc83 100644 --- a/docker/Dockerfile.aarch64 +++ b/docker/Dockerfile.aarch64 @@ -5,18 +5,24 @@ ENV DEBIAN_FRONTEND=noninteractive # Install packages for apt repo RUN apt-get -qq update \ && apt-get -qq install --no-install-recommends -y \ - # ffmpeg runtime dependencies - libgomp1 \ - # runtime dependencies - libopenexr24 \ - libgstreamer1.0-0 \ - libgstreamer-plugins-base1.0-0 \ - libopenblas-base \ - libjpeg-turbo8 \ - libpng16-16 \ - libtiff5 \ - libdc1394-22 \ - ## Tensorflow lite - && pip3 install https://github.com/google-coral/pycoral/releases/download/release-frogfish/tflite_runtime-2.5.0-cp38-cp38-linux_aarch64.whl \ + # ffmpeg runtime dependencies + libgomp1 \ + # runtime dependencies + libopenexr24 \ + libgstreamer1.0-0 \ + libgstreamer-plugins-base1.0-0 \ + libopenblas-base \ + libjpeg-turbo8 \ + libpng16-16 \ + libtiff5 \ + libdc1394-22 \ && rm -rf /var/lib/apt/lists/* \ - && (apt-get autoremove -y; apt-get autoclean -y) \ No newline at end of file + && (apt-get autoremove -y; apt-get autoclean -y) + +# s6-overlay +ADD https://github.com/just-containers/s6-overlay/releases/download/v2.2.0.3/s6-overlay-aarch64-installer /tmp/ +RUN chmod +x /tmp/s6-overlay-aarch64-installer && /tmp/s6-overlay-aarch64-installer / + +ENTRYPOINT ["/init"] + +CMD ["python3", "-u", "-m", "frigate"] \ No newline at end of file diff --git a/docker/Dockerfile.amd64 b/docker/Dockerfile.amd64 index 56f9839e8..d583e43f8 100644 --- a/docker/Dockerfile.amd64 +++ b/docker/Dockerfile.amd64 @@ -4,15 +4,25 @@ LABEL maintainer "blakeb@blakeshome.com" # By default, use the i965 driver ENV LIBVA_DRIVER_NAME=i965 # Install packages for apt repo + +RUN wget -qO - https://repositories.intel.com/graphics/intel-graphics.key | apt-key add - \ + && echo 'deb [arch=amd64] https://repositories.intel.com/graphics/ubuntu focal main' > /etc/apt/sources.list.d/intel-graphics.list \ + && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys F63F0F2B90935439 \ + && echo 'deb http://ppa.launchpad.net/kisak/kisak-mesa/ubuntu focal main' > /etc/apt/sources.list.d/kisak-mesa-focal.list + RUN apt-get -qq update \ && apt-get -qq install --no-install-recommends -y \ - # ffmpeg dependencies - libgomp1 \ - # VAAPI drivers for Intel hardware accel - libva-drm2 libva2 libmfx1 i965-va-driver vainfo intel-media-va-driver mesa-va-drivers \ - ## Tensorflow lite - && wget -q https://github.com/google-coral/pycoral/releases/download/release-frogfish/tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ - && python3.8 -m pip install tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ - && rm tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ + # ffmpeg dependencies + libgomp1 \ + # VAAPI drivers for Intel hardware accel + libva-drm2 libva2 libmfx1 i965-va-driver vainfo intel-media-va-driver-non-free mesa-vdpau-drivers mesa-va-drivers mesa-vdpau-drivers libdrm-radeon1 \ && rm -rf /var/lib/apt/lists/* \ - && (apt-get autoremove -y; apt-get autoclean -y) \ No newline at end of file + && (apt-get autoremove -y; apt-get autoclean -y) + +# s6-overlay +ADD https://github.com/just-containers/s6-overlay/releases/download/v2.2.0.3/s6-overlay-amd64-installer /tmp/ +RUN chmod +x /tmp/s6-overlay-amd64-installer && /tmp/s6-overlay-amd64-installer / + +ENTRYPOINT ["/init"] + +CMD ["python3", "-u", "-m", "frigate"] \ No newline at end of file diff --git a/docker/Dockerfile.amd64nvidia b/docker/Dockerfile.amd64nvidia index 8714f70ad..f893d684f 100644 --- a/docker/Dockerfile.amd64nvidia +++ b/docker/Dockerfile.amd64nvidia @@ -4,12 +4,8 @@ LABEL maintainer "blakeb@blakeshome.com" # Install packages for apt repo RUN apt-get -qq update \ && apt-get -qq install --no-install-recommends -y \ - # ffmpeg dependencies - libgomp1 \ - ## Tensorflow lite - && wget -q https://github.com/google-coral/pycoral/releases/download/release-frogfish/tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ - && python3.8 -m pip install tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ - && rm tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl \ + # ffmpeg dependencies + libgomp1 \ && rm -rf /var/lib/apt/lists/* \ && (apt-get autoremove -y; apt-get autoclean -y) @@ -45,3 +41,11 @@ ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64 ENV NVIDIA_VISIBLE_DEVICES all ENV NVIDIA_DRIVER_CAPABILITIES compute,utility,video ENV NVIDIA_REQUIRE_CUDA "cuda>=11.1 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441 brand=tesla,driver>=450,driver<451" + +# s6-overlay +ADD https://github.com/just-containers/s6-overlay/releases/download/v2.2.0.3/s6-overlay-amd64-installer /tmp/ +RUN chmod +x /tmp/s6-overlay-amd64-installer && /tmp/s6-overlay-amd64-installer / + +ENTRYPOINT ["/init"] + +CMD ["python3", "-u", "-m", "frigate"] \ No newline at end of file diff --git a/docker/Dockerfile.armv7 b/docker/Dockerfile.armv7 index 2e50cd22c..af44301b8 100644 --- a/docker/Dockerfile.armv7 +++ b/docker/Dockerfile.armv7 @@ -5,20 +5,26 @@ ENV DEBIAN_FRONTEND=noninteractive # Install packages for apt repo RUN apt-get -qq update \ && apt-get -qq install --no-install-recommends -y \ - # ffmpeg runtime dependencies - libgomp1 \ - # runtime dependencies - libopenexr24 \ - libgstreamer1.0-0 \ - libgstreamer-plugins-base1.0-0 \ - libopenblas-base \ - libjpeg-turbo8 \ - libpng16-16 \ - libtiff5 \ - libdc1394-22 \ - libaom0 \ - libx265-179 \ - ## Tensorflow lite - && pip3 install https://github.com/google-coral/pycoral/releases/download/release-frogfish/tflite_runtime-2.5.0-cp38-cp38-linux_armv7l.whl \ + # ffmpeg runtime dependencies + libgomp1 \ + # runtime dependencies + libopenexr24 \ + libgstreamer1.0-0 \ + libgstreamer-plugins-base1.0-0 \ + libopenblas-base \ + libjpeg-turbo8 \ + libpng16-16 \ + libtiff5 \ + libdc1394-22 \ + libaom0 \ + libx265-179 \ && rm -rf /var/lib/apt/lists/* \ - && (apt-get autoremove -y; apt-get autoclean -y) \ No newline at end of file + && (apt-get autoremove -y; apt-get autoclean -y) + +# s6-overlay +ADD https://github.com/just-containers/s6-overlay/releases/download/v2.2.0.3/s6-overlay-armhf-installer /tmp/ +RUN chmod +x /tmp/s6-overlay-armhf-installer && /tmp/s6-overlay-armhf-installer / + +ENTRYPOINT ["/init"] + +CMD ["python3", "-u", "-m", "frigate"] \ No newline at end of file diff --git a/docker/Dockerfile.base b/docker/Dockerfile.base index 794e81dac..ec1b5a0aa 100644 --- a/docker/Dockerfile.base +++ b/docker/Dockerfile.base @@ -1,8 +1,10 @@ ARG ARCH=amd64 ARG WHEELS_VERSION ARG FFMPEG_VERSION +ARG NGINX_VERSION FROM blakeblackshear/frigate-wheels:${WHEELS_VERSION}-${ARCH} as wheels FROM blakeblackshear/frigate-ffmpeg:${FFMPEG_VERSION}-${ARCH} as ffmpeg +FROM blakeblackshear/frigate-nginx:${NGINX_VERSION} as nginx FROM frigate-web as web FROM ubuntu:20.04 @@ -18,33 +20,28 @@ ENV DEBIAN_FRONTEND=noninteractive # Install packages for apt repo RUN apt-get -qq update \ && apt-get upgrade -y \ - && apt-get -qq install --no-install-recommends -y \ - gnupg wget unzip tzdata nginx libnginx-mod-rtmp \ - && apt-get -qq install --no-install-recommends -y \ - python3-pip \ + && apt-get -qq install --no-install-recommends -y gnupg wget unzip tzdata libxml2 \ + && apt-get -qq install --no-install-recommends -y python3-pip \ && pip3 install -U /wheels/*.whl \ && APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn apt-key adv --fetch-keys https://packages.cloud.google.com/apt/doc/apt-key.gpg \ && echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \ && echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections \ - && apt-get -qq update && apt-get -qq install --no-install-recommends -y \ - libedgetpu1-max=15.0 \ + && apt-get -qq update && apt-get -qq install --no-install-recommends -y libedgetpu1-max python3-tflite-runtime python3-pycoral \ && rm -rf /var/lib/apt/lists/* /wheels \ && (apt-get autoremove -y; apt-get autoclean -y) RUN pip3 install \ peewee_migrate \ + pydantic \ zeroconf \ - voluptuous\ - Flask-Sockets \ - gevent \ - gevent-websocket + ws4py -COPY nginx/nginx.conf /etc/nginx/nginx.conf +COPY --from=nginx /usr/local/nginx/ /usr/local/nginx/ # get model and labels COPY labelmap.txt /labelmap.txt -RUN wget -q https://github.com/google-coral/test_data/raw/master/ssdlite_mobiledet_coco_qat_postprocess_edgetpu.tflite -O /edgetpu_model.tflite -RUN wget -q https://github.com/google-coral/test_data/raw/master/ssdlite_mobiledet_coco_qat_postprocess.tflite -O /cpu_model.tflite +RUN wget -q https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess_edgetpu.tflite -O /edgetpu_model.tflite +RUN wget -q https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess.tflite -O /cpu_model.tflite WORKDIR /opt/frigate/ ADD frigate frigate/ @@ -52,10 +49,7 @@ ADD migrations migrations/ COPY --from=web /opt/frigate/build web/ -COPY run.sh /run.sh -RUN chmod +x /run.sh +COPY docker/rootfs/ / EXPOSE 5000 EXPOSE 1935 - -CMD ["/run.sh"] diff --git a/docker/Dockerfile.dev b/docker/Dockerfile.dev new file mode 100644 index 000000000..41a3296c9 --- /dev/null +++ b/docker/Dockerfile.dev @@ -0,0 +1,24 @@ +FROM frigate:latest + +ARG USERNAME=vscode +ARG USER_UID=1000 +ARG USER_GID=$USER_UID + +# Create the user +RUN groupadd --gid $USER_GID $USERNAME \ + && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME \ + # + # [Optional] Add sudo support. Omit if you don't need to install software after connecting. + && apt-get update \ + && apt-get install -y sudo \ + && echo $USERNAME ALL=\(root\) NOPASSWD:ALL > /etc/sudoers.d/$USERNAME \ + && chmod 0440 /etc/sudoers.d/$USERNAME + +RUN apt-get update \ + && apt-get install -y git curl vim htop + +RUN pip3 install pylint black + +# Install Node 14 +RUN curl -sL https://deb.nodesource.com/setup_14.x | bash - \ + && apt-get install -y nodejs diff --git a/docker/Dockerfile.ffmpeg.aarch64 b/docker/Dockerfile.ffmpeg.aarch64 index 3fa630a65..b53dda2ee 100644 --- a/docker/Dockerfile.ffmpeg.aarch64 +++ b/docker/Dockerfile.ffmpeg.aarch64 @@ -9,41 +9,41 @@ WORKDIR /tmp/workdir ENV DEBIAN_FRONTEND=noninteractive RUN apt-get -yqq update && \ - apt-get install -yq --no-install-recommends ca-certificates expat libgomp1 && \ + apt-get install -yq --no-install-recommends ca-certificates expat libgomp1 xutils-dev && \ apt-get autoremove -y && \ apt-get clean -y FROM base as build -ENV FFMPEG_VERSION=4.3.1 \ - AOM_VERSION=v1.0.0 \ - FDKAAC_VERSION=0.1.5 \ - FREETYPE_VERSION=2.5.5 \ - FRIBIDI_VERSION=0.19.7 \ - KVAZAAR_VERSION=1.2.0 \ - LAME_VERSION=3.100 \ - LIBPTHREAD_STUBS_VERSION=0.4 \ - LIBVIDSTAB_VERSION=1.1.0 \ - LIBXCB_VERSION=1.13.1 \ - XCBPROTO_VERSION=1.13 \ - OGG_VERSION=1.3.2 \ - OPENCOREAMR_VERSION=0.1.5 \ - OPUS_VERSION=1.2 \ - OPENJPEG_VERSION=2.1.2 \ - THEORA_VERSION=1.1.1 \ - VORBIS_VERSION=1.3.5 \ - VPX_VERSION=1.8.0 \ - WEBP_VERSION=1.0.2 \ - X264_VERSION=20170226-2245-stable \ - X265_VERSION=3.1.1 \ - XAU_VERSION=1.0.9 \ - XORG_MACROS_VERSION=1.19.2 \ - XPROTO_VERSION=7.0.31 \ - XVID_VERSION=1.3.4 \ - LIBZMQ_VERSION=4.3.2 \ - SRC=/usr/local +ENV FFMPEG_VERSION=4.3.2 \ + AOM_VERSION=v1.0.0 \ + FDKAAC_VERSION=0.1.5 \ + FREETYPE_VERSION=2.11.0 \ + FRIBIDI_VERSION=0.19.7 \ + KVAZAAR_VERSION=1.2.0 \ + LAME_VERSION=3.100 \ + LIBPTHREAD_STUBS_VERSION=0.4 \ + LIBVIDSTAB_VERSION=1.1.0 \ + LIBXCB_VERSION=1.13.1 \ + XCBPROTO_VERSION=1.13 \ + OGG_VERSION=1.3.2 \ + OPENCOREAMR_VERSION=0.1.5 \ + OPUS_VERSION=1.2 \ + OPENJPEG_VERSION=2.1.2 \ + THEORA_VERSION=1.1.1 \ + VORBIS_VERSION=1.3.5 \ + VPX_VERSION=1.8.0 \ + WEBP_VERSION=1.0.2 \ + X264_VERSION=20170226-2245-stable \ + X265_VERSION=3.1.1 \ + XAU_VERSION=1.0.9 \ + XORG_MACROS_VERSION=1.19.2 \ + XPROTO_VERSION=7.0.31 \ + XVID_VERSION=1.3.4 \ + LIBZMQ_VERSION=4.3.2 \ + SRC=/usr/local -ARG FREETYPE_SHA256SUM="5d03dd76c2171a7601e9ce10551d52d4471cf92cd205948e60289251daddffa8 freetype-2.5.5.tar.gz" +ARG FREETYPE_SHA256SUM="a45c6b403413abd5706f3582f04c8339d26397c4304b78fa552f2215df64101f freetype-2.11.0.tar.gz" ARG FRIBIDI_SHA256SUM="3fc96fa9473bd31dcb5500bdf1aa78b337ba13eb8c301e7c28923fea982453a8 0.19.7.tar.gz" ARG LIBVIDSTAB_SHA256SUM="14d2a053e56edad4f397be0cb3ef8eb1ec3150404ce99a426c4eb641861dc0bb v1.1.0.tar.gz" ARG OGG_SHA256SUM="e19ee34711d7af328cb26287f4137e70630e7261b17cbe3cd41011d73a654692 libogg-1.3.2.tar.gz" @@ -61,27 +61,27 @@ ARG PREFIX=/opt/ffmpeg ARG LD_LIBRARY_PATH="/opt/ffmpeg/lib:/opt/ffmpeg/lib64:/usr/lib64:/usr/lib:/lib64:/lib" -RUN buildDeps="autoconf \ - automake \ - cmake \ - curl \ - bzip2 \ - libexpat1-dev \ - g++ \ - gcc \ - git \ - gperf \ - libtool \ - make \ - nasm \ - perl \ - pkg-config \ - python \ - libssl-dev \ - yasm \ - linux-headers-raspi2 \ - libomxil-bellagio-dev \ - zlib1g-dev" && \ +RUN buildDeps="autoconf \ + automake \ + cmake \ + curl \ + bzip2 \ + libexpat1-dev \ + g++ \ + gcc \ + git \ + gperf \ + libtool \ + make \ + nasm \ + perl \ + pkg-config \ + python \ + libssl-dev \ + yasm \ + linux-headers-raspi2 \ + libomxil-bellagio-dev \ + zlib1g-dev" && \ apt-get -yqq update && \ apt-get install -yq --no-install-recommends ${buildDeps} ## opencore-amr https://sourceforge.net/projects/opencore-amr/ @@ -392,6 +392,16 @@ RUN \ make -j $(nproc) install && \ rm -rf ${DIR} + +RUN \ + DIR=/tmp/rkmpp && \ + mkdir -p ${DIR} && \ + cd ${DIR} && \ + git clone https://github.com/rockchip-linux/libdrm-rockchip && git clone https://github.com/rockchip-linux/mpp && \ + cd libdrm-rockchip && bash autogen.sh && ./configure && make && make install && \ + cd ../mpp && cmake -DRKPLATFORM=ON -DHAVE_DRM=ON && make -j6 && make install && \ + rm -rf ${DIR} + ## ffmpeg https://ffmpeg.org/ RUN \ DIR=/tmp/ffmpeg && mkdir -p ${DIR} && cd ${DIR} && \ @@ -434,6 +444,8 @@ RUN \ --enable-libkvazaar \ --enable-libaom \ --extra-libs=-lpthread \ + --enable-rkmpp \ + --enable-libdrm \ # --enable-omx \ # --enable-omx-rpi \ # --enable-mmal \ @@ -459,7 +471,7 @@ RUN \ cp -r ${PREFIX}/include/libav* ${PREFIX}/include/libpostproc ${PREFIX}/include/libsw* /usr/local/include && \ mkdir -p /usr/local/lib/pkgconfig && \ for pc in ${PREFIX}/lib/pkgconfig/libav*.pc ${PREFIX}/lib/pkgconfig/libpostproc.pc ${PREFIX}/lib/pkgconfig/libsw*.pc; do \ - sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ + sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ done FROM base AS release diff --git a/docker/Dockerfile.ffmpeg.amd64 b/docker/Dockerfile.ffmpeg.amd64 index 21e0e6b9f..5dc005505 100644 --- a/docker/Dockerfile.ffmpeg.amd64 +++ b/docker/Dockerfile.ffmpeg.amd64 @@ -14,33 +14,33 @@ RUN apt-get -yqq update && \ FROM base as build -ENV FFMPEG_VERSION=4.3.1 \ - AOM_VERSION=v1.0.0 \ - FDKAAC_VERSION=0.1.5 \ - FREETYPE_VERSION=2.5.5 \ - FRIBIDI_VERSION=0.19.7 \ - KVAZAAR_VERSION=1.2.0 \ - LAME_VERSION=3.100 \ - LIBPTHREAD_STUBS_VERSION=0.4 \ - LIBVIDSTAB_VERSION=1.1.0 \ - LIBXCB_VERSION=1.13.1 \ - XCBPROTO_VERSION=1.13 \ - OGG_VERSION=1.3.2 \ - OPENCOREAMR_VERSION=0.1.5 \ - OPUS_VERSION=1.2 \ - OPENJPEG_VERSION=2.1.2 \ - THEORA_VERSION=1.1.1 \ - VORBIS_VERSION=1.3.5 \ - VPX_VERSION=1.8.0 \ - WEBP_VERSION=1.0.2 \ - X264_VERSION=20170226-2245-stable \ - X265_VERSION=3.1.1 \ - XAU_VERSION=1.0.9 \ - XORG_MACROS_VERSION=1.19.2 \ - XPROTO_VERSION=7.0.31 \ - XVID_VERSION=1.3.4 \ - LIBZMQ_VERSION=4.3.2 \ - SRC=/usr/local +ENV FFMPEG_VERSION=4.3.2 \ + AOM_VERSION=v1.0.0 \ + FDKAAC_VERSION=0.1.5 \ + FREETYPE_VERSION=2.5.5 \ + FRIBIDI_VERSION=0.19.7 \ + KVAZAAR_VERSION=1.2.0 \ + LAME_VERSION=3.100 \ + LIBPTHREAD_STUBS_VERSION=0.4 \ + LIBVIDSTAB_VERSION=1.1.0 \ + LIBXCB_VERSION=1.13.1 \ + XCBPROTO_VERSION=1.13 \ + OGG_VERSION=1.3.2 \ + OPENCOREAMR_VERSION=0.1.5 \ + OPUS_VERSION=1.2 \ + OPENJPEG_VERSION=2.1.2 \ + THEORA_VERSION=1.1.1 \ + VORBIS_VERSION=1.3.5 \ + VPX_VERSION=1.8.0 \ + WEBP_VERSION=1.0.2 \ + X264_VERSION=20170226-2245-stable \ + X265_VERSION=3.1.1 \ + XAU_VERSION=1.0.9 \ + XORG_MACROS_VERSION=1.19.2 \ + XPROTO_VERSION=7.0.31 \ + XVID_VERSION=1.3.4 \ + LIBZMQ_VERSION=4.3.2 \ + SRC=/usr/local ARG FREETYPE_SHA256SUM="5d03dd76c2171a7601e9ce10551d52d4471cf92cd205948e60289251daddffa8 freetype-2.5.5.tar.gz" ARG FRIBIDI_SHA256SUM="3fc96fa9473bd31dcb5500bdf1aa78b337ba13eb8c301e7c28923fea982453a8 0.19.7.tar.gz" @@ -60,27 +60,27 @@ ARG PREFIX=/opt/ffmpeg ARG LD_LIBRARY_PATH="/opt/ffmpeg/lib:/opt/ffmpeg/lib64:/usr/lib64:/usr/lib:/lib64:/lib" -RUN buildDeps="autoconf \ - automake \ - cmake \ - curl \ - bzip2 \ - libexpat1-dev \ - g++ \ - gcc \ - git \ - gperf \ - libtool \ - make \ - nasm \ - perl \ - pkg-config \ - python \ - libssl-dev \ - yasm \ - libva-dev \ - libmfx-dev \ - zlib1g-dev" && \ +RUN buildDeps="autoconf \ + automake \ + cmake \ + curl \ + bzip2 \ + libexpat1-dev \ + g++ \ + gcc \ + git \ + gperf \ + libtool \ + make \ + nasm \ + perl \ + pkg-config \ + python \ + libssl-dev \ + yasm \ + libva-dev \ + libmfx-dev \ + zlib1g-dev" && \ apt-get -yqq update && \ apt-get install -yq --no-install-recommends ${buildDeps} ## opencore-amr https://sourceforge.net/projects/opencore-amr/ @@ -450,7 +450,7 @@ RUN \ cp -r ${PREFIX}/include/libav* ${PREFIX}/include/libpostproc ${PREFIX}/include/libsw* /usr/local/include && \ mkdir -p /usr/local/lib/pkgconfig && \ for pc in ${PREFIX}/lib/pkgconfig/libav*.pc ${PREFIX}/lib/pkgconfig/libpostproc.pc ${PREFIX}/lib/pkgconfig/libsw*.pc; do \ - sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ + sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ done FROM base AS release @@ -463,6 +463,6 @@ ENTRYPOINT ["ffmpeg"] COPY --from=build /usr/local /usr/local/ RUN \ - apt-get update -y && \ - apt-get install -y --no-install-recommends libva-drm2 libva2 i965-va-driver mesa-va-drivers && \ - rm -rf /var/lib/apt/lists/* + apt-get update -y && \ + apt-get install -y --no-install-recommends libva-drm2 libva2 i965-va-driver mesa-va-drivers && \ + rm -rf /var/lib/apt/lists/* diff --git a/docker/Dockerfile.ffmpeg.amd64nvidia b/docker/Dockerfile.ffmpeg.amd64nvidia index 402e8973d..71f91fe4f 100644 --- a/docker/Dockerfile.ffmpeg.amd64nvidia +++ b/docker/Dockerfile.ffmpeg.amd64nvidia @@ -37,36 +37,36 @@ FROM devel-base as build ENV NVIDIA_HEADERS_VERSION=9.1.23.1 -ENV FFMPEG_VERSION=4.3.1 \ - AOM_VERSION=v1.0.0 \ - FDKAAC_VERSION=0.1.5 \ - FREETYPE_VERSION=2.5.5 \ - FRIBIDI_VERSION=0.19.7 \ - KVAZAAR_VERSION=1.2.0 \ - LAME_VERSION=3.100 \ - LIBPTHREAD_STUBS_VERSION=0.4 \ - LIBVIDSTAB_VERSION=1.1.0 \ - LIBXCB_VERSION=1.13.1 \ - XCBPROTO_VERSION=1.13 \ - OGG_VERSION=1.3.2 \ - OPENCOREAMR_VERSION=0.1.5 \ - OPUS_VERSION=1.2 \ - OPENJPEG_VERSION=2.1.2 \ - THEORA_VERSION=1.1.1 \ - VORBIS_VERSION=1.3.5 \ - VPX_VERSION=1.8.0 \ - WEBP_VERSION=1.0.2 \ - X264_VERSION=20170226-2245-stable \ - X265_VERSION=3.1.1 \ - XAU_VERSION=1.0.9 \ - XORG_MACROS_VERSION=1.19.2 \ - XPROTO_VERSION=7.0.31 \ - XVID_VERSION=1.3.4 \ - LIBZMQ_VERSION=4.3.2 \ - LIBSRT_VERSION=1.4.1 \ - LIBARIBB24_VERSION=1.0.3 \ - LIBPNG_VERSION=1.6.9 \ - SRC=/usr/local +ENV FFMPEG_VERSION=4.3.2 \ + AOM_VERSION=v1.0.0 \ + FDKAAC_VERSION=0.1.5 \ + FREETYPE_VERSION=2.5.5 \ + FRIBIDI_VERSION=0.19.7 \ + KVAZAAR_VERSION=1.2.0 \ + LAME_VERSION=3.100 \ + LIBPTHREAD_STUBS_VERSION=0.4 \ + LIBVIDSTAB_VERSION=1.1.0 \ + LIBXCB_VERSION=1.13.1 \ + XCBPROTO_VERSION=1.13 \ + OGG_VERSION=1.3.2 \ + OPENCOREAMR_VERSION=0.1.5 \ + OPUS_VERSION=1.2 \ + OPENJPEG_VERSION=2.1.2 \ + THEORA_VERSION=1.1.1 \ + VORBIS_VERSION=1.3.5 \ + VPX_VERSION=1.8.0 \ + WEBP_VERSION=1.0.2 \ + X264_VERSION=20170226-2245-stable \ + X265_VERSION=3.1.1 \ + XAU_VERSION=1.0.9 \ + XORG_MACROS_VERSION=1.19.2 \ + XPROTO_VERSION=7.0.31 \ + XVID_VERSION=1.3.4 \ + LIBZMQ_VERSION=4.3.2 \ + LIBSRT_VERSION=1.4.1 \ + LIBARIBB24_VERSION=1.0.3 \ + LIBPNG_VERSION=1.6.9 \ + SRC=/usr/local ARG FREETYPE_SHA256SUM="5d03dd76c2171a7601e9ce10551d52d4471cf92cd205948e60289251daddffa8 freetype-2.5.5.tar.gz" ARG FRIBIDI_SHA256SUM="3fc96fa9473bd31dcb5500bdf1aa78b337ba13eb8c301e7c28923fea982453a8 0.19.7.tar.gz" @@ -87,35 +87,35 @@ ARG PREFIX=/opt/ffmpeg ARG LD_LIBRARY_PATH="/opt/ffmpeg/lib:/opt/ffmpeg/lib64" -RUN buildDeps="autoconf \ - automake \ - cmake \ - curl \ - bzip2 \ - libexpat1-dev \ - g++ \ - gcc \ - git \ - gperf \ - libtool \ - make \ - nasm \ - perl \ - pkg-config \ - python \ - libssl-dev \ - yasm \ - zlib1g-dev" && \ +RUN buildDeps="autoconf \ + automake \ + cmake \ + curl \ + bzip2 \ + libexpat1-dev \ + g++ \ + gcc \ + git \ + gperf \ + libtool \ + make \ + nasm \ + perl \ + pkg-config \ + python \ + libssl-dev \ + yasm \ + zlib1g-dev" && \ apt-get -yqq update && \ apt-get install -yq --no-install-recommends ${buildDeps} RUN \ - DIR=/tmp/nv-codec-headers && \ - git clone https://github.com/FFmpeg/nv-codec-headers ${DIR} && \ - cd ${DIR} && \ - git checkout n${NVIDIA_HEADERS_VERSION} && \ - make PREFIX="${PREFIX}" && \ - make install PREFIX="${PREFIX}" && \ + DIR=/tmp/nv-codec-headers && \ + git clone https://github.com/FFmpeg/nv-codec-headers ${DIR} && \ + cd ${DIR} && \ + git checkout n${NVIDIA_HEADERS_VERSION} && \ + make PREFIX="${PREFIX}" && \ + make install PREFIX="${PREFIX}" && \ rm -rf ${DIR} ## opencore-amr https://sourceforge.net/projects/opencore-amr/ @@ -527,7 +527,7 @@ RUN \ cp -r ${PREFIX}/include/libav* ${PREFIX}/include/libpostproc ${PREFIX}/include/libsw* /usr/local/include && \ mkdir -p /usr/local/lib/pkgconfig && \ for pc in ${PREFIX}/lib/pkgconfig/libav*.pc ${PREFIX}/lib/pkgconfig/libpostproc.pc ${PREFIX}/lib/pkgconfig/libsw*.pc; do \ - sed "s:${PREFIX}:/usr/local:g; s:/lib64:/lib:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ + sed "s:${PREFIX}:/usr/local:g; s:/lib64:/lib:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ done @@ -539,7 +539,7 @@ ENV LD_LIBRARY_PATH=/usr/local/lib:/usr/local/lib64 CMD ["--help"] ENTRYPOINT ["ffmpeg"] -# copy only needed files, without copying nvidia dev files +# copy only needed files, without copying nvidia dev files COPY --from=build /usr/local/bin /usr/local/bin/ COPY --from=build /usr/local/share /usr/local/share/ COPY --from=build /usr/local/lib /usr/local/lib/ diff --git a/docker/Dockerfile.ffmpeg.armv7 b/docker/Dockerfile.ffmpeg.armv7 index b56f8d909..0c40cef85 100644 --- a/docker/Dockerfile.ffmpeg.armv7 +++ b/docker/Dockerfile.ffmpeg.armv7 @@ -15,33 +15,33 @@ RUN apt-get -yqq update && \ FROM base as build -ENV FFMPEG_VERSION=4.3.1 \ - AOM_VERSION=v1.0.0 \ - FDKAAC_VERSION=0.1.5 \ - FREETYPE_VERSION=2.5.5 \ - FRIBIDI_VERSION=0.19.7 \ - KVAZAAR_VERSION=1.2.0 \ - LAME_VERSION=3.100 \ - LIBPTHREAD_STUBS_VERSION=0.4 \ - LIBVIDSTAB_VERSION=1.1.0 \ - LIBXCB_VERSION=1.13.1 \ - XCBPROTO_VERSION=1.13 \ - OGG_VERSION=1.3.2 \ - OPENCOREAMR_VERSION=0.1.5 \ - OPUS_VERSION=1.2 \ - OPENJPEG_VERSION=2.1.2 \ - THEORA_VERSION=1.1.1 \ - VORBIS_VERSION=1.3.5 \ - VPX_VERSION=1.8.0 \ - WEBP_VERSION=1.0.2 \ - X264_VERSION=20170226-2245-stable \ - X265_VERSION=3.1.1 \ - XAU_VERSION=1.0.9 \ - XORG_MACROS_VERSION=1.19.2 \ - XPROTO_VERSION=7.0.31 \ - XVID_VERSION=1.3.4 \ - LIBZMQ_VERSION=4.3.3 \ - SRC=/usr/local +ENV FFMPEG_VERSION=4.3.2 \ + AOM_VERSION=v1.0.0 \ + FDKAAC_VERSION=0.1.5 \ + FREETYPE_VERSION=2.5.5 \ + FRIBIDI_VERSION=0.19.7 \ + KVAZAAR_VERSION=1.2.0 \ + LAME_VERSION=3.100 \ + LIBPTHREAD_STUBS_VERSION=0.4 \ + LIBVIDSTAB_VERSION=1.1.0 \ + LIBXCB_VERSION=1.13.1 \ + XCBPROTO_VERSION=1.13 \ + OGG_VERSION=1.3.2 \ + OPENCOREAMR_VERSION=0.1.5 \ + OPUS_VERSION=1.2 \ + OPENJPEG_VERSION=2.1.2 \ + THEORA_VERSION=1.1.1 \ + VORBIS_VERSION=1.3.5 \ + VPX_VERSION=1.8.0 \ + WEBP_VERSION=1.0.2 \ + X264_VERSION=20170226-2245-stable \ + X265_VERSION=3.1.1 \ + XAU_VERSION=1.0.9 \ + XORG_MACROS_VERSION=1.19.2 \ + XPROTO_VERSION=7.0.31 \ + XVID_VERSION=1.3.4 \ + LIBZMQ_VERSION=4.3.3 \ + SRC=/usr/local ARG FREETYPE_SHA256SUM="5d03dd76c2171a7601e9ce10551d52d4471cf92cd205948e60289251daddffa8 freetype-2.5.5.tar.gz" ARG FRIBIDI_SHA256SUM="3fc96fa9473bd31dcb5500bdf1aa78b337ba13eb8c301e7c28923fea982453a8 0.19.7.tar.gz" @@ -60,30 +60,30 @@ ARG PREFIX=/opt/ffmpeg ARG LD_LIBRARY_PATH="/opt/ffmpeg/lib:/opt/ffmpeg/lib64:/usr/lib64:/usr/lib:/lib64:/lib:/opt/vc/lib" -RUN buildDeps="autoconf \ - automake \ - cmake \ - curl \ - bzip2 \ - libexpat1-dev \ - g++ \ - gcc \ - git \ - gperf \ - libtool \ - make \ - nasm \ - perl \ - pkg-config \ - python \ - sudo \ - libssl-dev \ - yasm \ - linux-headers-raspi2 \ - libomxil-bellagio-dev \ - libx265-dev \ - libaom-dev \ - zlib1g-dev" && \ +RUN buildDeps="autoconf \ + automake \ + cmake \ + curl \ + bzip2 \ + libexpat1-dev \ + g++ \ + gcc \ + git \ + gperf \ + libtool \ + make \ + nasm \ + perl \ + pkg-config \ + python \ + sudo \ + libssl-dev \ + yasm \ + linux-headers-raspi2 \ + libomxil-bellagio-dev \ + libx265-dev \ + libaom-dev \ + zlib1g-dev" && \ apt-get -yqq update && \ apt-get install -yq --no-install-recommends ${buildDeps} ## opencore-amr https://sourceforge.net/projects/opencore-amr/ @@ -471,7 +471,7 @@ RUN \ cp -r ${PREFIX}/include/libav* ${PREFIX}/include/libpostproc ${PREFIX}/include/libsw* /usr/local/include && \ mkdir -p /usr/local/lib/pkgconfig && \ for pc in ${PREFIX}/lib/pkgconfig/libav*.pc ${PREFIX}/lib/pkgconfig/libpostproc.pc ${PREFIX}/lib/pkgconfig/libsw*.pc; do \ - sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ + sed "s:${PREFIX}:/usr/local:g" <"$pc" >/usr/local/lib/pkgconfig/"${pc##*/}"; \ done FROM base AS release diff --git a/docker/Dockerfile.nginx b/docker/Dockerfile.nginx new file mode 100644 index 000000000..72e15f8e0 --- /dev/null +++ b/docker/Dockerfile.nginx @@ -0,0 +1,52 @@ +FROM ubuntu:20.04 AS base + +ENV DEBIAN_FRONTEND=noninteractive +RUN apt-get -yqq update && \ + apt-get install -yq --no-install-recommends ca-certificates expat libgomp1 && \ + apt-get autoremove -y && \ + apt-get clean -y + +FROM base as build + +ARG NGINX_VERSION=1.18.0 +ARG VOD_MODULE_VERSION=1.28 +ARG SECURE_TOKEN_MODULE_VERSION=1.4 +ARG RTMP_MODULE_VERSION=1.2.1 + +RUN cp /etc/apt/sources.list /etc/apt/sources.list~ \ + && sed -Ei 's/^# deb-src /deb-src /' /etc/apt/sources.list \ + && apt-get update + +RUN apt-get -yqq build-dep nginx + +RUN apt-get -yqq install --no-install-recommends curl \ + && mkdir /tmp/nginx \ + && curl -sL https://nginx.org/download/nginx-${NGINX_VERSION}.tar.gz | tar -C /tmp/nginx -zx --strip-components=1 \ + && mkdir /tmp/nginx-vod-module \ + && curl -sL https://github.com/kaltura/nginx-vod-module/archive/refs/tags/${VOD_MODULE_VERSION}.tar.gz | tar -C /tmp/nginx-vod-module -zx --strip-components=1 \ + # Patch MAX_CLIPS to allow more clips to be added than the default 128 + && sed -i 's/MAX_CLIPS (128)/MAX_CLIPS (1080)/g' /tmp/nginx-vod-module/vod/media_set.h \ + && mkdir /tmp/nginx-secure-token-module \ + && curl -sL https://github.com/kaltura/nginx-secure-token-module/archive/refs/tags/${SECURE_TOKEN_MODULE_VERSION}.tar.gz | tar -C /tmp/nginx-secure-token-module -zx --strip-components=1 \ + && mkdir /tmp/nginx-rtmp-module \ + && curl -sL https://github.com/arut/nginx-rtmp-module/archive/refs/tags/v${RTMP_MODULE_VERSION}.tar.gz | tar -C /tmp/nginx-rtmp-module -zx --strip-components=1 + +WORKDIR /tmp/nginx + +RUN ./configure --prefix=/usr/local/nginx \ + --with-file-aio \ + --with-http_sub_module \ + --with-http_ssl_module \ + --with-threads \ + --add-module=../nginx-vod-module \ + --add-module=../nginx-secure-token-module \ + --add-module=../nginx-rtmp-module \ + --with-cc-opt="-O3 -Wno-error=implicit-fallthrough" + +RUN make && make install +RUN rm -rf /usr/local/nginx/html /usr/local/nginx/conf/*.default + +FROM base +COPY --from=build /usr/local/nginx /usr/local/nginx +ENTRYPOINT ["/usr/local/nginx/sbin/nginx"] +CMD ["-g", "daemon off;"] \ No newline at end of file diff --git a/docker/Dockerfile.wheels b/docker/Dockerfile.wheels index 278d989e0..a6fa222ec 100644 --- a/docker/Dockerfile.wheels +++ b/docker/Dockerfile.wheels @@ -34,8 +34,7 @@ RUN pip3 wheel --wheel-dir=/wheels \ matplotlib \ click \ setproctitle \ - peewee \ - gevent + peewee FROM scratch diff --git a/docker/rootfs/etc/services.d/nginx/finish b/docker/rootfs/etc/services.d/nginx/finish new file mode 100644 index 000000000..24482e77f --- /dev/null +++ b/docker/rootfs/etc/services.d/nginx/finish @@ -0,0 +1,5 @@ +#!/usr/bin/execlineb -S1 +if { s6-test ${1} -ne 0 } +if { s6-test ${1} -ne 256 } + +s6-svscanctl -t /var/run/s6/services \ No newline at end of file diff --git a/docker/rootfs/etc/services.d/nginx/run b/docker/rootfs/etc/services.d/nginx/run new file mode 100644 index 000000000..5aba51c91 --- /dev/null +++ b/docker/rootfs/etc/services.d/nginx/run @@ -0,0 +1,2 @@ +#!/usr/bin/execlineb -P +/usr/local/nginx/sbin/nginx \ No newline at end of file diff --git a/nginx/nginx.conf b/docker/rootfs/usr/local/nginx/conf/nginx.conf similarity index 70% rename from nginx/nginx.conf rename to docker/rootfs/usr/local/nginx/conf/nginx.conf index 51842cb70..bd8826282 100644 --- a/nginx/nginx.conf +++ b/docker/rootfs/usr/local/nginx/conf/nginx.conf @@ -1,23 +1,23 @@ +daemon off; +user root; worker_processes 1; -error_log /var/log/nginx/error.log warn; +error_log /usr/local/nginx/logs/error.log warn; pid /var/run/nginx.pid; -load_module "modules/ngx_rtmp_module.so"; - events { worker_connections 1024; } http { - include /etc/nginx/mime.types; + include mime.types; default_type application/octet-stream; log_format main '$remote_addr - $remote_user [$time_local] "$request" ' '$status $body_bytes_sent "$http_referer" ' '"$http_user_agent" "$http_x_forwarded_for"'; - access_log /var/log/nginx/access.log main; + access_log /usr/local/nginx/logs/access.log main; sendfile on; @@ -34,9 +34,56 @@ http { keepalive 1024; } + upstream mqtt_ws { + server localhost:5002; + keepalive 1024; + } + + upstream jsmpeg { + server localhost:8082; + keepalive 1024; + } + server { listen 5000; + # vod settings + vod_base_url ''; + vod_segments_base_url ''; + vod_mode mapped; + vod_max_mapping_response_size 1m; + vod_upstream_location /api; + vod_align_segments_to_key_frames on; + vod_manifest_segment_durations_mode accurate; + + # vod caches + vod_metadata_cache metadata_cache 512m; + vod_mapping_cache mapping_cache 5m; + + # gzip manifests + gzip on; + gzip_types application/vnd.apple.mpegurl; + + # file handle caching / aio + open_file_cache max=1000 inactive=5m; + open_file_cache_valid 2m; + open_file_cache_min_uses 1; + open_file_cache_errors on; + aio on; + + location /vod/ { + vod hls; + + secure_token $args; + secure_token_types application/vnd.apple.mpegurl; + + add_header Access-Control-Allow-Headers '*'; + add_header Access-Control-Expose-Headers 'Server,range,Content-Length,Content-Range'; + add_header Access-Control-Allow-Methods 'GET, HEAD, OPTIONS'; + add_header Access-Control-Allow-Origin '*'; + expires -1; + } + location /stream/ { add_header 'Cache-Control' 'no-cache'; add_header 'Access-Control-Allow-Origin' "$http_origin" always; @@ -81,6 +128,11 @@ http { root /media/frigate; } + location /cache/ { + internal; # This tells nginx it's not accessible from the outside + alias /tmp/cache/; + } + location /recordings/ { add_header 'Access-Control-Allow-Origin' "$http_origin" always; add_header 'Access-Control-Allow-Credentials' 'true'; @@ -103,7 +155,15 @@ http { } location /ws { - proxy_pass http://frigate_api/ws; + proxy_pass http://mqtt_ws/; + proxy_http_version 1.1; + proxy_set_header Upgrade $http_upgrade; + proxy_set_header Connection "Upgrade"; + proxy_set_header Host $host; + } + + location /live/ { + proxy_pass http://jsmpeg/; proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection "Upgrade"; @@ -112,6 +172,7 @@ http { location /api/ { add_header 'Access-Control-Allow-Origin' '*'; + add_header 'Access-Control-Allow-Methods' 'GET, POST, PUT, DELETE, OPTIONS'; add_header Cache-Control "no-store"; proxy_pass http://frigate_api/; proxy_pass_request_headers on; diff --git a/docs/docs/configuration/advanced.md b/docs/docs/configuration/advanced.md index 7efcfb680..18521b7d5 100644 --- a/docs/docs/configuration/advanced.md +++ b/docs/docs/configuration/advanced.md @@ -1,50 +1,11 @@ --- id: advanced -title: Advanced -sidebar_label: Advanced +title: Advanced Options +sidebar_label: Advanced Options --- ## Advanced configuration -### `motion` - -Global motion detection config. These may also be defined at the camera level. - -```yaml -motion: - # Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below) - # Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive. - # The value should be between 1 and 255. - threshold: 25 - # Optional: Minimum size in pixels in the resized motion image that counts as motion - # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will make motion detection more sensitive to smaller - # moving objects. - contour_area: 100 - # Optional: Alpha value passed to cv2.accumulateWeighted when averaging the motion delta across multiple frames (default: shown below) - # Higher values mean the current frame impacts the delta a lot, and a single raindrop may register as motion. - # Too low and a fast moving person wont be detected as motion. - delta_alpha: 0.2 - # Optional: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below) - # Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster. - # Low values will cause things like moving shadows to be detected as motion for longer. - # https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/ - frame_alpha: 0.2 - # Optional: Height of the resized motion frame (default: 1/6th of the original frame height) - # This operates as an efficient blur alternative. Higher values will result in more granular motion detection at the expense of higher CPU usage. - # Lower values result in less CPU, but small changes may not register as motion. - frame_height: 180 -``` - -### `detect` - -Global object detection settings. These may also be defined at the camera level. - -```yaml -detect: - # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate) - max_disappeared: 25 -``` - ### `logger` Change the default log level for troubleshooting purposes. @@ -72,48 +33,32 @@ Examples of available modules are: ### `environment_vars` -This section can be used to set environment variables for those unable to modify the environment of the container (ie. within Hass.io) - -```yaml -environment_vars: - EXAMPLE_VAR: value -``` +This section can be used to set environment variables for those unable to modify the environment of the container (ie. within HassOS) ### `database` -Event and clip information is managed in a sqlite database at `/media/frigate/clips/frigate.db`. If that database is deleted, clips will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant. +Event and recording information is managed in a sqlite database at `/media/frigate/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant. -If you are storing your clips on a network share (SMB, NFS, etc), you may get a `database is locked` error message on startup. You can customize the location of the database in the config if necessary. +If you are storing your database on a network share (SMB, NFS, etc), you may get a `database is locked` error message on startup. You can customize the location of the database in the config if necessary. -This may need to be in a custom location if network storage is used for clips. - -```yaml -database: - path: /media/frigate/clips/frigate.db -``` - -### `detectors` - -```yaml -detectors: - # Required: name of the detector - coral: - # Required: type of the detector - # Valid values are 'edgetpu' (requires device property below) and 'cpu'. - type: edgetpu - # Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api - device: usb - # Optional: num_threads value passed to the tflite.Interpreter (default: shown below) - # This value is only used for CPU types - num_threads: 3 -``` +This may need to be in a custom location if network storage is used for the media folder. ### `model` +If using a custom model, the width and height will need to be specified. + +The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model. + ```yaml model: - # Required: height of the trained model - height: 320 - # Required: width of the trained model - width: 320 + labelmap: + 2: vehicle + 3: vehicle + 5: vehicle + 7: vehicle + 15: animal + 16: animal + 17: animal ``` + +Note that if you rename objects in the labelmap, you will also need to update your `objects -> track` list as well. diff --git a/docs/docs/configuration/camera_specific.md b/docs/docs/configuration/camera_specific.md new file mode 100644 index 000000000..b737a5605 --- /dev/null +++ b/docs/docs/configuration/camera_specific.md @@ -0,0 +1,87 @@ +--- +id: camera_specific +title: Camera Specific Configurations +--- + +### MJPEG Cameras + +The input and output parameters need to be adjusted for MJPEG cameras + +```yaml +input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -use_wallclock_as_timestamps 1 +``` + +Note that mjpeg cameras require encoding the video into h264 for recording, and rtmp roles. This will use significantly more CPU than if the cameras supported h264 feeds directly. + +```yaml +output_args: + record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v libx264 -an + rtmp: -c:v libx264 -an -f flv +``` + +### RTMP Cameras + +The input parameters need to be adjusted for RTMP cameras + +```yaml +ffmpeg: + input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rw_timeout 5000000 -use_wallclock_as_timestamps 1 -f live_flv +``` + +### Reolink 410/520 (possibly others) + +According to [this discussion](https://github.com/blakeblackshear/frigate/issues/1713#issuecomment-932976305), the http video streams seem to be the most reliable for Reolink. + +```yaml +cameras: + reolink: + ffmpeg: + hwaccel_args: + input_args: + - -avoid_negative_ts + - make_zero + - -fflags + - nobuffer+genpts+discardcorrupt + - -flags + - low_delay + - -strict + - experimental + - -analyzeduration + - 1000M + - -probesize + - 1000M + - -rw_timeout + - "5000000" + inputs: + - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password + roles: + - record + - rtmp + - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password + roles: + - detect + detect: + width: 640 + height: 480 + fps: 7 +``` + +![Resolutions](/img/reolink-settings.png) + +### Blue Iris RTSP Cameras + +You will need to remove `nobuffer` flag for Blue Iris RTSP cameras + +```yaml +ffmpeg: + input_args: -avoid_negative_ts make_zero -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rtsp_transport tcp -stimeout 5000000 -use_wallclock_as_timestamps 1 +``` + +### UDP Only Cameras + +If your cameras do not support TCP connections for RTSP, you can use UDP. + +```yaml +ffmpeg: + input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport udp -stimeout 5000000 -use_wallclock_as_timestamps 1 +``` diff --git a/docs/docs/configuration/cameras.md b/docs/docs/configuration/cameras.md index 5184e516c..ef6e05dd2 100644 --- a/docs/docs/configuration/cameras.md +++ b/docs/docs/configuration/cameras.md @@ -5,18 +5,15 @@ title: Cameras ## Setting Up Camera Inputs -Up to 4 inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create clips from a higher resolution stream, or vice versa. +Several inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create recordings from a higher resolution stream, or vice versa. Each role can only be assigned to one input per camera. The options for roles are as follows: -| Role | Description | -| -------- | ------------------------------------------------------------------------------------ | -| `detect` | Main feed for object detection | -| `clips` | Clips of events from objects detected in the `detect` feed. [docs](#recording-clips) | -| `record` | Saves 60 second segments of the video feed. [docs](#247-recordings) | -| `rtmp` | Broadcast as an RTMP feed for other services to consume. [docs](#rtmp-streams) | - -### Example +| Role | Description | +| -------- | ----------------------------------------------------------------------------------------------- | +| `detect` | Main feed for object detection | +| `record` | Saves segments of the video feed based on configuration settings. [docs](/configuration/record) | +| `rtmp` | Broadcast as an RTMP feed for other services to consume. [docs](/configuration/rtmp) | ```yaml mqtt: @@ -31,459 +28,18 @@ cameras: - rtmp - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/live roles: - - clips - record - width: 1280 - height: 720 - fps: 5 -``` - -`width`, `height`, and `fps` are only used for the `detect` role. Other streams are passed through, so there is no need to specify the resolution. - -## Masks & Zones - -### Masks - -Masks are used to ignore initial detection in areas of your camera's field of view. - -There are two types of masks available: - -- **Motion masks**: Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the video feed with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. Over masking will make it more difficult for objects to be tracked. To see this effect, create a mask, and then watch the video feed with `Motion Boxes` enabled again. -- **Object filter masks**: Object filter masks are used to filter out false positives for a given object type. These should be used to filter any areas where it is not possible for an object of that type to be. The bottom center of the detected object's bounding box is evaluated against the mask. If it is in a masked area, it is assumed to be a false positive. For example, you may want to mask out rooftops, walls, the sky, treetops for people. For cars, masking locations other than the street or your driveway will tell frigate that anything in your yard is a false positive. - -To create a poly mask: - -1. Visit the [web UI](/usage/web) -1. Click the camera you wish to create a mask for -1. Click "Mask & Zone creator" -1. Click "Add" on the type of mask or zone you would like to create -1. Click on the camera's latest image to create a masked area. The yaml representation will be updated in real-time -1. When you've finished creating your mask, click "Copy" and paste the contents into your `config.yaml` file and restart Frigate - -Example of a finished row corresponding to the below example image: - -```yaml -motion: - mask: "0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432" -``` - -![poly](/img/example-mask-poly.png) - -```yaml -# Optional: camera level motion config -motion: - # Optional: motion mask - # NOTE: see docs for more detailed info on creating masks - mask: 0,900,1080,900,1080,1920,0,1920 -``` - -### Zones - -Zones allow you to define a specific area of the frame and apply additional filters for object types so you can determine whether or not an object is within a particular area. Zones cannot have the same name as a camera. If desired, a single zone can include multiple cameras if you have multiple cameras covering the same area by configuring zones with the same name for each camera. - -During testing, `draw_zones` should be set in the config to draw the zone on the frames so you can adjust as needed. The zone line will increase in thickness when any object enters the zone. - -To create a zone, follow the same steps above for a "Motion mask", but use the section of the web UI for creating a zone instead. - -```yaml -# Optional: zones for this camera -zones: - # Required: name of the zone - # NOTE: This must be different than any camera names, but can match with another zone on another - # camera. - front_steps: - # Required: List of x,y coordinates to define the polygon of the zone. - # NOTE: Coordinates can be generated at https://www.image-map.net/ - coordinates: 545,1077,747,939,788,805 - # Optional: Zone level object filters. - # NOTE: The global and camera filters are applied upstream. - filters: - person: - min_area: 5000 - max_area: 100000 - threshold: 0.7 -``` - -## Objects - -For a list of available objects, see the [objects documentation](./objects.mdx). - -```yaml -# Optional: Camera level object filters config. -objects: - track: - - person - - car - # Optional: mask to prevent all object types from being detected in certain areas (default: no mask) - # Checks based on the bottom center of the bounding box of the object. - # NOTE: This mask is COMBINED with the object type specific mask below - mask: 0,0,1000,0,1000,200,0,200 - filters: - person: - min_area: 5000 - max_area: 100000 - min_score: 0.5 - threshold: 0.7 - # Optional: mask to prevent this object type from being detected in certain areas (default: no mask) - # Checks based on the bottom center of the bounding box of the object - mask: 0,0,1000,0,1000,200,0,200 -``` - -## Clips - -Frigate can save video clips without any CPU overhead for encoding by simply copying the stream directly with FFmpeg. It leverages FFmpeg's segment functionality to maintain a cache of video for each camera. The cache files are written to disk at `/tmp/cache` and do not introduce memory overhead. When an object is being tracked, it will extend the cache to ensure it can assemble a clip when the event ends. Once the event ends, it again uses FFmpeg to assemble a clip by combining the video clips without any encoding by the CPU. Assembled clips are are saved to `/media/frigate/clips`. Clips are retained according to the retention settings defined on the config for each object type. - -These clips will not be playable in the web UI or in Home Assistant's media browser unless your camera sends video as h264. - -:::caution -Previous versions of frigate included `-vsync drop` in input parameters. This is not compatible with FFmpeg's segment feature and must be removed from your input parameters if you have overrides set. -::: - -```yaml -clips: - # Required: enables clips for the camera (default: shown below) - # This value can be set via MQTT and will be updated in startup based on retained value - enabled: False - # Optional: Number of seconds before the event to include in the clips (default: shown below) - pre_capture: 5 - # Optional: Number of seconds after the event to include in the clips (default: shown below) - post_capture: 5 - # Optional: Objects to save clips for. (default: all tracked objects) - objects: - - person - # Optional: Restrict clips to objects that entered any of the listed zones (default: no required zones) - required_zones: [] - # Optional: Camera override for retention settings (default: global values) - retain: - # Required: Default retention days (default: shown below) - default: 10 - # Optional: Per object retention days - objects: - person: 15 -``` - -## Snapshots - -Frigate can save a snapshot image to `/media/frigate/clips` for each event named as `-.jpg`. - -```yaml -# Optional: Configuration for the jpg snapshots written to the clips directory for each event -snapshots: - # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below) - # This value can be set via MQTT and will be updated in startup based on retained value - enabled: False - # Optional: print a timestamp on the snapshots (default: shown below) - timestamp: False - # Optional: draw bounding box on the snapshots (default: shown below) - bounding_box: False - # Optional: crop the snapshot (default: shown below) - crop: False - # Optional: height to resize the snapshot to (default: original size) - height: 175 - # Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones) - required_zones: [] - # Optional: Camera override for retention settings (default: global values) - retain: - # Required: Default retention days (default: shown below) - default: 10 - # Optional: Per object retention days - objects: - person: 15 -``` - -## 24/7 Recordings - -24/7 recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM/DD/HH//MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding and are available in Home Assistant's media browser. Each camera supports a configurable retention policy in the config. - -:::caution -Previous versions of frigate included `-vsync drop` in input parameters. This is not compatible with FFmpeg's segment feature and must be removed from your input parameters if you have overrides set. -::: - -```yaml -# Optional: 24/7 recording configuration -record: - # Optional: Enable recording (default: global setting) - enabled: False - # Optional: Number of days to retain (default: global setting) - retain_days: 30 -``` - -## RTMP streams - -Frigate can re-stream your video feed as a RTMP feed for other applications such as Home Assistant to utilize it at `rtmp:///live/`. Port 1935 must be open. This allows you to use a video feed for detection in frigate and Home Assistant live view at the same time without having to make two separate connections to the camera. The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate. - -Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization. - -## Full example - -The following is a full example of all of the options together for a camera configuration - -```yaml -cameras: - # Required: name of the camera - back: - # Required: ffmpeg settings for the camera - ffmpeg: - # Required: A list of input streams for the camera. See documentation for more information. - inputs: - # Required: the path to the stream - # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {} - - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2 - # Required: list of roles for this stream. valid values are: detect,record,clips,rtmp - # NOTICE: In addition to assigning the record, clips, and rtmp roles, - # they must also be enabled in the camera config. - roles: - - detect - - rtmp - # Optional: stream specific global args (default: inherit) - global_args: - # Optional: stream specific hwaccel args (default: inherit) - hwaccel_args: - # Optional: stream specific input args (default: inherit) - input_args: - # Optional: camera specific global args (default: inherit) - global_args: - # Optional: camera specific hwaccel args (default: inherit) - hwaccel_args: - # Optional: camera specific input args (default: inherit) - input_args: - # Optional: camera specific output args (default: inherit) - output_args: - - # Required: width of the frame for the input with the detect role - width: 1280 - # Required: height of the frame for the input with the detect role - height: 720 - # Optional: desired fps for your camera for the input with the detect role - # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera. - # Frigate will attempt to autodetect if not specified. - fps: 5 - - # Optional: camera level motion config - motion: - # Optional: motion mask - # NOTE: see docs for more detailed info on creating masks - mask: 0,900,1080,900,1080,1920,0,1920 - - # Optional: timeout for highest scoring image before allowing it - # to be replaced by a newer image. (default: shown below) - best_image_timeout: 60 - - # Optional: zones for this camera - zones: - # Required: name of the zone - # NOTE: This must be different than any camera names, but can match with another zone on another - # camera. - front_steps: - # Required: List of x,y coordinates to define the polygon of the zone. - # NOTE: Coordinates can be generated at https://www.image-map.net/ - coordinates: 545,1077,747,939,788,805 - # Optional: Zone level object filters. - # NOTE: The global and camera filters are applied upstream. - filters: - person: - min_area: 5000 - max_area: 100000 - threshold: 0.7 - - # Optional: Camera level detect settings detect: - # Optional: enables detection for the camera (default: True) - # This value can be set via MQTT and will be updated in startup based on retained value - enabled: True - # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate) - max_disappeared: 25 - - # Optional: save clips configuration - clips: - # Required: enables clips for the camera (default: shown below) - # This value can be set via MQTT and will be updated in startup based on retained value - enabled: False - # Optional: Number of seconds before the event to include in the clips (default: shown below) - pre_capture: 5 - # Optional: Number of seconds after the event to include in the clips (default: shown below) - post_capture: 5 - # Optional: Objects to save clips for. (default: all tracked objects) - objects: - - person - # Optional: Restrict clips to objects that entered any of the listed zones (default: no required zones) - required_zones: [] - # Optional: Camera override for retention settings (default: global values) - retain: - # Required: Default retention days (default: shown below) - default: 10 - # Optional: Per object retention days - objects: - person: 15 - - # Optional: 24/7 recording configuration - record: - # Optional: Enable recording (default: global setting) - enabled: False - # Optional: Number of days to retain (default: global setting) - retain_days: 30 - - # Optional: RTMP re-stream configuration - rtmp: - # Required: Enable the live stream (default: True) - enabled: True - - # Optional: Configuration for the jpg snapshots written to the clips directory for each event - snapshots: - # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below) - # This value can be set via MQTT and will be updated in startup based on retained value - enabled: False - # Optional: print a timestamp on the snapshots (default: shown below) - timestamp: False - # Optional: draw bounding box on the snapshots (default: shown below) - bounding_box: False - # Optional: crop the snapshot (default: shown below) - crop: False - # Optional: height to resize the snapshot to (default: original size) - height: 175 - # Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones) - required_zones: [] - # Optional: Camera override for retention settings (default: global values) - retain: - # Required: Default retention days (default: shown below) - default: 10 - # Optional: Per object retention days - objects: - person: 15 - - # Optional: Configuration for the jpg snapshots published via MQTT - mqtt: - # Optional: Enable publishing snapshot via mqtt for camera (default: shown below) - # NOTE: Only applies to publishing image data to MQTT via 'frigate///snapshot'. - # All other messages will still be published. - enabled: True - # Optional: print a timestamp on the snapshots (default: shown below) - timestamp: True - # Optional: draw bounding box on the snapshots (default: shown below) - bounding_box: True - # Optional: crop the snapshot (default: shown below) - crop: True - # Optional: height to resize the snapshot to (default: shown below) - height: 270 - # Optional: Restrict mqtt messages to objects that entered any of the listed zones (default: no required zones) - required_zones: [] - - # Optional: Camera level object filters config. - objects: - track: - - person - - car - # Optional: mask to prevent all object types from being detected in certain areas (default: no mask) - # Checks based on the bottom center of the bounding box of the object. - # NOTE: This mask is COMBINED with the object type specific mask below - mask: 0,0,1000,0,1000,200,0,200 - filters: - person: - min_area: 5000 - max_area: 100000 - min_score: 0.5 - threshold: 0.7 - # Optional: mask to prevent this object type from being detected in certain areas (default: no mask) - # Checks based on the bottom center of the bounding box of the object - mask: 0,0,1000,0,1000,200,0,200 + width: 1280 + height: 720 ``` -## Camera specific configuration - -### MJPEG Cameras - -The input and output parameters need to be adjusted for MJPEG cameras +Additional cameras are simply added to the config under the `cameras` entry. ```yaml -input_args: - - -avoid_negative_ts - - make_zero - - -fflags - - nobuffer - - -flags - - low_delay - - -strict - - experimental - - -fflags - - +genpts+discardcorrupt - - -r - - "3" # <---- adjust depending on your desired frame rate from the mjpeg image - - -use_wallclock_as_timestamps - - "1" -``` - -Note that mjpeg cameras require encoding the video into h264 for clips, recording, and rtmp roles. This will use significantly more CPU than if the cameras supported h264 feeds directly. - -```yaml -output_args: - record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v libx264 -an - clips: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v libx264 -an - rtmp: -c:v libx264 -an -f flv -``` - -### RTMP Cameras - -The input parameters need to be adjusted for RTMP cameras - -```yaml -ffmpeg: - input_args: - - -avoid_negative_ts - - make_zero - - -fflags - - nobuffer - - -flags - - low_delay - - -strict - - experimental - - -fflags - - +genpts+discardcorrupt - - -use_wallclock_as_timestamps - - "1" -``` - -### Reolink 410/520 (possibly others) - -Several users have reported success with the rtmp video from Reolink cameras. - -```yaml -ffmpeg: - input_args: - - -avoid_negative_ts - - make_zero - - -fflags - - nobuffer - - -flags - - low_delay - - -strict - - experimental - - -fflags - - +genpts+discardcorrupt - - -rw_timeout - - "5000000" - - -use_wallclock_as_timestamps - - "1" -``` - -### Blue Iris RTSP Cameras - -You will need to remove `nobuffer` flag for Blue Iris RTSP cameras - -```yaml -ffmpeg: - input_args: - - -avoid_negative_ts - - make_zero - - -flags - - low_delay - - -strict - - experimental - - -fflags - - +genpts+discardcorrupt - - -rtsp_transport - - tcp - - -stimeout - - "5000000" - - -use_wallclock_as_timestamps - - "1" +mqtt: ... +cameras: + back: ... + front: ... + side: ... ``` diff --git a/docs/docs/configuration/detectors.md b/docs/docs/configuration/detectors.md index 58ec474ef..176138f65 100644 --- a/docs/docs/configuration/detectors.md +++ b/docs/docs/configuration/detectors.md @@ -3,13 +3,13 @@ id: detectors title: Detectors --- -The default config will look for a USB Coral device. If you do not have a Coral, you will need to configure a CPU detector. If you have PCI or multiple Coral devices, you need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras. +By default, Frigate will use a single CPU detector. If you have a Coral, you will need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras. Frigate supports `edgetpu` and `cpu` as detector types. The device value should be specified according to the [Documentation for the TensorFlow Lite Python API](https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api). **Note**: There is no support for Nvidia GPUs to perform object detection with tensorflow. It can be used for ffmpeg decoding, but not object detection. -Single USB Coral: +### Single USB Coral ```yaml detectors: @@ -18,7 +18,7 @@ detectors: device: usb ``` -Multiple USB Corals: +### Multiple USB Corals ```yaml detectors: @@ -30,16 +30,16 @@ detectors: device: usb:1 ``` -Native Coral (Dev Board): +### Native Coral (Dev Board) ```yaml detectors: coral: type: edgetpu - device: '' + device: "" ``` -Multiple PCIE/M.2 Corals: +### Multiple PCIE/M.2 Corals ```yaml detectors: @@ -51,7 +51,7 @@ detectors: device: pci:1 ``` -Mixing Corals: +### Mixing Corals ```yaml detectors: @@ -63,12 +63,16 @@ detectors: device: pci ``` -CPU Detectors (not recommended): +### CPU Detectors (not recommended) ```yaml detectors: cpu1: type: cpu + num_threads: 3 cpu2: type: cpu + num_threads: 3 ``` + +When using CPU detectors, you can add a CPU detector per camera. Adding more detectors than the number of cameras should not improve performance. diff --git a/docs/docs/configuration/hardware_acceleration.md b/docs/docs/configuration/hardware_acceleration.md new file mode 100644 index 000000000..e2153f4f2 --- /dev/null +++ b/docs/docs/configuration/hardware_acceleration.md @@ -0,0 +1,70 @@ +--- +id: hardware_acceleration +title: Hardware Acceleration +--- + +It is recommended to update your configuration to enable hardware accelerated decoding in ffmpeg. Depending on your system, these parameters may not be compatible. More information on hardware accelerated decoding for ffmpeg can be found here: https://trac.ffmpeg.org/wiki/HWAccelIntro + +### Raspberry Pi 3/4 (32-bit OS) + +Ensure you increase the allocated RAM for your GPU to at least 128 (raspi-config > Performance Options > GPU Memory). +**NOTICE**: If you are using the addon, you may need to turn off `Protection mode` for hardware acceleration. + +```yaml +ffmpeg: + hwaccel_args: + - -c:v + - h264_mmal +``` + +### Raspberry Pi 3/4 (64-bit OS) + +**NOTICE**: If you are using the addon, you may need to turn off `Protection mode` for hardware acceleration. + +```yaml +ffmpeg: + hwaccel_args: + - -c:v + - h264_v4l2m2m +``` + +### Intel-based CPUs (<10th Generation) via Quicksync + +```yaml +ffmpeg: + hwaccel_args: + - -hwaccel + - vaapi + - -hwaccel_device + - /dev/dri/renderD128 + - -hwaccel_output_format + - yuv420p +``` + +### Intel-based CPUs (>=10th Generation) via Quicksync + +```yaml +ffmpeg: + hwaccel_args: + - -hwaccel + - qsv + - -qsv_device + - /dev/dri/renderD128 +``` + +### AMD/ATI GPUs (Radeon HD 2000 and newer GPUs) via libva-mesa-driver + +**Note:** You also need to set `LIBVA_DRIVER_NAME=radeonsi` as an environment variable on the container. + +```yaml +ffmpeg: + hwaccel_args: + - -hwaccel + - vaapi + - -hwaccel_device + - /dev/dri/renderD128 +``` + +### NVIDIA GPU + +NVIDIA GPU based decoding via NVDEC is supported, but requires special configuration. See the [NVIDIA NVDEC documentation](/configuration/nvdec) for more details. diff --git a/docs/docs/configuration/index.md b/docs/docs/configuration/index.md index bdffb16ef..ed0f6b3eb 100644 --- a/docs/docs/configuration/index.md +++ b/docs/docs/configuration/index.md @@ -1,13 +1,13 @@ --- id: index -title: Configuration +title: Configuration File --- -For HassOS installations, the default location for the config file is `/config/frigate.yml`. +For Home Assistant Addon installations, the config file needs to be in the root of your Home Assistant config directory (same location as `configuration.yaml`) and named `frigate.yml`. -For all other installations, the default location for the config file is '/config/config.yml'. This can be overridden with the `CONFIG_FILE` environment variable. Camera specific ffmpeg parameters are documented [here](cameras.md). +For all other installation types, the config file should be mapped to `/config/config.yml` inside the container. -It is recommended to start with a minimal configuration and add to it: +It is recommended to start with a minimal configuration and add to it as described in [this guide](/guides/getting_started): ```yaml mqtt: @@ -20,14 +20,18 @@ cameras: roles: - detect - rtmp - width: 1280 - height: 720 - fps: 5 + detect: + width: 1280 + height: 720 ``` -## Required +### Full configuration reference: -## `mqtt` +:::caution + +It is not recommended to copy this full configuration file. Only specify values that are different from the defaults. Configuration options and default values may change in future versions. + +::: ```yaml mqtt: @@ -36,10 +40,10 @@ mqtt: # Optional: port (default: shown below) port: 1883 # Optional: topic prefix (default: shown below) - # WARNING: must be unique if you are running multiple instances + # NOTE: must be unique if you are running multiple instances topic_prefix: frigate # Optional: client id (default: shown below) - # WARNING: must be unique if you are running multiple instances + # NOTE: must be unique if you are running multiple instances client_id: frigate # Optional: user user: mqtt_user @@ -47,56 +51,82 @@ mqtt: # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}. # eg. password: '{FRIGATE_MQTT_PASSWORD}' password: password + # Optional: tls_ca_certs for enabling TLS using self-signed certs (default: None) + tls_ca_certs: /path/to/ca.crt + # Optional: tls_client_cert and tls_client key in order to use self-signed client + # certificates (default: None) + # NOTE: certificate must not be password-protected + # do not set user and password when using a client certificate + tls_client_cert: /path/to/client.crt + tls_client_key: /path/to/client.key + # Optional: tls_insecure (true/false) for enabling TLS verification of + # the server hostname in the server certificate (default: None) + tls_insecure: false # Optional: interval in seconds for publishing stats (default: shown below) stats_interval: 60 -``` -## `cameras` +# Optional: Detectors configuration. Defaults to a single CPU detector +detectors: + # Required: name of the detector + coral: + # Required: type of the detector + # Valid values are 'edgetpu' (requires device property below) and 'cpu'. + type: edgetpu + # Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api + device: usb + # Optional: num_threads value passed to the tflite.Interpreter (default: shown below) + # This value is only used for CPU types + num_threads: 3 -Each of your cameras must be configured. The following is the minimum required to register a camera in Frigate. Check the [camera configuration page](cameras.md) for a complete list of options. +# Optional: Database configuration +database: + # The path to store the SQLite DB (default: shown below) + path: /media/frigate/frigate.db -```yaml -cameras: - # Name of your camera - front_door: - ffmpeg: - inputs: - - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2 - roles: - - detect - - rtmp - width: 1280 - height: 720 - fps: 5 -``` +# Optional: model modifications +model: + # Optional: path to the model (default: automatic based on detector) + path: /edgetpu_model.tflite + # Optional: path to the labelmap (default: shown below) + labelmap_path: /labelmap.txt + # Required: Object detection model input width (default: shown below) + width: 320 + # Required: Object detection model input height (default: shown below) + height: 320 + # Optional: Label name modifications. These are merged into the standard labelmap. + labelmap: + 2: vehicle -## Optional +# Optional: logger verbosity settings +logger: + # Optional: Default log verbosity (default: shown below) + default: info + # Optional: Component specific logger overrides + logs: + frigate.event: debug -### `clips` +# Optional: set environment variables +environment_vars: + EXAMPLE_VAR: value -```yaml -clips: - # Optional: Maximum length of time to retain video during long events. (default: shown below) - # NOTE: If an object is being tracked for longer than this amount of time, the cache - # will begin to expire and the resulting clip will be the last x seconds of the event. - max_seconds: 300 - # Optional: size of tmpfs mount to create for cache files (default: not set) - # mount -t tmpfs -o size={tmpfs_cache_size} tmpfs /tmp/cache - # NOTICE: Addon users must have Protection mode disabled for the addon when using this setting. - # Also, if you have mounted a tmpfs volume through docker, this value should not be set in your config. - tmpfs_cache_size: 256m - # Optional: Retention settings for clips (default: shown below) - retain: - # Required: Default retention days (default: shown below) - default: 10 - # Optional: Per object retention days - objects: - person: 15 -``` +# Optional: birdseye configuration +birdseye: + # Optional: Enable birdseye view (default: shown below) + enabled: True + # Optional: Width of the output resolution (default: shown below) + width: 1280 + # Optional: Height of the output resolution (default: shown below) + height: 720 + # Optional: Encoding quality of the mpeg1 feed (default: shown below) + # 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources. + quality: 8 + # Optional: Mode of the view. Available options are: objects, motion, and continuous + # objects - cameras are included if they have had a tracked object within the last 30 seconds + # motion - cameras are included if motion was detected in the last 30 seconds + # continuous - all cameras are included always + mode: objects -### `ffmpeg` - -```yaml +# Optional: ffmpeg configuration ffmpeg: # Optional: global ffmpeg args (default: shown below) global_args: -hide_banner -loglevel warning @@ -110,22 +140,36 @@ ffmpeg: # Optional: output args for detect streams (default: shown below) detect: -f rawvideo -pix_fmt yuv420p # Optional: output args for record streams (default: shown below) - record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an - # Optional: output args for clips streams (default: shown below) - clips: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an + record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an # Optional: output args for rtmp streams (default: shown below) rtmp: -c copy -f flv -``` -### `objects` +# Optional: Detect configuration +# NOTE: Can be overridden at the camera level +detect: + # Optional: width of the frame for the input with the detect role (default: shown below) + width: 1280 + # Optional: height of the frame for the input with the detect role (default: shown below) + height: 720 + # Optional: desired fps for your camera for the input with the detect role (default: shown below) + # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera. + fps: 5 + # Optional: enables detection for the camera (default: True) + # This value can be set via MQTT and will be updated in startup based on retained value + enabled: True + # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate) + max_disappeared: 25 -Can be overridden at the camera level. For a list of available objects, see the [objects documentation](./objects.mdx). - -```yaml +# Optional: Object configuration +# NOTE: Can be overridden at the camera level objects: # Optional: list of objects to track from labelmap.txt (default: shown below) track: - person + # Optional: mask to prevent all object types from being detected in certain areas (default: no mask) + # Checks based on the bottom center of the bounding box of the object. + # NOTE: This mask is COMBINED with the object type specific mask below + mask: 0,0,1000,0,1000,200,0,200 # Optional: filters to reduce false positives for specific object types filters: person: @@ -137,20 +181,207 @@ objects: min_score: 0.5 # Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below) threshold: 0.7 -``` + # Optional: mask to prevent this object type from being detected in certain areas (default: no mask) + # Checks based on the bottom center of the bounding box of the object + mask: 0,0,1000,0,1000,200,0,200 -### `record` +# Optional: Motion configuration +# NOTE: Can be overridden at the camera level +motion: + # Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below) + # Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive. + # The value should be between 1 and 255. + threshold: 25 + # Optional: Minimum size in pixels in the resized motion image that counts as motion (default: ~0.17% of the motion frame area) + # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will make motion detection more sensitive to smaller + # moving objects. + contour_area: 100 + # Optional: Alpha value passed to cv2.accumulateWeighted when averaging the motion delta across multiple frames (default: shown below) + # Higher values mean the current frame impacts the delta a lot, and a single raindrop may register as motion. + # Too low and a fast moving person wont be detected as motion. + delta_alpha: 0.2 + # Optional: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below) + # Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster. + # Low values will cause things like moving shadows to be detected as motion for longer. + # https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/ + frame_alpha: 0.2 + # Optional: Height of the resized motion frame (default: 1/6th of the original frame height, but no less than 180) + # This operates as an efficient blur alternative. Higher values will result in more granular motion detection at the expense of higher CPU usage. + # Lower values result in less CPU, but small changes may not register as motion. + frame_height: 180 + # Optional: motion mask + # NOTE: see docs for more detailed info on creating masks + mask: 0,900,1080,900,1080,1920,0,1920 -Can be overridden at the camera level. 24/7 recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM/DD/HH//MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding and are available in Home Assistant's media browser. Each camera supports a configurable retention policy in the config. - -:::caution -Previous versions of frigate included `-vsync drop` in input parameters. This is not compatible with FFmpeg's segment feature and must be removed from your input parameters if you have overrides set. -::: - -```yaml +# Optional: Record configuration +# NOTE: Can be overridden at the camera level record: - # Optional: Enable recording + # Optional: Enable recording (default: shown below) enabled: False - # Optional: Number of days to retain - retain_days: 30 + # Optional: Number of days to retain recordings regardless of events (default: shown below) + # NOTE: This should be set to 0 and retention should be defined in events section below + # if you only want to retain recordings of events. + retain_days: 0 + # Optional: Event recording settings + events: + # Optional: Maximum length of time to retain video during long events. (default: shown below) + # NOTE: If an object is being tracked for longer than this amount of time, the retained recordings + # will be the last x seconds of the event unless retain_days under record is > 0. + max_seconds: 300 + # Optional: Number of seconds before the event to include (default: shown below) + pre_capture: 5 + # Optional: Number of seconds after the event to include (default: shown below) + post_capture: 5 + # Optional: Objects to save recordings for. (default: all tracked objects) + objects: + - person + # Optional: Restrict recordings to objects that entered any of the listed zones (default: no required zones) + required_zones: [] + # Optional: Retention settings for recordings of events + retain: + # Required: Default retention days (default: shown below) + default: 10 + # Optional: Per object retention days + objects: + person: 15 + +# Optional: Configuration for the jpg snapshots written to the clips directory for each event +# NOTE: Can be overridden at the camera level +snapshots: + # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below) + # This value can be set via MQTT and will be updated in startup based on retained value + enabled: False + # Optional: print a timestamp on the snapshots (default: shown below) + timestamp: False + # Optional: draw bounding box on the snapshots (default: shown below) + bounding_box: False + # Optional: crop the snapshot (default: shown below) + crop: False + # Optional: height to resize the snapshot to (default: original size) + height: 175 + # Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones) + required_zones: [] + # Optional: Camera override for retention settings (default: global values) + retain: + # Required: Default retention days (default: shown below) + default: 10 + # Optional: Per object retention days + objects: + person: 15 + +# Optional: RTMP configuration +# NOTE: Can be overridden at the camera level +rtmp: + # Optional: Enable the RTMP stream (default: True) + enabled: True + +# Optional: Live stream configuration for WebUI +# NOTE: Can be overridden at the camera level +live: + # Optional: Set the height of the live stream. (default: 720) + # This must be less than or equal to the height of the detect stream. Lower resolutions + # reduce bandwidth required for viewing the live stream. Width is computed to match known aspect ratio. + height: 720 + # Optional: Set the encode quality of the live stream (default: shown below) + # 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources. + quality: 8 + +# Optional: in-feed timestamp style configuration +# NOTE: Can be overridden at the camera level +timestamp_style: + # Optional: Position of the timestamp (default: shown below) + # "tl" (top left), "tr" (top right), "bl" (bottom left), "br" (bottom right) + position: "tl" + # Optional: Format specifier conform to the Python package "datetime" (default: shown below) + # Additional Examples: + # german: "%d.%m.%Y %H:%M:%S" + format: "%m/%d/%Y %H:%M:%S" + # Optional: Color of font + color: + # All Required when color is specified (default: shown below) + red: 255 + green: 255 + blue: 255 + # Optional: Line thickness of font (default: shown below) + thickness: 2 + # Optional: Effect of lettering (default: shown below) + # None (No effect), + # "solid" (solid background in inverse color of font) + # "shadow" (shadow for font) + effect: None + +# Required +cameras: + # Required: name of the camera + back: + # Required: ffmpeg settings for the camera + ffmpeg: + # Required: A list of input streams for the camera. See documentation for more information. + inputs: + # Required: the path to the stream + # NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {} + - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2 + # Required: list of roles for this stream. valid values are: detect,record,rtmp + # NOTICE: In addition to assigning the record, and rtmp roles, + # they must also be enabled in the camera config. + roles: + - detect + - rtmp + # Optional: stream specific global args (default: inherit) + # global_args: + # Optional: stream specific hwaccel args (default: inherit) + # hwaccel_args: + # Optional: stream specific input args (default: inherit) + # input_args: + # Optional: camera specific global args (default: inherit) + # global_args: + # Optional: camera specific hwaccel args (default: inherit) + # hwaccel_args: + # Optional: camera specific input args (default: inherit) + # input_args: + # Optional: camera specific output args (default: inherit) + # output_args: + + # Optional: timeout for highest scoring image before allowing it + # to be replaced by a newer image. (default: shown below) + best_image_timeout: 60 + + # Optional: zones for this camera + zones: + # Required: name of the zone + # NOTE: This must be different than any camera names, but can match with another zone on another + # camera. + front_steps: + # Required: List of x,y coordinates to define the polygon of the zone. + # NOTE: Coordinates can be generated at https://www.image-map.net/ + coordinates: 545,1077,747,939,788,805 + # Optional: List of objects that can trigger this zone (default: all tracked objects) + objects: + - person + # Optional: Zone level object filters. + # NOTE: The global and camera filters are applied upstream. + filters: + person: + min_area: 5000 + max_area: 100000 + threshold: 0.7 + + # Optional: Configuration for the jpg snapshots published via MQTT + mqtt: + # Optional: Enable publishing snapshot via mqtt for camera (default: shown below) + # NOTE: Only applies to publishing image data to MQTT via 'frigate///snapshot'. + # All other messages will still be published. + enabled: True + # Optional: print a timestamp on the snapshots (default: shown below) + timestamp: True + # Optional: draw bounding box on the snapshots (default: shown below) + bounding_box: True + # Optional: crop the snapshot (default: shown below) + crop: True + # Optional: height to resize the snapshot to (default: shown below) + height: 270 + # Optional: jpeg encode quality (default: shown below) + quality: 70 + # Optional: Restrict mqtt messages to objects that entered any of the listed zones (default: no required zones) + required_zones: [] ``` diff --git a/docs/docs/configuration/masks.md b/docs/docs/configuration/masks.md new file mode 100644 index 000000000..92eb9c89f --- /dev/null +++ b/docs/docs/configuration/masks.md @@ -0,0 +1,77 @@ +--- +id: masks +title: Masks +--- + +There are two types of masks available: + +**Motion masks**: Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the debug feed with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. Over masking will make it more difficult for objects to be tracked. To see this effect, create a mask, and then watch the video feed with `Motion Boxes` enabled again. + +**Object filter masks**: Object filter masks are used to filter out false positives for a given object type based on location. These should be used to filter any areas where it is not possible for an object of that type to be. The bottom center of the detected object's bounding box is evaluated against the mask. If it is in a masked area, it is assumed to be a false positive. For example, you may want to mask out rooftops, walls, the sky, treetops for people. For cars, masking locations other than the street or your driveway will tell frigate that anything in your yard is a false positive. + +To create a poly mask: + +1. Visit the Web UI +1. Click the camera you wish to create a mask for +1. Select "Debug" at the top +1. Expand the "Options" below the video feed +1. Click "Mask & Zone creator" +1. Click "Add" on the type of mask or zone you would like to create +1. Click on the camera's latest image to create a masked area. The yaml representation will be updated in real-time +1. When you've finished creating your mask, click "Copy" and paste the contents into your config file and restart Frigate + +Example of a finished row corresponding to the below example image: + +```yaml +motion: + mask: "0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432" +``` + +Multiple masks can be listed. + +```yaml +motion: + mask: + - 458,1346,336,973,317,869,375,866,432 + - 0,461,3,0,1919,0,1919,843,1699,492,1344 +``` + +![poly](/img/example-mask-poly-min.png) + +### Further Clarification + +This is a response to a [question posed on reddit](https://www.reddit.com/r/homeautomation/comments/ppxdve/replacing_my_doorbell_with_a_security_camera_a_6/hd876w4?utm_source=share&utm_medium=web2x&context=3): + +It is helpful to understand a bit about how Frigate uses motion detection and object detection together. + +First, Frigate uses motion detection as a first line check to see if there is anything happening in the frame worth checking with object detection. + +Once motion is detected, it tries to group up nearby areas of motion together in hopes of identifying a rectangle in the image that will capture the area worth inspecting. These are the red "motion boxes" you see in the debug viewer. + +After the area with motion is identified, Frigate creates a "region" (the green boxes in the debug viewer) to run object detection on. The models are trained on square images, so these regions are always squares. It adds a margin around the motion area in hopes of capturing a cropped view of the object moving that fills most of the image passed to object detection, but doesn't cut anything off. It also takes into consideration the location of the bounding box from the previous frame if it is tracking an object. + +After object detection runs, if there are detected objects that seem to be cut off, Frigate reframes the region and runs object detection again on the same frame to get a better look. + +All of this happens for each area of motion and tracked object. + +> Are you simply saying that INITIAL triggering of any kind of detection will only happen in un-masked areas, but that once this triggering happens, the masks become irrelevant and object detection takes precedence? + +Essentially, yes. I wouldn't describe it as object detection taking precedence though. The motion masks just prevent those areas from being counted as motion. Those masks do not modify the regions passed to object detection in any way, so you can absolutely detect objects in areas masked for motion. + +> If so, this is completely expected and intuitive behavior for me. Because obviously if a "foot" starts motion detection the camera should be able to check if it's an entire person before it fully crosses into the zone. The docs imply this is the behavior, so I also don't understand why this would be detrimental to object detection on the whole. + +When just a foot is triggering motion, Frigate will zoom in and look only at the foot. If that even qualifies as a person, it will determine the object is being cut off and look again and again until it zooms back out enough to find the whole person. + +It is also detrimental to how Frigate tracks a moving object. Motion nearby the bounding box from the previous frame is used to intelligently determine where the region should be in the next frame. With too much masking, tracking is hampered and if an object walks from an unmasked area into a fully masked area, they essentially disappear and will be picked up as a "new" object if they leave the masked area. This is important because Frigate uses the history of scores while tracking an object to determine if it is a false positive or not. It takes a minimum of 3 frames for Frigate to determine is the object type it thinks it is, and the median score must be greater than the threshold. If a person meets this threshold while on the sidewalk before they walk into your stoop, you will get an alert the instant they step a single foot into a zone. + +> I thought the main point of this feature was to cut down on CPU use when motion is happening in unnecessary areas. + +It is, but the definition of "unnecessary" varies. I want to ignore areas of motion that I know are definitely not being triggered by objects of interest. Timestamps, trees, sky, rooftops. I don't want to ignore motion from objects that I want to track and know where they go. + +> For me, giving my masks ANY padding results in a lot of people detection I'm not interested in. I live in the city and catch a lot of the sidewalk on my camera. People walk by my front door all the time and the margin between the sidewalk and actually walking onto my stoop is very thin, so I basically have everything but the exact contours of my stoop masked out. This results in very tidy detections but this info keeps throwing me off. Am I just overthinking it? + +This is what `required_zones` are for. You should define a zone (remember this is evaluated based on the bottom center of the bounding box) and make it required to save snapshots and clips (now events in 0.9.0). You can also use this in your conditions for a notification. + +> Maybe my specific situation just warrants this. I've just been having a hard time understanding the relevance of this information - it seems to be that it's exactly what would be expected when "masking out" an area of ANY image. + +That may be the case for you. Frigate will definitely work harder tracking people on the sidewalk to make sure it doesn't miss anyone who steps foot on your stoop. The trade off with the way you have it now is slower recognition of objects and potential misses. That may be acceptable based on your needs. Also, if your resolution is low enough on the detect stream, your regions may already be so big that they grab the entire object anyway. diff --git a/docs/docs/configuration/nvdec.md b/docs/docs/configuration/nvdec.md index b2ec01a47..52e56cd1f 100644 --- a/docs/docs/configuration/nvdec.md +++ b/docs/docs/configuration/nvdec.md @@ -1,6 +1,6 @@ --- id: nvdec -title: nVidia hardware decoder +title: NVIDIA hardware decoder --- Certain nvidia cards include a hardware decoder, which can greatly improve the @@ -9,6 +9,8 @@ ffmpeg with NVDEC support is required. The special docker architecture 'amd64nvi includes this support for amd64 platforms. An aarch64 for the Jetson, which also includes NVDEC may be added in the future. +Some more detailed setup instructions are also available in [this issue](https://github.com/blakeblackshear/frigate/issues/1847#issuecomment-932076731). + ## Docker setup ### Requirements @@ -23,7 +25,7 @@ In order to pass NVDEC, the docker engine must be set to `nvidia` and the enviro In a docker compose file, these lines need to be set: -``` +```yaml services: frigate: ... @@ -41,7 +43,7 @@ The decoder you choose will depend on the input video. A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the container to get a list) -``` +```shell V..... h263_cuvid Nvidia CUVID H263 decoder (codec h263) V..... h264_cuvid Nvidia CUVID H264 decoder (codec h264) V..... hevc_cuvid Nvidia CUVID HEVC decoder (codec hevc) @@ -57,10 +59,9 @@ A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the c For example, for H265 video (hevc), you'll select `hevc_cuvid`. Add `-c:v hevc_cuvid` to your ffmpeg input arguments: -``` +```yaml ffmpeg: - input_args: - ... + input_args: ... - -c:v - hevc_cuvid ``` @@ -100,10 +101,10 @@ processes: To further improve performance, you can set ffmpeg to skip frames in the output, using the fps filter: -``` - output_args: - - -filter:v - - fps=fps=5 +```yaml +output_args: + - -filter:v + - fps=fps=5 ``` This setting, for example, allows Frigate to consume my 10-15fps camera streams on diff --git a/docs/docs/configuration/objects.mdx b/docs/docs/configuration/objects.mdx index 3e95f9e83..fd42a4399 100644 --- a/docs/docs/configuration/objects.mdx +++ b/docs/docs/configuration/objects.mdx @@ -1,16 +1,15 @@ --- id: objects -title: Default available objects -sidebar_label: Available objects +title: Objects --- -import labels from '../../../labelmap.txt'; +import labels from "../../../labelmap.txt"; -By default, Frigate includes the following object models from the Google Coral test data. +By default, Frigate includes the following object models from the Google Coral test data. Note that `car` is listed twice because `truck` has been renamed to `car` by default. These object types are frequently confused.
    - {labels.split('\n').map((label) => ( -
  • {label.replace(/^\d+\s+/, '')}
    • + {labels.split("\n").map((label) => ( +
  • {label.replace(/^\d+\s+/, "")}
    • ))}
@@ -22,15 +21,4 @@ Models for both CPU and EdgeTPU (Coral) are bundled in the image. You can use yo - EdgeTPU Model: `/edgetpu_model.tflite` - Labels: `/labelmap.txt` -You also need to update the model width/height in the config if they differ from the defaults. - -### Customizing the Labelmap - -The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. You must retain the same number of labels, but you can change the names. To change: - -- Download the [COCO labelmap](https://dl.google.com/coral/canned_models/coco_labels.txt) -- Modify the label names as desired. For example, change `7 truck` to `7 car` -- Mount the new file at `/labelmap.txt` in the container with an additional volume - ``` - -v ./config/labelmap.txt:/labelmap.txt - ``` +You also need to update the [model config](/configuration/advanced#model) if they differ from the defaults. diff --git a/docs/docs/configuration/optimizing.md b/docs/docs/configuration/optimizing.md deleted file mode 100644 index a17862eff..000000000 --- a/docs/docs/configuration/optimizing.md +++ /dev/null @@ -1,73 +0,0 @@ ---- -id: optimizing -title: Optimizing performance ---- - -- **Google Coral**: It is strongly recommended to use a Google Coral, Frigate will no longer fall back to CPU in the event one is not found. Offloading TensorFlow to the Google Coral is an order of magnitude faster and will reduce your CPU load dramatically. A $60 device will outperform $2000 CPU. Frigate should work with any supported Coral device from https://coral.ai -- **Resolution**: For the `detect` input, choose a camera resolution where the smallest object you want to detect barely fits inside a 300x300px square. The model used by Frigate is trained on 300x300px images, so you will get worse performance and no improvement in accuracy by using a larger resolution since Frigate resizes the area where it is looking for objects to 300x300 anyway. -- **FPS**: 5 frames per second should be adequate. Higher frame rates will require more CPU usage without improving detections or accuracy. Reducing the frame rate on your camera will have the greatest improvement on system resources. -- **Hardware Acceleration**: Make sure you configure the `hwaccel_args` for your hardware. They provide a significant reduction in CPU usage if they are available. -- **Masks**: Masks can be used to ignore motion and reduce your idle CPU load. If you have areas with regular motion such as timestamps or trees blowing in the wind, frigate will constantly try to determine if that motion is from a person or other object you are tracking. Those detections not only increase your average CPU usage, but also clog the pipeline for detecting objects elsewhere. If you are experiencing high values for `detection_fps` when no objects of interest are in the cameras, you should use masks to tell frigate to ignore movement from trees, bushes, timestamps, or any part of the image where detections should not be wasted looking for objects. - -### FFmpeg Hardware Acceleration - -Frigate works on Raspberry Pi 3b/4 and x86 machines. It is recommended to update your configuration to enable hardware accelerated decoding in ffmpeg. Depending on your system, these parameters may not be compatible. - -Raspberry Pi 3/4 (32-bit OS) -Ensure you increase the allocated RAM for your GPU to at least 128 (raspi-config > Performance Options > GPU Memory). -**NOTICE**: If you are using the addon, ensure you turn off `Protection mode` for hardware acceleration. - -```yaml -ffmpeg: - hwaccel_args: - - -c:v - - h264_mmal -``` - -Raspberry Pi 3/4 (64-bit OS) -**NOTICE**: If you are using the addon, ensure you turn off `Protection mode` for hardware acceleration. - -```yaml -ffmpeg: - hwaccel_args: - - -c:v - - h264_v4l2m2m -``` - -Intel-based CPUs (<10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync) - -```yaml -ffmpeg: - hwaccel_args: - - -hwaccel - - vaapi - - -hwaccel_device - - /dev/dri/renderD128 - - -hwaccel_output_format - - yuv420p -``` - -Intel-based CPUs (>=10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync) - -```yaml -ffmpeg: - hwaccel_args: - - -hwaccel - - qsv - - -qsv_device - - /dev/dri/renderD128 -``` - -AMD/ATI GPUs (Radeon HD 2000 and newer GPUs) via libva-mesa-driver (https://trac.ffmpeg.org/wiki/Hardware/QuickSync) -**Note:** You also need to set `LIBVA_DRIVER_NAME=radeonsi` as an environment variable on the container. - -```yaml -ffmpeg: - hwaccel_args: - - -hwaccel - - vaapi - - -hwaccel_device - - /dev/dri/renderD128 -``` - -Nvidia GPU based decoding via NVDEC is supported, but requires special configuration. See the [nvidia NVDEC documentation](/configuration/nvdec) for more details. diff --git a/docs/docs/configuration/record.md b/docs/docs/configuration/record.md new file mode 100644 index 000000000..23189d1af --- /dev/null +++ b/docs/docs/configuration/record.md @@ -0,0 +1,25 @@ +--- +id: record +title: Recording +--- + +Recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM/DD/HH//MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding. Each camera supports a configurable retention policy in the config. Frigate chooses the largest matching retention value between the recording retention and the event retention when determining if a recording should be removed. + +H265 recordings can be viewed in Edge and Safari only. All other browsers require recordings to be encoded with H264. + +## What if I don't want 24/7 recordings? + +If you only used clips in previous versions with recordings disabled, you can use the following config to get the same behavior. This is also the default behavior when recordings are enabled. + +```yaml +record: + enabled: True + retain_days: 0 + events: + retain: + default: 10 +``` + +This configuration will retain recording segments that overlap with events for 10 days. Because multiple events can reference the same recording segments, this avoids storing duplicate footage for overlapping events and reduces overall storage needs. + +When `retain_days` is set to `0`, events will have up to `max_seconds` (defaults to 5 minutes) of recordings retained. Increasing `retain_days` to `1` will allow events to exceed the `max_seconds` limitation of up to 1 day. diff --git a/docs/docs/configuration/rtmp.md b/docs/docs/configuration/rtmp.md new file mode 100644 index 000000000..af5b0f5f8 --- /dev/null +++ b/docs/docs/configuration/rtmp.md @@ -0,0 +1,8 @@ +--- +id: rtmp +title: RTMP +--- + +Frigate can re-stream your video feed as a RTMP feed for other applications such as Home Assistant to utilize it at `rtmp:///live/`. Port 1935 must be open. This allows you to use a video feed for detection in frigate and Home Assistant live view at the same time without having to make two separate connections to the camera. The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate. + +Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization. diff --git a/docs/docs/configuration/snapshots.md b/docs/docs/configuration/snapshots.md new file mode 100644 index 000000000..73b8f779d --- /dev/null +++ b/docs/docs/configuration/snapshots.md @@ -0,0 +1,6 @@ +--- +id: snapshots +title: Snapshots +--- + +Frigate can save a snapshot image to `/media/frigate/clips` for each event named as `-.jpg`. diff --git a/docs/docs/configuration/zones.md b/docs/docs/configuration/zones.md new file mode 100644 index 000000000..a4cfa3bb4 --- /dev/null +++ b/docs/docs/configuration/zones.md @@ -0,0 +1,38 @@ +--- +id: zones +title: Zones +--- + +Zones allow you to define a specific area of the frame and apply additional filters for object types so you can determine whether or not an object is within a particular area. Zones cannot have the same name as a camera. If desired, a single zone can include multiple cameras if you have multiple cameras covering the same area by configuring zones with the same name for each camera. + +During testing, enable the Zones option for the debug feed so you can adjust as needed. The zone line will increase in thickness when any object enters the zone. + +To create a zone, follow [the steps for a "Motion mask"](/configuration/masks), but use the section of the web UI for creating a zone instead. + +### Restricting zones to specific objects + +Sometimes you want to limit a zone to specific object types to have more granular control of when events/snapshots are saved. The following example will limit one zone to person objects and the other to cars. + +```yaml +camera: + record: + events: + required_zones: + - entire_yard + - front_yard_street + snapshots: + required_zones: + - entire_yard + - front_yard_street + zones: + entire_yard: + coordinates: ... (everywhere you want a person) + objects: + - person + front_yard_street: + coordinates: ... (just the street) + objects: + - car +``` + +Only car objects can trigger the `front_yard_street` zone and only person can trigger the `entire_yard`. You will get events for person objects that enter anywhere in the yard, and events for cars only if they enter the street. diff --git a/docs/docs/contributing.md b/docs/docs/contributing.md index 6d03d8708..a818000b4 100644 --- a/docs/docs/contributing.md +++ b/docs/docs/contributing.md @@ -36,6 +36,59 @@ Fork [blakeblackshear/frigate-hass-integration](https://github.com/blakeblackshe - [Frigate source code](#frigate-core-web-and-docs) - GNU make - Docker +- Extra Coral device (optional, but very helpful to simulate real world performance) + +### Setup + +#### 1. Build the docker container locally with the appropriate make command + +For x86 machines, use `make amd64_frigate` + +#### 2. Create a local config file for testing + +Place the file at `config/config.yml` in the root of the repo. + +Here is an example, but modify for your needs: + +```yaml +mqtt: + host: mqtt + +cameras: + test: + ffmpeg: + inputs: + - path: /media/frigate/car-stopping.mp4 + input_args: -re -stream_loop -1 -fflags +genpts + roles: + - detect + - rtmp + detect: + height: 1080 + width: 1920 + fps: 5 +``` + +These input args tell ffmpeg to read the mp4 file in an infinite loop. You can use any valid ffmpeg input here. + +#### 3. Gather some mp4 files for testing + +Create and place these files in a `debug` folder in the root of the repo. This is also where recordings will be created if you enable them in your test config. Update your config from step 2 above to point at the right file. You can check the `docker-compose.yml` file in the repo to see how the volumes are mapped. + +#### 4. Open the repo with Visual Studio Code + +Upon opening, you should be prompted to open the project in a remote container. This will build a container on top of the base frigate container with all the development dependencies installed. This ensures everyone uses a consistent development environment without the need to install any dependencies on your host machine. + +#### 5. Run frigate from the command line + +VSCode will start the docker compose file for you and open a terminal window connected to `frigate-dev`. + +- Run `python3 -m frigate` to start the backend. +- In a separate terminal window inside VS Code, change into the `web` directory and run `npm install && npm start` to start the frontend. + +#### 6. Teardown + +After closing VSCode, you may still have containers running. To close everything down, just run `docker-compose down -v` to cleanup all containers. ## Web Interface @@ -109,7 +162,7 @@ npm run test #### 1. Installation ```console -npm run install +npm install ``` #### 2. Local Development diff --git a/docs/docs/faqs.md b/docs/docs/faqs.md new file mode 100644 index 000000000..7159402b0 --- /dev/null +++ b/docs/docs/faqs.md @@ -0,0 +1,34 @@ +--- +id: faqs +title: Frequently Asked Questions +--- + +### Fatal Python error: Bus error + +This error message is due to a shm-size that is too small. Try updating your shm-size according to [this guide](/installation#calculating-required-shm-size). + +### I am seeing a solid green image for my camera. + +A solid green image means that frigate has not received any frames from ffmpeg. Check the logs to see why ffmpeg is exiting and adjust your ffmpeg args accordingly. + +### How can I get sound or audio in my recordings? + +By default, Frigate removes audio from recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](configuration/index#ffmpeg). + +### My mjpeg stream or snapshots look green and crazy + +This almost always means that the width/height defined for your camera are not correct. Double check the resolution with vlc or another player. Also make sure you don't have the width and height values backwards. + +![mismatched-resolution](/img/mismatched-resolution-min.jpg) + +### I can't view events or recordings in the Web UI. + +Ensure your cameras send h264 encoded video + +### "[mov,mp4,m4a,3gp,3g2,mj2 @ 0x5639eeb6e140] moov atom not found" + +These messages in the logs are expected in certain situations. Frigate checks the integrity of the recordings before storing. Occasionally these cached files will be invalid and cleaned up automatically. + +### "On connect called" + +If you see repeated "On connect called" messages in your config, check for another instance of frigate. This happens when multiple frigate containers are trying to connect to mqtt with the same client_id. diff --git a/docs/docs/guides/camera_setup.md b/docs/docs/guides/camera_setup.md new file mode 100644 index 000000000..959856fa0 --- /dev/null +++ b/docs/docs/guides/camera_setup.md @@ -0,0 +1,47 @@ +--- +id: camera_setup +title: Camera setup +--- + +Cameras configured to output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. H.265 has better compression, but far less compatibility. Safari and Edge are the only browsers able to play H.265. Ideally, cameras should be configured directly for the desired resolutions and frame rates you want to use in Frigate. Reducing frame rates within Frigate will waste CPU resources decoding extra frames that are discarded. There are three different goals that you want to tune your stream configurations around. + +- **Detection**: This is the only stream that Frigate will decode for processing. Also, this is the stream where snapshots will be generated from. The resolution for detection should be tuned for the size of the objects you want to detect. See [Choosing a detect resolution](#choosing-a-detect-resolution) for more details. The recommended frame rate is 5fps, but may need to be higher for very fast moving objects. Higher resolutions and frame rates will drive higher CPU usage on your server. + +- **Recording**: This stream should be the resolution you wish to store for reference. Typically, this will be the highest resolution your camera supports. I recommend setting this feed to 15 fps. + +- **Stream Viewing**: This stream will be rebroadcast as is to Home Assistant for viewing with the stream component. Setting this resolution too high will use significant bandwidth when viewing streams in Home Assistant, and they may not load reliably over slower connections. + +### Choosing a detect resolution + +The ideal resolution for detection is one where the objects you want to detect fit inside the dimensions of the model used by Frigate (320x320). Frigate does not pass the entire camera frame to object detection. It will crop an area of motion from the full frame and look in that portion of the frame. If the area being inspected is larger than 320x320, Frigate must resize it before running object detection. Higher resolutions do not improve the detection accuracy because the additional detail is lost in the resize. Below you can see a reference for how large a 320x320 area is against common resolutions. + +Larger resolutions **do** improve performance if the objects are very small in the frame. + +![Resolutions](/img/resolutions-min.jpg) + +### Example Camera Configuration + +For the Dahua/Loryta 5442 camera, I use the following settings: + +**Main Stream (Recording)** + +- Encode Mode: H.264 +- Resolution: 2688\*1520 +- Frame Rate(FPS): 15 +- I Frame Interval: 30 + +**Sub Stream 1 (RTMP)** + +- Enable: Sub Stream 1 +- Encode Mode: H.264 +- Resolution: 720\*576 +- Frame Rate: 10 +- I Frame Interval: 10 + +**Sub Stream 2 (Detection)** + +- Enable: Sub Stream 2 +- Encode Mode: H.264 +- Resolution: 1280\*720 +- Frame Rate: 5 +- I Frame Interval: 5 diff --git a/docs/docs/configuration/false_positives.md b/docs/docs/guides/false_positives.md similarity index 100% rename from docs/docs/configuration/false_positives.md rename to docs/docs/guides/false_positives.md diff --git a/docs/docs/guides/getting_started.md b/docs/docs/guides/getting_started.md new file mode 100644 index 000000000..90de06471 --- /dev/null +++ b/docs/docs/guides/getting_started.md @@ -0,0 +1,193 @@ +--- +id: getting_started +title: Creating a config file +--- + +This guide walks through the steps to build a configuration file for Frigate. It assumes that you already have an environment setup as described in [Installation](/installation). You should also configure your cameras according to the [camera setup guide](/guides/camera_setup) + +### Step 1: Configure the MQTT server + +Frigate requires a functioning MQTT server. Start by adding the mqtt section at the top level in your config: + +```yaml +mqtt: + host: +``` + +If using the Mosquitto Addon in Home Assistant, a username and password is required. For example: + +```yaml +mqtt: + host: + user: + password: +``` + +Frigate supports many configuration options for mqtt. See the [configuration reference](/configuration/index#full-configuration-reference) for more info. + +### Step 2: Configure detectors + +By default, Frigate will use a single CPU detector. If you have a USB Coral, you will need to add a detectors section to your config. + +```yaml +mqtt: + host: + +detectors: + coral: + type: edgetpu + device: usb +``` + +More details on available detectors can be found [here](/configuration/detectors). + +### Step 3: Add a minimal camera configuration + +Now let's add the first camera: + +```yaml +mqtt: + host: + +detectors: + coral: + type: edgetpu + device: usb + +cameras: + camera_1: # <------ Name the camera + ffmpeg: + inputs: + - path: rtsp://10.0.10.10:554/rtsp # <----- Update for your camera + roles: + - detect + - rtmp + detect: + width: 1280 # <---- update for your camera's resolution + height: 720 # <---- update for your camera's resolution +``` + +### Step 4: Start Frigate + +At this point you should be able to start Frigate and see the the video feed in the UI. + +If you get a green image from the camera, this means ffmpeg was not able to get the video feed from your camera. Check the logs for error messages from ffmpeg. The default ffmpeg arguments are designed to work with RTSP cameras that support TCP connections. FFmpeg arguments for other types of cameras can be found [here](/configuration/camera_specific). + +### Step 5: Configure hardware acceleration (optional) + +Now that you have a working camera configuration, you want to setup hardware acceleration to minimize the CPU required to decode your video streams. See the [hardware acceleration](/configuration/hardware_acceleration) config reference for examples applicable to your hardware. + +In order to best evaluate the performance impact of hardware acceleration, it is recommended to temporarily disable detection. + +```yaml +mqtt: ... + +detectors: ... + +cameras: + camera_1: + ffmpeg: ... + detect: + enabled: False + ... +``` + +Here is an example configuration with hardware acceleration configured: + +```yaml +mqtt: ... + +detectors: ... + +cameras: + camera_1: + ffmpeg: + inputs: ... + hwaccel_args: -c:v h264_v4l2m2m + detect: ... +``` + +### Step 6: Setup motion masks + +Now that you have optimized your configuration for decoding the video stream, you will want to check to see where to implement motion masks. To do this, navigate to the camera in the UI, select "Debug" at the top, and enable "Motion boxes" in the options below the video feed. Watch for areas that continuously trigger unwanted motion to be detected. Common areas to mask include camera timestamps and trees that frequently blow in the wind. The goal is to avoid wasting object detection cycles looking at these areas. + +Now that you know where you need to mask, use the "Mask & Zone creator" in the options pane to generate the coordinates needed for your config file. More information about masks can be found [here](/configuration/masks). + +:::caution + +Note that motion masks should not be used to mark out areas where you do not want objects to be detected or to reduce false positives. They do not alter the image sent to object detection, so you can still get events and detections in areas with motion masks. These only prevent motion in these areas from initiating object detection. + +::: + +Your configuration should look similar to this now. + +```yaml +mqtt: + host: mqtt.local + +detectors: + coral: + type: edgetpu + device: usb + +cameras: + camera_1: + ffmpeg: + inputs: + - path: rtsp://10.0.10.10:554/rtsp + roles: + - detect + - rtmp + detect: + width: 1280 + height: 720 + motion: + mask: + - 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432 +``` + +### Step 7: Enable recording (optional) + +To enable recording video, add the `record` role to a stream and enable it in the config. + +```yaml +mqtt: ... + +detectors: ... + +cameras: + camera_1: + ffmpeg: + inputs: + - path: rtsp://10.0.10.10:554/rtsp + roles: + - detect + - rtmp + - record # <----- Add role + detect: ... + record: # <----- Enable recording + enabled: True + motion: ... +``` + +By default, Frigate will retain video of all events for 10 days. The full set of options for recording can be found [here](/configuration/index#full-configuration-reference). + +### Step 8: Enable snapshots (optional) + +To enable snapshots of your events, just enable it in the config. + +```yaml +mqtt: ... + +detectors: ... + +cameras: + camera_1: ... + detect: ... + record: ... + snapshots: # <----- Enable snapshots + enabled: True + motion: ... +``` + +By default, Frigate will retain snapshots of all events for 10 days. The full set of options for snapshots can be found [here](/configuration/index#full-configuration-reference). diff --git a/docs/docs/guides/ha_notifications.md b/docs/docs/guides/ha_notifications.md new file mode 100644 index 000000000..b8070a90c --- /dev/null +++ b/docs/docs/guides/ha_notifications.md @@ -0,0 +1,56 @@ +--- +id: ha_notifications +title: Home Assistant notifications +--- + +The best way to get started with notifications for Frigate is to use the [Blueprint](https://community.home-assistant.io/t/frigate-mobile-app-notifications/311091). You can use the yaml generated from the Blueprint as a starting point and customize from there. + +It is generally recommended to trigger notifications based on the `frigate/events` mqtt topic. This provides the event_id needed to fetch [thumbnails/snapshots/clips](/integrations/home-assistant#notification-api) and other useful information to customize when and where you want to receive alerts. The data is published in the form of a change feed, which means you can reference the "previous state" of the object in the `before` section and the "current state" of the object in the `after` section. You can see an example [here](/integrations/mqtt#frigateevents). + +Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as frigate finds a "better" image. + +```yaml +automation: + - alias: Notify of events + trigger: + platform: mqtt + topic: frigate/events + action: + - service: notify.mobile_app_pixel_3 + data_template: + message: 'A {{trigger.payload_json["after"]["label"]}} was detected.' + data: + image: 'https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg?format=android' + tag: '{{trigger.payload_json["after"]["id"]}}' + when: '{{trigger.payload_json["after"]["start_time"]|int}}' +``` + +## Conditions + +Conditions with the `before` and `after` values allow a high degree of customization for automations. + +When a person enters a zone named yard + +```yaml +condition: + - "{{ trigger.payload_json['after']['label'] == 'person' }}" + - "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}" +``` + +When a person leaves a zone named yard + +```yaml +condition: + - "{{ trigger.payload_json['after']['label'] == 'person' }}" + - "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}" + - "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}" +``` + +Notify for dogs in the front with a high top score + +```yaml +condition: + - "{{ trigger.payload_json['after']['label'] == 'dog' }}" + - "{{ trigger.payload_json['after']['camera'] == 'front' }}" + - "{{ trigger.payload_json['after']['top_score'] > 0.98 }}" +``` diff --git a/docs/docs/guides/stationary_objects.md b/docs/docs/guides/stationary_objects.md new file mode 100644 index 000000000..fabb97a3c --- /dev/null +++ b/docs/docs/guides/stationary_objects.md @@ -0,0 +1,37 @@ +--- +id: stationary_objects +title: Avoiding stationary objects +--- + +Many people use Frigate to detect cars entering their driveway, and they often run into an issue with repeated events of a parked car being repeatedly detected. This is because object tracking stops when motion ends and the event ends. Motion detection works by determining if a sufficient number of pixels have changed between frames. Shadows or other lighting changes will be detected as motion. This will often cause a new event for a parked car. + +You can use zones to restrict events and notifications to objects that have entered specific areas. + +:::caution + +It is not recommended to use masks to try and eliminate parked cars in your driveway. Masks are designed to prevent motion from triggering object detection and/or to indicate areas that are guaranteed false positives. + +Frigate is designed to track objects as they move and over-masking can prevent it from knowing that an object in the current frame is the same as the previous frame. You want Frigate to detect objects everywhere and configure your events and alerts to be based on the location of the object with zones. + +::: + +To only be notified of cars that enter your driveway from the street, you could create multiple zones that cover your driveway. For cars, you would only notify if `entered_zones` from the events MQTT topic has more than 1 zone. + +See [this example](/configuration/zones#restricting-zones-to-specific-objects) from the Zones documentation to see how to restrict zones to certain object types. + +![Driveway Zones](/img/driveway_zones-min.png) + +To limit snapshots and events, you can list the zone for the entrance of your driveway under `required_zones` in your configuration file. Example below. + +```yaml +camera: + record: + events: + required_zones: + - zone_2 + zones: + zone_1: + coordinates: ... (parking area) + zone_2: + coordinates: ... (entrance to driveway) +``` diff --git a/docs/docs/hardware.md b/docs/docs/hardware.md index 5cf20df87..b7e725c23 100644 --- a/docs/docs/hardware.md +++ b/docs/docs/hardware.md @@ -5,25 +5,42 @@ title: Recommended hardware ## Cameras -Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, clips, and recordings without re-encoding. +Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, and recordings without re-encoding. -## Computer +I recommend Dahua, Hikvision, and Amcrest in that order. Dahua edges out Hikvision because they are easier to find and order, not because they are better cameras. I personally use Dahua cameras because they are easier to purchase directly. In my experience Dahua and Hikvision both have multiple streams with configurable resolutions and frame rates and rock solid streams. They also both have models with large sensors well known for excellent image quality at night. Not all the models are equal. Larger sensors are better than higher resolutions; especially at night. Amcrest is the fallback recommendation because they are rebranded Dahuas. They are rebranding the lower end models with smaller sensors or less configuration options. -| Name | Inference Speed | Notes | -| ----------------------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------- | -| Atomic Pi | 16ms | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. | -| Intel NUC NUC7i3BNK | 8-10ms | Great performance. Can handle many cameras at 5fps depending on typical amounts of motion. | -| BMAX B2 Plus | 10-12ms | Good balance of performance and cost. Also capable of running many other services at the same time as frigate. | -| Minisforum GK41 | 9-10ms | Great alternative to a NUC with dual Gigabit NICs. Easily handles several 1080p cameras. | -| Raspberry Pi 3B (32bit) | 60ms | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0. | -| Raspberry Pi 4 (32bit) | 15-20ms | Can handle a small number of cameras. The 2GB version runs fine. | -| Raspberry Pi 4 (64bit) | 10-15ms | Can handle a small number of cameras. The 2GB version runs fine. | +Many users have reported various issues with Reolink cameras, so I do not recommend them. If you are using Reolink, I suggest the [Reolink specific configuration](configuration/camera_specific#reolink-410520-possibly-others). Wifi cameras are also not recommended. Their streams are less reliable and cause connection loss and/or lost video data. -## Unraid +Here are some of the camera's I recommend: -Many people have powerful enough NAS devices or home servers to also run docker. There is a Unraid Community App. -To install make sure you have the [community app plugin here](https://forums.unraid.net/topic/38582-plug-in-community-applications/). Then search for "Frigate" in the apps section within Unraid - you can see the online store [here](https://unraid.net/community/apps?q=frigate#r) +- Loryta(Dahua) T5442TM-AS-LED (affiliate link) +- Loryta(Dahua) IPC-T5442TM-AS (affiliate link) +- Amcrest IP5M-T1179EW-28MM (affiliate link) -| Name | Inference Speed | Notes | -| ------------------------------------ | --------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| [M2 Coral Edge TPU](http://coral.ai) | 6.2ms | Install the Coral plugin from Unraid Community App Center [info here](https://forums.unraid.net/topic/98064-support-blakeblackshear-frigate/?do=findComment&comment=949789) | +I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website. + +## Server + +My current favorite is the Odyssey X86 Blue J4125 because the Coral M.2 compatibility and dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website. + +| Name | Inference Speed | Coral Compatibility | Notes | +| -------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------- | ----------------------------------------------------------------------------------------------------------------------------- | +| Odyssey X86 Blue J4125 (affiliate link) | 9-10ms | M.2 B+M | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras. | +| Minisforum GK41 (affiliate link) | 9-10ms | USB | Great alternative to a NUC. Easily handles several 1080p cameras. | +| Minisforum GK50 (affiliate link) | 9-10ms | USB | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras. | +| Intel NUC (affiliate link) | 8-10ms | USB | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion. | +| BMAX B2 Plus (affiliate link) | 10-12ms | USB | Good balance of performance and cost. Also capable of running many other services at the same time as frigate. | +| Atomic Pi (affiliate link) | 16ms | USB | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding. | +| Raspberry Pi 3B (32bit) (affiliate link) | 60ms | USB | Can handle a small number of cameras, but the detection speeds are slow due to USB 2.0. | +| Raspberry Pi 4 (32bit) (affiliate link) | 15-20ms | USB | Can handle a small number of cameras. The 2GB version runs fine. | +| Raspberry Pi 4 (64bit) (affiliate link) | 10-15ms | USB | Can handle a small number of cameras. The 2GB version runs fine. | + +## Google Coral TPU + +It is strongly recommended to use a Google Coral. Frigate is designed around the expectation that a Coral is used to achieve very low inference speeds. Offloading TensorFlow to the Google Coral is an order of magnitude faster and will reduce your CPU load dramatically. A $60 device will outperform $2000 CPU. Frigate should work with any supported Coral device from https://coral.ai + +The USB version is compatible with the widest variety of hardware and does not require a driver on the host machine. However, it does lack the automatic throttling features of the other versions. + +The PCIe and M.2 versions require installation of a driver on the host. Follow the instructions for your version from https://coral.ai + +A single Coral can handle many cameras and will be sufficient for the majority of users. You can calculate the maximum performance of your Coral based on the inference speed reported by Frigate. With an inference speed of 10, your Coral will top out at `1000/10=100`, or 100 frames per second. If your detection fps is regularly getting close to that, you should first consider tuning motion masks. If those are already properly configured, a second Coral may be needed. diff --git a/docs/docs/how-it-works.md b/docs/docs/how-it-works.md deleted file mode 100644 index d92a738b0..000000000 --- a/docs/docs/how-it-works.md +++ /dev/null @@ -1,13 +0,0 @@ ---- -id: how-it-works -title: How Frigate Works -sidebar_label: How it works ---- - -Frigate is designed to minimize resource and maximize performance by only looking for objects when and where it is necessary - -![Diagram](/img/diagram.png) - -1. Look for Motion -2. Calculate Detection Regions -3. Run Object Detection diff --git a/docs/docs/index.md b/docs/docs/index.md index 0bee0be22..8fc6e81fd 100644 --- a/docs/docs/index.md +++ b/docs/docs/index.md @@ -1,13 +1,12 @@ --- id: index -title: Frigate -sidebar_label: Features +title: Introduction slug: / --- A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. -Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. +Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but strongly recommended. CPU detection should only be used for testing purposes. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. - Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration) - Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary @@ -15,11 +14,12 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but - Uses a very low overhead motion detection to determine where to run object detection - Object detection with TensorFlow runs in separate processes for maximum FPS - Communicates over MQTT for easy integration into other systems -- 24/7 recording +- Recording with retention based on detected objects - Re-streaming via RTMP to reduce the number of connections to your camera +- A dynamic combined camera view of all tracked cameras. ## Screenshots -![Media Browser](/img/media_browser.png) +![Media Browser](/img/media_browser-min.png) -![Notification](/img/notification.png) +![Notification](/img/notification-min.png) diff --git a/docs/docs/installation.md b/docs/docs/installation.md index c3f916ad1..d42f4b4e0 100644 --- a/docs/docs/installation.md +++ b/docs/docs/installation.md @@ -3,25 +3,44 @@ id: installation title: Installation --- -Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). See instructions below for installing the HassOS addon. +Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). Note that a Home Assistant Addon is **not** the same thing as the integration. The [integration](integrations/home-assistant) is required to integrate Frigate into Home Assistant. -For Home Assistant users, there is also a [custom component (aka integration)](https://github.com/blakeblackshear/frigate-hass-integration). This custom component adds tighter integration with Home Assistant by automatically setting up camera entities, sensors, media browser for clips and recordings, and a public API to simplify notifications. +## Dependencies -Note that HassOS Addons and custom components are different things. If you are already running Frigate with Docker directly, you do not need the Addon since the Addon would run another instance of Frigate. +**MQTT broker** - Frigate requires an MQTT broker. If using Home Assistant, Frigate and Home Assistant must be connected to the same MQTT broker. -## HassOS Addon +## Preparing your hardware -HassOS users can install via the addon repository. Frigate requires an MQTT server. +### Operating System -1. Navigate to Supervisor > Add-on Store > Repositories -2. Add https://github.com/blakeblackshear/frigate-hass-addons -3. Setup your network configuration in the `Configuration` tab if deisred -4. Create the file `frigate.yml` in your `config` directory with your detailed Frigate configuration -5. Start the addon container -6. If you are using hardware acceleration for ffmpeg, you will need to disable "Protection mode" +Frigate runs best with docker installed on bare metal debian-based distributions. For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer often introduces a sizable amount of overhead for communication with Coral devices, but [not in all circumstances](https://github.com/blakeblackshear/frigate/discussions/1837). + +Windows is not officially supported, but some users have had success getting it to run under WSL or Virtualbox. Getting the GPU and/or Coral devices properly passed to Frigate may be difficult or impossible. Search previous discussions or issues for help. + +### Calculating required shm-size + +Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is 64m. + +The default shm-size of 64m is fine for setups with 2 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size. + +You can calculate the necessary shm-size for each camera with the following formula: + +``` +(width * height * 1.5 * 9 + 270480)/1048576 = +``` + +The shm size cannot be set per container for Home Assistant Addons. You must set `default-shm-size` in `/etc/docker/daemon.json` to increase the default shm size. This will increase the shm size for all of your docker containers. This may or may not cause issues with your setup. https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file + +### Raspberry Pi 3/4 + +By default, the Raspberry Pi limits the amount of memory available to the GPU. In order to use ffmpeg hardware acceleration, you must increase the available memory by setting `gpu_mem` to the maximum recommended value in `config.txt` as described in the [official docs](https://www.raspberrypi.org/documentation/computers/config_txt.html#memory-options). + +Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with it's own power supply. Some have reported success with this (affiliate link). ## Docker +Running in Docker directly is the recommended install method. + Make sure you choose the right image for your architecture: | Arch | Image Name | @@ -41,13 +60,14 @@ services: privileged: true # this may not be necessary for all setups restart: unless-stopped image: blakeblackshear/frigate: + shm_size: "64mb" # update for your cameras based on calculation above devices: - - /dev/bus/usb:/dev/bus/usb + - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions - /dev/dri/renderD128 # for intel hwaccel, needs to be updated for your hardware volumes: - /etc/localtime:/etc/localtime:ro - - :/config/config.yml:ro - - :/media/frigate + - /path/to/your/config.yml:/config/config.yml:ro + - /path/to/your/storage:/media/frigate - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear target: /tmp/cache tmpfs: @@ -68,8 +88,9 @@ docker run -d \ --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \ --device /dev/bus/usb:/dev/bus/usb \ --device /dev/dri/renderD128 \ - -v :/media/frigate \ - -v :/config/config.yml:ro \ + --shm-size=64m \ + -v /path/to/your/storage:/media/frigate \ + -v /path/to/your/config.yml:/config/config.yml:ro \ -v /etc/localtime:/etc/localtime:ro \ -e FRIGATE_RTSP_PASSWORD='password' \ -p 5000:5000 \ @@ -77,48 +98,62 @@ docker run -d \ blakeblackshear/frigate: ``` -### Calculating shm-size +## Home Assistant Operating System (HassOS) -The default shm-size of 64m is fine for setups with 3 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it could be because you have too many high resolution cameras and you need to specify a higher shm size. +:::caution -You can calculate the necessary shm-size for each camera with the following formula: +Due to limitations in Home Assistant Operating System, Frigate cannot utilize external storage for recordings or snapshots. -``` -(width * height * 1.5 * 7 + 270480)/1048576 = +::: + +:::tip + +If possible, it is recommended to run Frigate standalone in Docker and use [Frigate's Proxy Addon](https://github.com/blakeblackshear/frigate-hass-addons/blob/main/frigate_proxy/README.md). + +::: + +HassOS users can install via the addon repository. + +1. Navigate to Supervisor > Add-on Store > Repositories +2. Add https://github.com/blakeblackshear/frigate-hass-addons +3. Install your desired Frigate NVR Addon and navigate to it's page +4. Setup your network configuration in the `Configuration` tab +5. (not for proxy addon) Create the file `frigate.yml` in your `config` directory with your detailed Frigate configuration +6. Start the addon container +7. (not for proxy addon) If you are using hardware acceleration for ffmpeg, you may need to disable "Protection mode" + +## Home Assistant Supervised + +:::tip + +If possible, it is recommended to run Frigate standalone in Docker and use [Frigate's Proxy Addon](https://github.com/blakeblackshear/frigate-hass-addons/blob/main/frigate_proxy/README.md). + +::: + +When running Home Assistant with the [Supervised install method](https://github.com/home-assistant/supervised-installer), you can get the benefit of running the Addon along with the ability to customize the storage used by Frigate. + +In order to customize the storage location for Frigate, simply use `fstab` to mount the drive you want at `/usr/share/hassio/media`. Here is an example fstab entry: + +```shell +UUID=1a65fec6-c25f-404a-b3d2-1f2fcf6095c8 /media/data ext4 defaults 0 0 +/media/data/homeassistant/media /usr/share/hassio/media none bind 0 0 ``` -The shm size cannot be set per container for Home Assistant Addons. You must set `default-shm-size` in `/etc/docker/daemon.json` to increase the default shm size. This will increase the shm size for all of your docker containers. This may or may not cause issues with your setup. https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file +Then follow the instructions listed for [Home Assistant Operating System](#home-assistant-operating-system-hassos). ## Kubernetes Use the [helm chart](https://github.com/blakeblackshear/blakeshome-charts/tree/master/charts/frigate). -## Virtualization +## Unraid -For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices for ffmpeg decoding. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer typically introduces a sizable amount of overhead for communication with Coral devices. +Many people have powerful enough NAS devices or home servers to also run docker. There is a Unraid Community App. +To install make sure you have the [community app plugin here](https://forums.unraid.net/topic/38582-plug-in-community-applications/). Then search for "Frigate" in the apps section within Unraid - you can see the online store [here](https://unraid.net/community/apps?q=frigate#r) -### Proxmox +## Proxmox -Some people have had success running Frigate in LXC directly with the following config: +It is recommended to run Frigate in LXC for maximum performance. See [this discussion](https://github.com/blakeblackshear/frigate/discussions/1111) for more information. -``` -arch: amd64 -cores: 2 -features: nesting=1 -hostname: FrigateLXC -memory: 4096 -net0: name=eth0,bridge=vmbr0,firewall=1,hwaddr=2E:76:AE:5A:58:48,ip=dhcp,ip6=auto,type=veth -ostype: debian -rootfs: local-lvm:vm-115-disk-0,size=12G -swap: 512 -lxc.cgroup.devices.allow: c 189:385 rwm -lxc.mount.entry: /dev/dri/renderD128 dev/dri/renderD128 none bind,optional,create=file -lxc.mount.entry: /dev/bus/usb/004/002 dev/bus/usb/004/002 none bind,optional,create=file -lxc.apparmor.profile: unconfined -lxc.cgroup.devices.allow: a -lxc.cap.drop: -``` - -### ESX +## ESX For details on running Frigate under ESX, see details [here](https://github.com/blakeblackshear/frigate/issues/305). diff --git a/docs/docs/usage/api.md b/docs/docs/integrations/api.md similarity index 83% rename from docs/docs/usage/api.md rename to docs/docs/integrations/api.md index 83ffbdf00..69b6e7632 100644 --- a/docs/docs/usage/api.md +++ b/docs/docs/integrations/api.md @@ -5,7 +5,7 @@ title: HTTP API A web server is available on port 5000 with the following endpoints. -### `/api/` +### `GET /api/` An mjpeg stream for debugging. Keep in mind the mjpeg endpoint is for debugging only and will put additional load on the system when in use. @@ -24,7 +24,7 @@ Accepts the following query string parameters: You can access a higher resolution mjpeg stream by appending `h=height-in-pixels` to the endpoint. For example `http://localhost:5000/api/back?h=1080`. You can also increase the FPS by appending `fps=frame-rate` to the URL such as `http://localhost:5000/api/back?fps=10` or both with `?fps=10&h=1000`. -### `/api///best.jpg[?h=300&crop=1]` +### `GET /api///best.jpg[?h=300&crop=1&quality=70]` The best snapshot for any object type. It is a full resolution image by default. @@ -32,8 +32,9 @@ Example parameters: - `h=300`: resizes the image to 300 pixes tall - `crop=1`: crops the image to the region of the detection rather than returning the entire image +- `quality=70`: sets the jpeg encoding quality (0-100) -### `/api//latest.jpg[?h=300]` +### `GET /api//latest.jpg[?h=300]` The most recent frame that frigate has finished processing. It is a full resolution image by default. @@ -48,12 +49,13 @@ Accepts the following query string parameters: | `mask` | int | Overlay the mask on the image (0 or 1) | | `motion` | int | Draw blue boxes for areas with detected motion (0 or 1) | | `regions` | int | Draw green boxes for areas where object detection was run (0 or 1) | +| `quality` | int | Jpeg encoding quality (0-100). Defaults to 70. | Example parameters: - `h=300`: resizes the image to 300 pixes tall -### `/api/stats` +### `GET /api/stats` Contains some granular debug info that can be used for sensors in Home Assistant. @@ -150,15 +152,15 @@ Sample response: } ``` -### `/api/config` +### `GET /api/config` A json representation of your configuration -### `/api/version` +### `GET /api/version` Version info -### `/api/events` +### `GET /api/events` Events from the database. Accepts the following query string parameters: @@ -174,19 +176,27 @@ Events from the database. Accepts the following query string parameters: | `has_clip` | int | Filter to events that have clips (0 or 1) | | `include_thumbnails` | int | Include thumbnails in the response (0 or 1) | -### `/api/events/summary` +### `GET /api/events/summary` Returns summary data for events in the database. Used by the Home Assistant integration. -### `/api/events/` +### `GET /api/events/` Returns data for a single event. -### `/api/events//thumbnail.jpg` +### `DELETE /api/events/` + +Permanently deletes the event along with any clips/snapshots. + +### `GET /api/events//thumbnail.jpg` Returns a thumbnail for the event id optimized for notifications. Works while the event is in progress and after completion. Passing `?format=android` will convert the thumbnail to 2:1 aspect ratio. -### `/api/events//snapshot.jpg` +### `GET /api/events//clip.mp4` + +Returns the clip for the event id. Works after the event has ended. + +### `GET /api/events//snapshot.jpg` Returns the snapshot image for the event id. Works while the event is in progress and after completion. @@ -198,11 +208,24 @@ Accepts the following query string parameters, but they are only applied when an | `bbox` | int | Show bounding boxes for detected objects (0 or 1) | | `timestamp` | int | Print the timestamp in the upper left (0 or 1) | | `crop` | int | Crop the snapshot to the (0 or 1) | +| `quality` | int | Jpeg encoding quality (0-100). Defaults to 70. | -### `/clips/-.mp4` - -Video clip for the given camera and event id. - -### `/clips/-.jpg` +### `GET /clips/-.jpg` JPG snapshot for the given camera and event id. + +### `GET /vod/-////master.m3u8` + +HTTP Live Streaming Video on Demand URL for the specified hour and camera. Can be viewed in an application like VLC. + +### `GET /vod/event//index.m3u8` + +HTTP Live Streaming Video on Demand URL for the specified event. Can be viewed in an application like VLC. + +### `GET /vod/event//index.m3u8` + +HTTP Live Streaming Video on Demand URL for the specified event. Can be viewed in an application like VLC. + +### `GET /vod//start//end//index.m3u8` + +HTTP Live Streaming Video on Demand URL for the camera with the specified time range. Can be viewed in an application like VLC. diff --git a/docs/docs/usage/home-assistant.md b/docs/docs/integrations/home-assistant.md similarity index 60% rename from docs/docs/usage/home-assistant.md rename to docs/docs/integrations/home-assistant.md index 110ea6d6e..165eef1c4 100644 --- a/docs/docs/usage/home-assistant.md +++ b/docs/docs/integrations/home-assistant.md @@ -1,7 +1,6 @@ --- id: home-assistant -title: Integration with Home Assistant -sidebar_label: Home Assistant +title: Home Assistant Integration --- The best way to integrate with Home Assistant is to use the [official integration](https://github.com/blakeblackshear/frigate-hass-integration). @@ -70,138 +69,41 @@ Home Assistant > Configuration > Integrations > Frigate > Options | --------------- | --------------------------------------------------------------------------------- | | `camera` | Live camera stream (requires RTMP), camera for image of the last detected object. | | `sensor` | States to monitor Frigate performance, object counts for all zones and cameras. | -| `switch` | Switch entities to toggle detection, clips and snapshots. | +| `switch` | Switch entities to toggle detection, recordings and snapshots. | | `binary_sensor` | A "motion" binary sensor entity per camera/zone/object. | ## Media Browser Support The integration provides: -- Rich UI with thumbnails for browsing event clips -- Rich UI for browsing 24/7 recordings by month, day, camera, time +- Browsing event recordings with thumbnails +- Browsing snapshots +- Browsing recordings by month, day, camera, time This is accessible via "Media Browser" on the left menu panel in Home Assistant. -## API +## Notification API -- Notification API with public facing endpoints for images in notifications +Many people do not want to expose Frigate to the web, so the integration creates some public API endpoints that can be used for notifications. -### Notifications - -Frigate publishes event information in the form of a change feed via MQTT. This -allows lots of customization for notifications to meet your needs. Event changes -are published with `before` and `after` information as shown -[here](#frigateevents). Note that some people may not want to expose frigate to -the web, so you can leverage the HA API that frigate custom_integration ties -into (which is exposed to the web, and thus can be used for mobile notifications -etc): - -To load an image taken by frigate from Home Assistants API see below: +To load a thumbnail for an event: ``` https://HA_URL/api/frigate/notifications//thumbnail.jpg ``` -To load a video clip taken by frigate from Home Assistants API : +To load a snapshot for an event: ``` -https://HA_URL/api/frigate/notifications///clip.mp4 +https://HA_URL/api/frigate/notifications//snapshot.jpg ``` -Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as frigate finds a "better" image. +To load a video clip of an event: -```yaml -automation: - - alias: Notify of events - trigger: - platform: mqtt - topic: frigate/events - action: - - service: notify.mobile_app_pixel_3 - data_template: - message: 'A {{trigger.payload_json["after"]["label"]}} was detected.' - data: - image: 'https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg?format=android' - tag: '{{trigger.payload_json["after"]["id"]}}' - when: '{{trigger.payload_json["after"]["start_time"]|int}}' ``` - -```yaml -automation: - - alias: When a person enters a zone named yard - trigger: - platform: mqtt - topic: frigate/events - condition: - - "{{ trigger.payload_json['after']['label'] == 'person' }}" - - "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}" - action: - - service: notify.mobile_app_pixel_3 - data_template: - message: "A {{trigger.payload_json['after']['label']}} has entered the yard." - data: - image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg" - tag: "{{trigger.payload_json['after']['id']}}" - when: '{{trigger.payload_json["after"]["start_time"]|int}}' -``` - -```yaml -- alias: When a person leaves a zone named yard - trigger: - platform: mqtt - topic: frigate/events - condition: - - "{{ trigger.payload_json['after']['label'] == 'person' }}" - - "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}" - - "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}" - action: - - service: notify.mobile_app_pixel_3 - data_template: - message: "A {{trigger.payload_json['after']['label']}} has left the yard." - data: - image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg" - tag: "{{trigger.payload_json['after']['id']}}" - when: '{{trigger.payload_json["after"]["start_time"]|int}}' -``` - -```yaml -- alias: Notify for dogs in the front with a high top score - trigger: - platform: mqtt - topic: frigate/events - condition: - - "{{ trigger.payload_json['after']['label'] == 'dog' }}" - - "{{ trigger.payload_json['after']['camera'] == 'front' }}" - - "{{ trigger.payload_json['after']['top_score'] > 0.98 }}" - action: - - service: notify.mobile_app_pixel_3 - data_template: - message: "High confidence dog detection." - data: - image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg" - tag: "{{trigger.payload_json['after']['id']}}" - when: '{{trigger.payload_json["after"]["start_time"]|int}}' -``` - -If you are using telegram, you can fetch the image directly from Frigate: - -```yaml -automation: - - alias: Notify of events - trigger: - platform: mqtt - topic: frigate/events - action: - - service: notify.telegram_full - data_template: - message: 'A {{trigger.payload_json["after"]["label"]}} was detected.' - data: - photo: - # this url should work for addon users - - url: 'http://ccab4aaf-frigate:5000/api/events/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg' - caption: 'A {{trigger.payload_json["after"]["label"]}} was detected on {{ trigger.payload_json["after"]["camera"] }} camera' +https://HA_URL/api/frigate/notifications//clip.mp4 ``` @@ -282,6 +184,6 @@ which server they are referring to. ## FAQ -### If I am detecting multiple objects, how do I assign the correct `binary_sensor` to the camera in HomeKit? +#### If I am detecting multiple objects, how do I assign the correct `binary_sensor` to the camera in HomeKit? The [HomeKit integration](https://www.home-assistant.io/integrations/homekit/) randomly links one of the binary sensors (motion sensor entities) grouped with the camera device in Home Assistant. You can specify a `linked_motion_sensor` in the Home Assistant [HomeKit configuration](https://www.home-assistant.io/integrations/homekit/#linked_motion_sensor) for each camera. diff --git a/docs/docs/usage/mqtt.md b/docs/docs/integrations/mqtt.md similarity index 81% rename from docs/docs/usage/mqtt.md rename to docs/docs/integrations/mqtt.md index 83d92bbc2..c17f320c3 100644 --- a/docs/docs/usage/mqtt.md +++ b/docs/docs/integrations/mqtt.md @@ -11,6 +11,10 @@ Designed to be used as an availability topic with Home Assistant. Possible messa "online": published when frigate is running (on startup) "offline": published right before frigate stops +### `frigate/restart` + +Causes frigate to exit. Docker should be configured to automatically restart the container on exit. + ### `frigate//` Publishes the count of objects for the camera for use as a sensor in Home Assistant. @@ -32,11 +36,12 @@ Message published for each changed event. The first message is published when th ```json { - "type": "update", // new, update, or end + "type": "update", // new, update, end "before": { "id": "1607123955.475377-mxklsc", "camera": "front_door", "frame_time": 1607123961.837752, + "snapshot_time": 1607123961.837752, "label": "person", "top_score": 0.958984375, "false_positive": false, @@ -48,12 +53,15 @@ Message published for each changed event. The first message is published when th "region": [264, 450, 667, 853], "current_zones": ["driveway"], "entered_zones": ["yard", "driveway"], - "thumbnail": null + "thumbnail": null, + "has_snapshot": false, + "has_clip": false }, "after": { "id": "1607123955.475377-mxklsc", "camera": "front_door", "frame_time": 1607123962.082975, + "snapshot_time": 1607123961.837752, "label": "person", "top_score": 0.958984375, "false_positive": false, @@ -65,7 +73,9 @@ Message published for each changed event. The first message is published when th "region": [218, 440, 693, 915], "current_zones": ["yard", "driveway"], "entered_zones": ["yard", "driveway"], - "thumbnail": null + "thumbnail": null, + "has_snapshot": false, + "has_clip": false } } ``` @@ -82,13 +92,13 @@ Topic to turn detection for a camera on and off. Expected values are `ON` and `O Topic with current state of detection for a camera. Published values are `ON` and `OFF`. -### `frigate//clips/set` +### `frigate//recordings/set` -Topic to turn clips for a camera on and off. Expected values are `ON` and `OFF`. +Topic to turn recordings for a camera on and off. Expected values are `ON` and `OFF`. -### `frigate//clips/state` +### `frigate//recordings/state` -Topic with current state of clips for a camera. Published values are `ON` and `OFF`. +Topic with current state of recordings for a camera. Published values are `ON` and `OFF`. ### `frigate//snapshots/set` diff --git a/docs/docs/troubleshooting.md b/docs/docs/troubleshooting.md deleted file mode 100644 index d7d12afa2..000000000 --- a/docs/docs/troubleshooting.md +++ /dev/null @@ -1,28 +0,0 @@ ---- -id: troubleshooting -title: Troubleshooting and FAQ ---- - -### How can I get sound or audio in my clips and recordings? -By default, Frigate removes audio from clips and recordings to reduce the likelihood of failing for invalid data. If you would like to include audio, you need to override the output args to remove `-an` for where you want to include audio. The recommended audio codec is `aac`. Not all audio codecs are supported by RTMP, so you may need to re-encode your audio with `-c:a aac`. The default ffmpeg args are shown [here](/frigate/configuration/index#ffmpeg). - -### My mjpeg stream or snapshots look green and crazy -This almost always means that the width/height defined for your camera are not correct. Double check the resolution with vlc or another player. Also make sure you don't have the width and height values backwards. - -![mismatched-resolution](/img/mismatched-resolution.jpg) - -### I have clips and snapshots in my clips folder, but I can't view them in the Web UI. -This is usually caused one of two things: - -- The permissions on the parent folder don't have execute and nginx returns a 403 error you can see in the browser logs - - In this case, try mounting a volume to `/media/frigate` inside the container instead of `/media/frigate/clips`. -- Your cameras do not send h264 encoded video and the mp4 files are not playable in the browser - - -### "[mov,mp4,m4a,3gp,3g2,mj2 @ 0x5639eeb6e140] moov atom not found" - -These messages in the logs are expected in certain situations. Frigate checks the integrity of the video cache before assembling clips. Occasionally these cached files will be invalid and cleaned up automatically. - -### "On connect called" - -If you see repeated "On connect called" messages in your config, check for another instance of frigate. This happens when multiple frigate containers are trying to connect to mqtt with the same client_id. diff --git a/docs/docs/usage/howtos.md b/docs/docs/usage/howtos.md deleted file mode 100644 index 9392caf0a..000000000 --- a/docs/docs/usage/howtos.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -id: howtos -title: Community Guides -sidebar_label: Community Guides ---- - -## Communitiy Guides/How-To's - -- Best Camera AI Person & Object Detection - How to Setup Frigate w/ Home Assistant - digiblurDIY [YouTube](https://youtu.be/V8vGdoYO6-Y) - [Article](https://www.digiblur.com/2021/05/how-to-setup-frigate-home-assistant.html) -- Even More Free Local Object Detection with Home Assistant - Frigate Install - Everything Smart Home [YouTube](https://youtu.be/pqDCEZSVeRk) -- Home Assistant Frigate integration for local image recognition - KPeyanski [YouTube](https://youtu.be/Q2UT78lFQpo) - [Article](https://peyanski.com/home-assistant-frigate-integration/) diff --git a/docs/docs/usage/web.md b/docs/docs/usage/web.md deleted file mode 100644 index f6b73dff9..000000000 --- a/docs/docs/usage/web.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -id: web -title: Web Interface ---- - -Frigate comes bundled with a simple web ui that supports the following: - -- Show cameras -- Browse events -- Mask helper diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js index 9df91fe62..4f44ee909 100644 --- a/docs/docusaurus.config.js +++ b/docs/docusaurus.config.js @@ -3,8 +3,8 @@ const path = require('path'); module.exports = { title: 'Frigate', tagline: 'NVR With Realtime Object Detection for IP Cameras', - url: 'https://blakeblackshear.github.io', - baseUrl: '/frigate/', + url: 'https://docs.frigate.video', + baseUrl: '/', onBrokenLinks: 'throw', onBrokenMarkdownLinks: 'warn', favicon: 'img/favicon.ico', diff --git a/docs/package-lock.json b/docs/package-lock.json index fcf2b20cb..cf88c7daf 100644 --- a/docs/package-lock.json +++ b/docs/package-lock.json @@ -5,420 +5,432 @@ 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"^4.1.0" + } } } }, diff --git a/docs/package.json b/docs/package.json index 0c7864e0a..ed4e223db 100644 --- a/docs/package.json +++ b/docs/package.json @@ -12,8 +12,8 @@ "clear": "docusaurus clear" }, "dependencies": { - "@docusaurus/core": "2.0.0-alpha.70", - "@docusaurus/preset-classic": "2.0.0-alpha.70", + "@docusaurus/core": "^2.0.0-beta.ff31de0ff", + "@docusaurus/preset-classic": "^2.0.0-beta.ff31de0ff", "@mdx-js/react": "^1.6.21", "clsx": "^1.1.1", "raw-loader": "^4.0.2", diff --git a/docs/sidebars.js b/docs/sidebars.js index a8e6714cb..2b3669bdf 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -1,16 +1,34 @@ module.exports = { docs: { - Frigate: ['index', 'how-it-works', 'hardware', 'installation', 'troubleshooting'], + Frigate: [ + 'index', + 'hardware', + 'installation', + ], + Guides: [ + 'guides/camera_setup', + 'guides/getting_started', + 'guides/false_positives', + 'guides/ha_notifications', + 'guides/stationary_objects', + ], Configuration: [ 'configuration/index', - 'configuration/cameras', - 'configuration/optimizing', 'configuration/detectors', - 'configuration/false_positives', + 'configuration/cameras', + 'configuration/masks', + 'configuration/record', + 'configuration/snapshots', 'configuration/objects', + 'configuration/rtmp', + 'configuration/zones', 'configuration/advanced', + 'configuration/hardware_acceleration', + 'configuration/nvdec', + 'configuration/camera_specific', ], - Usage: ['usage/home-assistant', 'usage/web', 'usage/api', 'usage/mqtt'], + Integrations: ['integrations/home-assistant', 'integrations/api', 'integrations/mqtt'], + Troubleshooting: ['faqs'], Development: ['contributing'], }, }; diff --git a/docs/static/img/driveway_zones-min.png b/docs/static/img/driveway_zones-min.png new file mode 100644 index 000000000..39e19540d Binary files /dev/null and b/docs/static/img/driveway_zones-min.png differ diff --git a/docs/static/img/driveway_zones.png b/docs/static/img/driveway_zones.png new file mode 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a/docs/static/img/reolink-settings.png b/docs/static/img/reolink-settings.png new file mode 100644 index 000000000..ebb043f32 Binary files /dev/null and b/docs/static/img/reolink-settings.png differ diff --git a/docs/static/img/resolutions-min.jpg b/docs/static/img/resolutions-min.jpg new file mode 100644 index 000000000..19169ac39 Binary files /dev/null and b/docs/static/img/resolutions-min.jpg differ diff --git a/docs/static/img/resolutions.png b/docs/static/img/resolutions.png new file mode 100644 index 000000000..59d8c8bc0 Binary files /dev/null and b/docs/static/img/resolutions.png differ diff --git a/frigate/__main__.py b/frigate/__main__.py index 2524c621a..0d9a3dbe2 100644 --- a/frigate/__main__.py +++ b/frigate/__main__.py @@ -1,4 +1,6 @@ -import faulthandler; faulthandler.enable() +import faulthandler + +faulthandler.enable() import sys import threading @@ -6,10 +8,10 @@ threading.current_thread().name = "frigate" from frigate.app import FrigateApp -cli = sys.modules['flask.cli'] +cli = sys.modules["flask.cli"] cli.show_server_banner = lambda *x: None -if __name__ == '__main__': +if __name__ == "__main__": frigate_app = FrigateApp() frigate_app.start() diff --git a/frigate/app.py b/frigate/app.py index 8e5178c79..c1a9b6f48 100644 --- a/frigate/app.py +++ b/frigate/app.py @@ -2,38 +2,40 @@ import json import logging import multiprocessing as mp import os +import signal +import sys +import threading from logging.handlers import QueueHandler from typing import Dict, List -import sys -import signal import yaml -from gevent import pywsgi -from geventwebsocket.handler import WebSocketHandler from peewee_migrate import Router from playhouse.sqlite_ext import SqliteExtDatabase from playhouse.sqliteq import SqliteQueueDatabase -from frigate.config import FrigateConfig -from frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR +from frigate.config import DetectorTypeEnum, FrigateConfig +from frigate.const import CACHE_DIR, CLIPS_DIR, RECORD_DIR from frigate.edgetpu import EdgeTPUProcess -from frigate.events import EventProcessor, EventCleanup +from frigate.events import EventCleanup, EventProcessor from frigate.http import create_app from frigate.log import log_process, root_configurer -from frigate.models import Event -from frigate.mqtt import create_mqtt_client +from frigate.models import Event, Recordings +from frigate.mqtt import MqttSocketRelay, create_mqtt_client from frigate.object_processing import TrackedObjectProcessor -from frigate.record import RecordingMaintainer +from frigate.output import output_frames +from frigate.record import RecordingCleanup, RecordingMaintainer from frigate.stats import StatsEmitter, stats_init +from frigate.version import VERSION from frigate.video import capture_camera, track_camera from frigate.watchdog import FrigateWatchdog -from frigate.zeroconf import broadcast_zeroconf logger = logging.getLogger(__name__) -class FrigateApp(): + +class FrigateApp: def __init__(self): self.stop_event = mp.Event() + self.base_config: FrigateConfig = None self.config: FrigateConfig = None self.detection_queue = mp.Queue() self.detectors: Dict[str, EdgeTPUProcess] = {} @@ -54,148 +56,257 @@ class FrigateApp(): else: logger.debug(f"Skipping directory: {d}") - tmpfs_size = self.config.clips.tmpfs_cache_size - if tmpfs_size: - logger.info(f"Creating tmpfs of size {tmpfs_size}") - rc = os.system(f"mount -t tmpfs -o size={tmpfs_size} tmpfs {CACHE_DIR}") - if rc != 0: - logger.error(f"Failed to create tmpfs, error code: {rc}") - def init_logger(self): - self.log_process = mp.Process(target=log_process, args=(self.log_queue,), name='log_process') + self.log_process = mp.Process( + target=log_process, args=(self.log_queue,), name="log_process" + ) self.log_process.daemon = True self.log_process.start() root_configurer(self.log_queue) - + def init_config(self): - config_file = os.environ.get('CONFIG_FILE', '/config/config.yml') - self.config = FrigateConfig(config_file=config_file) + config_file = os.environ.get("CONFIG_FILE", "/config/config.yml") + user_config = FrigateConfig.parse_file(config_file) + self.config = user_config.runtime_config for camera_name in self.config.cameras.keys(): # create camera_metrics self.camera_metrics[camera_name] = { - 'camera_fps': mp.Value('d', 0.0), - 'skipped_fps': mp.Value('d', 0.0), - 'process_fps': mp.Value('d', 0.0), - 'detection_enabled': mp.Value('i', self.config.cameras[camera_name].detect.enabled), - 'detection_fps': mp.Value('d', 0.0), - 'detection_frame': mp.Value('d', 0.0), - 'read_start': mp.Value('d', 0.0), - 'ffmpeg_pid': mp.Value('i', 0), - 'frame_queue': mp.Queue(maxsize=2), + "camera_fps": mp.Value("d", 0.0), + "skipped_fps": mp.Value("d", 0.0), + "process_fps": mp.Value("d", 0.0), + "detection_enabled": mp.Value( + "i", self.config.cameras[camera_name].detect.enabled + ), + "detection_fps": mp.Value("d", 0.0), + "detection_frame": mp.Value("d", 0.0), + "read_start": mp.Value("d", 0.0), + "ffmpeg_pid": mp.Value("i", 0), + "frame_queue": mp.Queue(maxsize=2), } - + def check_config(self): for name, camera in self.config.cameras.items(): - assigned_roles = list(set([r for i in camera.ffmpeg.inputs for r in i.roles])) - if not camera.clips.enabled and 'clips' in assigned_roles: - logger.warning(f"Camera {name} has clips assigned to an input, but clips is not enabled.") - elif camera.clips.enabled and not 'clips' in assigned_roles: - logger.warning(f"Camera {name} has clips enabled, but clips is not assigned to an input.") + assigned_roles = list( + set([r for i in camera.ffmpeg.inputs for r in i.roles]) + ) + if not camera.record.enabled and "record" in assigned_roles: + logger.warning( + f"Camera {name} has record assigned to an input, but record is not enabled." + ) + elif camera.record.enabled and not "record" in assigned_roles: + logger.warning( + f"Camera {name} has record enabled, but record is not assigned to an input." + ) - if not camera.record.enabled and 'record' in assigned_roles: - logger.warning(f"Camera {name} has record assigned to an input, but record is not enabled.") - elif camera.record.enabled and not 'record' in assigned_roles: - logger.warning(f"Camera {name} has record enabled, but record is not assigned to an input.") + if not camera.rtmp.enabled and "rtmp" in assigned_roles: + logger.warning( + f"Camera {name} has rtmp assigned to an input, but rtmp is not enabled." + ) + elif camera.rtmp.enabled and not "rtmp" in assigned_roles: + logger.warning( + f"Camera {name} has rtmp enabled, but rtmp is not assigned to an input." + ) - if not camera.rtmp.enabled and 'rtmp' in assigned_roles: - logger.warning(f"Camera {name} has rtmp assigned to an input, but rtmp is not enabled.") - elif camera.rtmp.enabled and not 'rtmp' in assigned_roles: - logger.warning(f"Camera {name} has rtmp enabled, but rtmp is not assigned to an input.") - def set_log_levels(self): - logging.getLogger().setLevel(self.config.logger.default) + logging.getLogger().setLevel(self.config.logger.default.value.upper()) for log, level in self.config.logger.logs.items(): - logging.getLogger(log).setLevel(level) - - if not 'geventwebsocket.handler' in self.config.logger.logs: - logging.getLogger('geventwebsocket.handler').setLevel('ERROR') + logging.getLogger(log).setLevel(level.value.upper()) + + if not "werkzeug" in self.config.logger.logs: + logging.getLogger("werkzeug").setLevel("ERROR") def init_queues(self): # Queues for clip processing self.event_queue = mp.Queue() self.event_processed_queue = mp.Queue() + self.video_output_queue = mp.Queue(maxsize=len(self.config.cameras.keys()) * 2) # Queue for cameras to push tracked objects to - self.detected_frames_queue = mp.Queue(maxsize=len(self.config.cameras.keys())*2) + self.detected_frames_queue = mp.Queue( + maxsize=len(self.config.cameras.keys()) * 2 + ) def init_database(self): + # Migrate DB location + old_db_path = os.path.join(CLIPS_DIR, "frigate.db") + if not os.path.isfile(self.config.database.path) and os.path.isfile( + old_db_path + ): + os.rename(old_db_path, self.config.database.path) + + # Migrate DB schema migrate_db = SqliteExtDatabase(self.config.database.path) # Run migrations - del(logging.getLogger('peewee_migrate').handlers[:]) + del logging.getLogger("peewee_migrate").handlers[:] router = Router(migrate_db) router.run() migrate_db.close() self.db = SqliteQueueDatabase(self.config.database.path) - models = [Event] + models = [Event, Recordings] self.db.bind(models) def init_stats(self): self.stats_tracking = stats_init(self.camera_metrics, self.detectors) def init_web_server(self): - self.flask_app = create_app(self.config, self.db, self.stats_tracking, self.detected_frames_processor, self.mqtt_client) + self.flask_app = create_app( + self.config, + self.db, + self.stats_tracking, + self.detected_frames_processor, + ) def init_mqtt(self): self.mqtt_client = create_mqtt_client(self.config, self.camera_metrics) + def start_mqtt_relay(self): + self.mqtt_relay = MqttSocketRelay( + self.mqtt_client, self.config.mqtt.topic_prefix + ) + self.mqtt_relay.start() + def start_detectors(self): + model_path = self.config.model.path model_shape = (self.config.model.height, self.config.model.width) for name in self.config.cameras.keys(): self.detection_out_events[name] = mp.Event() - shm_in = mp.shared_memory.SharedMemory(name=name, create=True, size=self.config.model.height*self.config.model.width*3) - shm_out = mp.shared_memory.SharedMemory(name=f"out-{name}", create=True, size=20*6*4) + + try: + shm_in = mp.shared_memory.SharedMemory( + name=name, + create=True, + size=self.config.model.height * self.config.model.width * 3, + ) + except FileExistsError: + shm_in = mp.shared_memory.SharedMemory(name=name) + + try: + shm_out = mp.shared_memory.SharedMemory( + name=f"out-{name}", create=True, size=20 * 6 * 4 + ) + except FileExistsError: + shm_out = mp.shared_memory.SharedMemory(name=f"out-{name}") + self.detection_shms.append(shm_in) self.detection_shms.append(shm_out) for name, detector in self.config.detectors.items(): - if detector.type == 'cpu': - self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, 'cpu', detector.num_threads) - if detector.type == 'edgetpu': - self.detectors[name] = EdgeTPUProcess(name, self.detection_queue, self.detection_out_events, model_shape, detector.device, detector.num_threads) + if detector.type == DetectorTypeEnum.cpu: + self.detectors[name] = EdgeTPUProcess( + name, + self.detection_queue, + self.detection_out_events, + model_path, + model_shape, + "cpu", + detector.num_threads, + ) + if detector.type == DetectorTypeEnum.edgetpu: + self.detectors[name] = EdgeTPUProcess( + name, + self.detection_queue, + self.detection_out_events, + model_path, + model_shape, + detector.device, + detector.num_threads, + ) def start_detected_frames_processor(self): - self.detected_frames_processor = TrackedObjectProcessor(self.config, self.mqtt_client, self.config.mqtt.topic_prefix, - self.detected_frames_queue, self.event_queue, self.event_processed_queue, self.stop_event) + self.detected_frames_processor = TrackedObjectProcessor( + self.config, + self.mqtt_client, + self.config.mqtt.topic_prefix, + self.detected_frames_queue, + self.event_queue, + self.event_processed_queue, + self.video_output_queue, + self.stop_event, + ) self.detected_frames_processor.start() + def start_video_output_processor(self): + output_processor = mp.Process( + target=output_frames, + name=f"output_processor", + args=( + self.config, + self.video_output_queue, + ), + ) + output_processor.daemon = True + self.output_processor = output_processor + output_processor.start() + logger.info(f"Output process started: {output_processor.pid}") + def start_camera_processors(self): model_shape = (self.config.model.height, self.config.model.width) for name, config in self.config.cameras.items(): - camera_process = mp.Process(target=track_camera, name=f"camera_processor:{name}", args=(name, config, model_shape, - self.detection_queue, self.detection_out_events[name], self.detected_frames_queue, - self.camera_metrics[name])) + camera_process = mp.Process( + target=track_camera, + name=f"camera_processor:{name}", + args=( + name, + config, + model_shape, + self.config.model.merged_labelmap, + self.detection_queue, + self.detection_out_events[name], + self.detected_frames_queue, + self.camera_metrics[name], + ), + ) camera_process.daemon = True - self.camera_metrics[name]['process'] = camera_process + self.camera_metrics[name]["process"] = camera_process camera_process.start() logger.info(f"Camera processor started for {name}: {camera_process.pid}") def start_camera_capture_processes(self): for name, config in self.config.cameras.items(): - capture_process = mp.Process(target=capture_camera, name=f"camera_capture:{name}", args=(name, config, - self.camera_metrics[name])) + capture_process = mp.Process( + target=capture_camera, + name=f"camera_capture:{name}", + args=(name, config, self.camera_metrics[name]), + ) capture_process.daemon = True - self.camera_metrics[name]['capture_process'] = capture_process + self.camera_metrics[name]["capture_process"] = capture_process capture_process.start() logger.info(f"Capture process started for {name}: {capture_process.pid}") - + def start_event_processor(self): - self.event_processor = EventProcessor(self.config, self.camera_metrics, self.event_queue, self.event_processed_queue, self.stop_event) + self.event_processor = EventProcessor( + self.config, + self.camera_metrics, + self.event_queue, + self.event_processed_queue, + self.stop_event, + ) self.event_processor.start() - + def start_event_cleanup(self): self.event_cleanup = EventCleanup(self.config, self.stop_event) self.event_cleanup.start() - + def start_recording_maintainer(self): self.recording_maintainer = RecordingMaintainer(self.config, self.stop_event) self.recording_maintainer.start() + def start_recording_cleanup(self): + self.recording_cleanup = RecordingCleanup(self.config, self.stop_event) + self.recording_cleanup.start() + def start_stats_emitter(self): - self.stats_emitter = StatsEmitter(self.config, self.stats_tracking, self.mqtt_client, self.config.mqtt.topic_prefix, self.stop_event) + self.stats_emitter = StatsEmitter( + self.config, + self.stats_tracking, + self.mqtt_client, + self.config.mqtt.topic_prefix, + self.stop_event, + ) self.stats_emitter.start() def start_watchdog(self): @@ -204,6 +315,7 @@ class FrigateApp(): def start(self): self.init_logger() + logger.info(f"Starting Frigate ({VERSION})") try: try: self.init_config() @@ -223,14 +335,17 @@ class FrigateApp(): self.log_process.terminate() sys.exit(1) self.start_detectors() + self.start_video_output_processor() self.start_detected_frames_processor() self.start_camera_processors() self.start_camera_capture_processes() self.init_stats() self.init_web_server() + self.start_mqtt_relay() self.start_event_processor() self.start_event_cleanup() self.start_recording_maintainer() + self.start_recording_cleanup() self.start_stats_emitter() self.start_watchdog() # self.zeroconf = broadcast_zeroconf(self.config.mqtt.client_id) @@ -238,22 +353,26 @@ class FrigateApp(): def receiveSignal(signalNumber, frame): self.stop() sys.exit() - + signal.signal(signal.SIGTERM, receiveSignal) - server = pywsgi.WSGIServer(('127.0.0.1', 5001), self.flask_app, handler_class=WebSocketHandler) - server.serve_forever() + try: + self.flask_app.run(host="127.0.0.1", port=5001, debug=False) + except KeyboardInterrupt: + pass self.stop() - + def stop(self): logger.info(f"Stopping...") self.stop_event.set() + self.mqtt_relay.stop() self.detected_frames_processor.join() self.event_processor.join() self.event_cleanup.join() self.recording_maintainer.join() + self.recording_cleanup.join() self.stats_emitter.join() self.frigate_watchdog.join() self.db.stop() diff --git a/frigate/config.py b/frigate/config.py index 0878f3c1f..fcafb394f 100644 --- a/frigate/config.py +++ b/frigate/config.py @@ -1,1057 +1,806 @@ -import base64 +from __future__ import annotations + import json import logging import os -from typing import Dict +from enum import Enum +from typing import Dict, List, Optional, Tuple, Union -import cv2 import matplotlib.pyplot as plt import numpy as np -import voluptuous as vol import yaml +from pydantic import BaseModel, Extra, Field, validator +from pydantic.fields import PrivateAttr -from frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR -from frigate.util import create_mask +from frigate.const import BASE_DIR, CACHE_DIR, RECORD_DIR +from frigate.edgetpu import load_labels +from frigate.util import create_mask, deep_merge logger = logging.getLogger(__name__) -DEFAULT_TRACKED_OBJECTS = ['person'] +# TODO: Identify what the default format to display timestamps is +DEFAULT_TIME_FORMAT = "%m/%d/%Y %H:%M:%S" +# German Style: +# DEFAULT_TIME_FORMAT = "%d.%m.%Y %H:%M:%S" + +FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")} + +DEFAULT_TRACKED_OBJECTS = ["person"] +DEFAULT_DETECTORS = {"cpu": {"type": "cpu"}} + + +class FrigateBaseModel(BaseModel): + class Config: + extra = Extra.forbid + + +class DetectorTypeEnum(str, Enum): + edgetpu = "edgetpu" + cpu = "cpu" + + +class DetectorConfig(FrigateBaseModel): + type: DetectorTypeEnum = Field(default=DetectorTypeEnum.cpu, title="Detector Type") + device: str = Field(default="usb", title="Device Type") + num_threads: int = Field(default=3, title="Number of detection threads") + + +class MqttConfig(FrigateBaseModel): + host: str = Field(title="MQTT Host") + port: int = Field(default=1883, title="MQTT Port") + topic_prefix: str = Field(default="frigate", title="MQTT Topic Prefix") + client_id: str = Field(default="frigate", title="MQTT Client ID") + stats_interval: int = Field(default=60, title="MQTT Camera Stats Interval") + user: Optional[str] = Field(title="MQTT Username") + password: Optional[str] = Field(title="MQTT Password") + tls_ca_certs: Optional[str] = Field(title="MQTT TLS CA Certificates") + tls_client_cert: Optional[str] = Field(title="MQTT TLS Client Certificate") + tls_client_key: Optional[str] = Field(title="MQTT TLS Client Key") + tls_insecure: Optional[bool] = Field(title="MQTT TLS Insecure") + + @validator("password", pre=True, always=True) + def validate_password(cls, v, values): + if (v is None) != (values["user"] is None): + raise ValueError("Password must be provided with username.") + return v + + +class RetainConfig(FrigateBaseModel): + default: float = Field(default=10, title="Default retention period.") + objects: Dict[str, float] = Field( + default_factory=dict, title="Object retention period." + ) + + +class EventsConfig(FrigateBaseModel): + max_seconds: int = Field(default=300, title="Maximum event duration.") + pre_capture: int = Field(default=5, title="Seconds to retain before event starts.") + post_capture: int = Field(default=5, title="Seconds to retain after event ends.") + required_zones: List[str] = Field( + default_factory=list, + title="List of required zones to be entered in order to save the event.", + ) + objects: Optional[List[str]] = Field( + title="List of objects to be detected in order to save the event.", + ) + retain: RetainConfig = Field( + default_factory=RetainConfig, title="Event retention settings." + ) + + +class RecordConfig(FrigateBaseModel): + enabled: bool = Field(default=False, title="Enable record on all cameras.") + retain_days: float = Field(default=0, title="Recording retention period in days.") + events: EventsConfig = Field( + default_factory=EventsConfig, title="Event specific settings." + ) + + +class MotionConfig(FrigateBaseModel): + threshold: int = Field( + default=25, + title="Motion detection threshold (1-255).", + ge=1, + le=255, + ) + contour_area: Optional[int] = Field(title="Contour Area") + delta_alpha: float = Field(default=0.2, title="Delta Alpha") + frame_alpha: float = Field(default=0.2, title="Frame Alpha") + frame_height: Optional[int] = Field(title="Frame Height") + mask: Union[str, List[str]] = Field( + default="", title="Coordinates polygon for the motion mask." + ) + + +class RuntimeMotionConfig(MotionConfig): + raw_mask: Union[str, List[str]] = "" + mask: np.ndarray = None + + def __init__(self, **config): + frame_shape = config.get("frame_shape", (1, 1)) + + if "frame_height" not in config: + config["frame_height"] = max(frame_shape[0] // 6, 180) + + if "contour_area" not in config: + frame_width = frame_shape[1] * config["frame_height"] / frame_shape[0] + config["contour_area"] = ( + config["frame_height"] * frame_width * 0.00173611111 + ) + + mask = config.get("mask", "") + config["raw_mask"] = mask -DETECTORS_SCHEMA = vol.Schema( - { - vol.Required(str): { - vol.Required('type', default='edgetpu'): vol.In(['cpu', 'edgetpu']), - vol.Optional('device', default='usb'): str, - vol.Optional('num_threads', default=3): int - } - } -) - -DEFAULT_DETECTORS = { - 'coral': { - 'type': 'edgetpu', - 'device': 'usb' - } -} - -MQTT_SCHEMA = vol.Schema( - { - vol.Required('host'): str, - vol.Optional('port', default=1883): int, - vol.Optional('topic_prefix', default='frigate'): str, - vol.Optional('client_id', default='frigate'): str, - vol.Optional('stats_interval', default=60): int, - 'user': str, - 'password': str - } -) - -RETAIN_SCHEMA = vol.Schema( - { - vol.Required('default',default=10): int, - 'objects': { - str: int - } - } -) - -CLIPS_SCHEMA = vol.Schema( - { - vol.Optional('max_seconds', default=300): int, - 'tmpfs_cache_size': str, - vol.Optional('retain', default={}): RETAIN_SCHEMA - } -) - -FFMPEG_GLOBAL_ARGS_DEFAULT = ['-hide_banner','-loglevel','warning'] -FFMPEG_INPUT_ARGS_DEFAULT = ['-avoid_negative_ts', 'make_zero', - '-fflags', '+genpts+discardcorrupt', - '-rtsp_transport', 'tcp', - '-stimeout', '5000000', - '-use_wallclock_as_timestamps', '1'] -DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT = ['-f', 'rawvideo', - '-pix_fmt', 'yuv420p'] -RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-c", "copy", "-f", "flv"] -SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-f", "segment", "-segment_time", - "10", "-segment_format", "mp4", "-reset_timestamps", "1", "-strftime", - "1", "-c", "copy", "-an"] -RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-f", "segment", "-segment_time", - "60", "-segment_format", "mp4", "-reset_timestamps", "1", "-strftime", - "1", "-c", "copy", "-an"] - -GLOBAL_FFMPEG_SCHEMA = vol.Schema( - { - vol.Optional('global_args', default=FFMPEG_GLOBAL_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('hwaccel_args', default=[]): vol.Any(str, [str]), - vol.Optional('input_args', default=FFMPEG_INPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('output_args', default={}): { - vol.Optional('detect', default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('record', default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('clips', default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('rtmp', default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - } - } -) - -MOTION_SCHEMA = vol.Schema( - { - 'mask': vol.Any(str, [str]), - 'threshold': vol.Range(min=1, max=255), - 'contour_area': int, - 'delta_alpha': float, - 'frame_alpha': float, - 'frame_height': int - } -) - -DETECT_SCHEMA = vol.Schema( - { - 'max_disappeared': int - } -) - -FILTER_SCHEMA = vol.Schema( - { - str: { - 'min_area': int, - 'max_area': int, - 'threshold': float, - } - } -) - -def filters_for_all_tracked_objects(object_config): - for tracked_object in object_config.get('track', DEFAULT_TRACKED_OBJECTS): - if not 'filters' in object_config: - object_config['filters'] = {} - if not tracked_object in object_config['filters']: - object_config['filters'][tracked_object] = {} - return object_config - -OBJECTS_SCHEMA = vol.Schema(vol.All(filters_for_all_tracked_objects, - { - 'track': [str], - 'mask': vol.Any(str, [str]), - vol.Optional('filters', default = {}): FILTER_SCHEMA.extend( - { - str: { - 'min_score': float, - 'mask': vol.Any(str, [str]), - } - }) - } -)) - -def each_role_used_once(inputs): - roles = [role for i in inputs for role in i['roles']] - roles_set = set(roles) - if len(roles) > len(roles_set): - raise ValueError - return inputs - -def detect_is_required(inputs): - roles = [role for i in inputs for role in i['roles']] - if not 'detect' in roles: - raise ValueError - return inputs - -CAMERA_FFMPEG_SCHEMA = vol.Schema( - { - vol.Required('inputs'): vol.All([{ - vol.Required('path'): str, - vol.Required('roles'): ['detect', 'clips', 'record', 'rtmp'], - 'global_args': vol.Any(str, [str]), - 'hwaccel_args': vol.Any(str, [str]), - 'input_args': vol.Any(str, [str]), - }], vol.Msg(each_role_used_once, msg="Each input role may only be used once"), - vol.Msg(detect_is_required, msg="The detect role is required")), - 'global_args': vol.Any(str, [str]), - 'hwaccel_args': vol.Any(str, [str]), - 'input_args': vol.Any(str, [str]), - 'output_args': { - vol.Optional('detect', default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('record', default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('clips', default=SAVE_CLIPS_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - vol.Optional('rtmp', default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT): vol.Any(str, [str]), - } - } -) - -def ensure_zones_and_cameras_have_different_names(cameras): - zones = [zone for camera in cameras.values() for zone in camera['zones'].keys()] - for zone in zones: - if zone in cameras.keys(): - raise ValueError - return cameras - -CAMERAS_SCHEMA = vol.Schema(vol.All( - { - str: { - vol.Required('ffmpeg'): CAMERA_FFMPEG_SCHEMA, - vol.Required('height'): int, - vol.Required('width'): int, - 'fps': int, - vol.Optional('best_image_timeout', default=60): int, - vol.Optional('zones', default={}): { - str: { - vol.Required('coordinates'): vol.Any(str, [str]), - vol.Optional('filters', default={}): FILTER_SCHEMA - } - }, - vol.Optional('clips', default={}): { - vol.Optional('enabled', default=False): bool, - vol.Optional('pre_capture', default=5): int, - vol.Optional('post_capture', default=5): int, - vol.Optional('required_zones', default=[]): [str], - 'objects': [str], - vol.Optional('retain', default={}): RETAIN_SCHEMA, - }, - vol.Optional('record', default={}): { - 'enabled': bool, - 'retain_days': int, - }, - vol.Optional('rtmp', default={}): { - vol.Required('enabled', default=True): bool, - }, - vol.Optional('snapshots', default={}): { - vol.Optional('enabled', default=False): bool, - vol.Optional('timestamp', default=False): bool, - vol.Optional('bounding_box', default=False): bool, - vol.Optional('crop', default=False): bool, - vol.Optional('required_zones', default=[]): [str], - 'height': int, - vol.Optional('retain', default={}): RETAIN_SCHEMA, - }, - vol.Optional('mqtt', default={}): { - vol.Optional('enabled', default=True): bool, - vol.Optional('timestamp', default=True): bool, - vol.Optional('bounding_box', default=True): bool, - vol.Optional('crop', default=True): bool, - vol.Optional('height', default=270): int, - vol.Optional('required_zones', default=[]): [str], - }, - vol.Optional('objects', default={}): OBJECTS_SCHEMA, - vol.Optional('motion', default={}): MOTION_SCHEMA, - vol.Optional('detect', default={}): DETECT_SCHEMA.extend({ - vol.Optional('enabled', default=True): bool - }) - } - }, vol.Msg(ensure_zones_and_cameras_have_different_names, msg='Zones cannot share names with cameras')) -) - -FRIGATE_CONFIG_SCHEMA = vol.Schema( - { - vol.Optional('database', default={}): { - vol.Optional('path', default=os.path.join(CLIPS_DIR, 'frigate.db')): str - }, - vol.Optional('model', default={'width': 320, 'height': 320}): { - vol.Required('width'): int, - vol.Required('height'): int - }, - vol.Optional('detectors', default=DEFAULT_DETECTORS): DETECTORS_SCHEMA, - 'mqtt': MQTT_SCHEMA, - vol.Optional('logger', default={'default': 'info', 'logs': {}}): { - vol.Optional('default', default='info'): vol.In(['info', 'debug', 'warning', 'error', 'critical']), - vol.Optional('logs', default={}): {str: vol.In(['info', 'debug', 'warning', 'error', 'critical']) } - }, - vol.Optional('snapshots', default={}): { - vol.Optional('retain', default={}): RETAIN_SCHEMA - }, - vol.Optional('clips', default={}): CLIPS_SCHEMA, - vol.Optional('record', default={}): { - vol.Optional('enabled', default=False): bool, - vol.Optional('retain_days', default=30): int, - }, - vol.Optional('ffmpeg', default={}): GLOBAL_FFMPEG_SCHEMA, - vol.Optional('objects', default={}): OBJECTS_SCHEMA, - vol.Optional('motion', default={}): MOTION_SCHEMA, - vol.Optional('detect', default={}): DETECT_SCHEMA, - vol.Required('cameras', default={}): CAMERAS_SCHEMA, - vol.Optional('environment_vars', default={}): { str: str } - } -) - -class DatabaseConfig(): - def __init__(self, config): - self._path = config['path'] - - @property - def path(self): - return self._path - - def to_dict(self): - return { - 'path': self.path - } - -class ModelConfig(): - def __init__(self, config): - self._width = config['width'] - self._height = config['height'] - - @property - def width(self): - return self._width - - @property - def height(self): - return self._height - - def to_dict(self): - return { - 'width': self.width, - 'height': self.height - } - -class DetectorConfig(): - def __init__(self, config): - self._type = config['type'] - self._device = config['device'] - self._num_threads = config['num_threads'] - - @property - def type(self): - return self._type - - @property - def device(self): - return self._device - - @property - def num_threads(self): - return self._num_threads - - def to_dict(self): - return { - 'type': self.type, - 'device': self.device, - 'num_threads': self.num_threads - } - -class LoggerConfig(): - def __init__(self, config): - self._default = config['default'].upper() - self._logs = {k: v.upper() for k, v in config['logs'].items()} - - @property - def default(self): - return self._default - - @property - def logs(self): - return self._logs - - def to_dict(self): - return { - 'default': self.default, - 'logs': self.logs - } - -class MqttConfig(): - def __init__(self, config): - self._host = config['host'] - self._port = config['port'] - self._topic_prefix = config['topic_prefix'] - self._client_id = config['client_id'] - self._user = config.get('user') - self._password = config.get('password') - self._stats_interval = config.get('stats_interval') - - @property - def host(self): - return self._host - - @property - def port(self): - return self._port - - @property - def topic_prefix(self): - return self._topic_prefix - - @property - def client_id(self): - return self._client_id - - @property - def user(self): - return self._user - - @property - def password(self): - return self._password - - @property - def stats_interval(self): - return self._stats_interval - - def to_dict(self): - return { - 'host': self.host, - 'port': self.port, - 'topic_prefix': self.topic_prefix, - 'client_id': self.client_id, - 'user': self.user, - 'stats_interval': self.stats_interval - } - -class CameraInput(): - def __init__(self, camera_config, global_config, ffmpeg_input): - self._path = ffmpeg_input['path'] - self._roles = ffmpeg_input['roles'] - self._global_args = ffmpeg_input.get('global_args', camera_config.get('global_args', global_config['global_args'])) - self._hwaccel_args = ffmpeg_input.get('hwaccel_args', camera_config.get('hwaccel_args', global_config['hwaccel_args'])) - self._input_args = ffmpeg_input.get('input_args', camera_config.get('input_args', global_config['input_args'])) - - @property - def path(self): - return self._path - - @property - def roles(self): - return self._roles - - @property - def global_args(self): - return self._global_args if isinstance(self._global_args, list) else self._global_args.split(' ') - - @property - def hwaccel_args(self): - return self._hwaccel_args if isinstance(self._hwaccel_args, list) else self._hwaccel_args.split(' ') - - @property - def input_args(self): - return self._input_args if isinstance(self._input_args, list) else self._input_args.split(' ') - -class CameraFfmpegConfig(): - def __init__(self, global_config, config): - self._inputs = [CameraInput(config, global_config, i) for i in config['inputs']] - self._output_args = config.get('output_args', global_config['output_args']) - - @property - def inputs(self): - return self._inputs - - @property - def output_args(self): - return {k: v if isinstance(v, list) else v.split(' ') for k, v in self._output_args.items()} - -class RetainConfig(): - def __init__(self, global_config, config): - self._default = config.get('default', global_config.get('default')) - self._objects = config.get('objects', global_config.get('objects', {})) - - @property - def default(self): - return self._default - - @property - def objects(self): - return self._objects - - def to_dict(self): - return { - 'default': self.default, - 'objects': self.objects - } - -class ClipsConfig(): - def __init__(self, config): - self._max_seconds = config['max_seconds'] - self._tmpfs_cache_size = config.get('tmpfs_cache_size', '').strip() - self._retain = RetainConfig(config['retain'], config['retain']) - - @property - def max_seconds(self): - return self._max_seconds - - @property - def tmpfs_cache_size(self): - return self._tmpfs_cache_size - - @property - def retain(self): - return self._retain - - def to_dict(self): - return { - 'max_seconds': self.max_seconds, - 'tmpfs_cache_size': self.tmpfs_cache_size, - 'retain': self.retain.to_dict() - } - -class SnapshotsConfig(): - def __init__(self, config): - self._retain = RetainConfig(config['retain'], config['retain']) - - @property - def retain(self): - return self._retain - - def to_dict(self): - return { - 'retain': self.retain.to_dict() - } - -class RecordConfig(): - def __init__(self, global_config, config): - self._enabled = config.get('enabled', global_config['enabled']) - self._retain_days = config.get('retain_days', global_config['retain_days']) - - @property - def enabled(self): - return self._enabled - - @property - def retain_days(self): - return self._retain_days - - def to_dict(self): - return { - 'enabled': self.enabled, - 'retain_days': self.retain_days, - } - -class FilterConfig(): - def __init__(self, global_config, config, global_mask=None, frame_shape=None): - self._min_area = config.get('min_area', global_config.get('min_area', 0)) - self._max_area = config.get('max_area', global_config.get('max_area', 24000000)) - self._threshold = config.get('threshold', global_config.get('threshold', 0.7)) - self._min_score = config.get('min_score', global_config.get('min_score', 0.5)) - - self._raw_mask = [] - if global_mask: - if isinstance(global_mask, list): - self._raw_mask += global_mask - elif isinstance(global_mask, str): - self._raw_mask += [global_mask] - - mask = config.get('mask') if mask: - if isinstance(mask, list): - self._raw_mask += mask - elif isinstance(mask, str): - self._raw_mask += [mask] - self._mask = create_mask(frame_shape, self._raw_mask) if self._raw_mask else None - - @property - def min_area(self): - return self._min_area - - @property - def max_area(self): - return self._max_area - - @property - def threshold(self): - return self._threshold - - @property - def min_score(self): - return self._min_score - - @property - def mask(self): - return self._mask - - def to_dict(self): - return { - 'min_area': self.min_area, - 'max_area': self.max_area, - 'threshold': self.threshold, - 'min_score': self.min_score, - 'mask': self._raw_mask - } - -class ObjectConfig(): - def __init__(self, global_config, config, frame_shape): - self._track = config.get('track', global_config.get('track', DEFAULT_TRACKED_OBJECTS)) - self._raw_mask = config.get('mask') - self._filters = { name: FilterConfig(global_config['filters'].get(name, {}), config['filters'].get(name, {}), self._raw_mask, frame_shape) for name in self._track } - - @property - def track(self): - return self._track - - @property - def filters(self) -> Dict[str, FilterConfig]: - return self._filters - - def to_dict(self): - return { - 'track': self.track, - 'mask': self._raw_mask, - 'filters': { k: f.to_dict() for k, f in self.filters.items() } - } - -class CameraSnapshotsConfig(): - def __init__(self, global_config, config): - self._enabled = config['enabled'] - self._timestamp = config['timestamp'] - self._bounding_box = config['bounding_box'] - self._crop = config['crop'] - self._height = config.get('height') - self._retain = RetainConfig(global_config['snapshots']['retain'], config['retain']) - self._required_zones = config['required_zones'] - - @property - def enabled(self): - return self._enabled - - @property - def timestamp(self): - return self._timestamp - - @property - def bounding_box(self): - return self._bounding_box - - @property - def crop(self): - return self._crop - - @property - def height(self): - return self._height - - @property - def retain(self): - return self._retain - - @property - def required_zones(self): - return self._required_zones - - def to_dict(self): - return { - 'enabled': self.enabled, - 'timestamp': self.timestamp, - 'bounding_box': self.bounding_box, - 'crop': self.crop, - 'height': self.height, - 'retain': self.retain.to_dict(), - 'required_zones': self.required_zones - } - -class CameraMqttConfig(): - def __init__(self, config): - self._enabled = config['enabled'] - self._timestamp = config['timestamp'] - self._bounding_box = config['bounding_box'] - self._crop = config['crop'] - self._height = config.get('height') - self._required_zones = config['required_zones'] - - @property - def enabled(self): - return self._enabled - - @property - def timestamp(self): - return self._timestamp - - @property - def bounding_box(self): - return self._bounding_box - - @property - def crop(self): - return self._crop - - @property - def height(self): - return self._height - - @property - def required_zones(self): - return self._required_zones - - def to_dict(self): - return { - 'enabled': self.enabled, - 'timestamp': self.timestamp, - 'bounding_box': self.bounding_box, - 'crop': self.crop, - 'height': self.height, - 'required_zones': self.required_zones - } - -class CameraClipsConfig(): - def __init__(self, global_config, config): - self._enabled = config['enabled'] - self._pre_capture = config['pre_capture'] - self._post_capture = config['post_capture'] - self._objects = config.get('objects') - self._retain = RetainConfig(global_config['clips']['retain'], config['retain']) - self._required_zones = config['required_zones'] - - @property - def enabled(self): - return self._enabled - - @property - def pre_capture(self): - return self._pre_capture - - @property - def post_capture(self): - return self._post_capture - - @property - def objects(self): - return self._objects - - @property - def retain(self): - return self._retain - - @property - def required_zones(self): - return self._required_zones - - def to_dict(self): - return { - 'enabled': self.enabled, - 'pre_capture': self.pre_capture, - 'post_capture': self.post_capture, - 'objects': self.objects, - 'retain': self.retain.to_dict(), - 'required_zones': self.required_zones - } - -class CameraRtmpConfig(): - def __init__(self, global_config, config): - self._enabled = config['enabled'] - - @property - def enabled(self): - return self._enabled - - def to_dict(self): - return { - 'enabled': self.enabled, - } - -class MotionConfig(): - def __init__(self, global_config, config, frame_shape): - self._raw_mask = config.get('mask') - if self._raw_mask: - self._mask = create_mask(frame_shape, self._raw_mask) + config["mask"] = create_mask(frame_shape, mask) else: - default_mask = np.zeros(frame_shape, np.uint8) - default_mask[:] = 255 - self._mask = default_mask - self._threshold = config.get('threshold', global_config.get('threshold', 25)) - self._contour_area = config.get('contour_area', global_config.get('contour_area', 100)) - self._delta_alpha = config.get('delta_alpha', global_config.get('delta_alpha', 0.2)) - self._frame_alpha = config.get('frame_alpha', global_config.get('frame_alpha', 0.2)) - self._frame_height = config.get('frame_height', global_config.get('frame_height', frame_shape[0]//6)) + empty_mask = np.zeros(frame_shape, np.uint8) + empty_mask[:] = 255 + config["mask"] = empty_mask + + super().__init__(**config) + + def dict(self, **kwargs): + ret = super().dict(**kwargs) + if "mask" in ret: + ret["mask"] = ret["raw_mask"] + ret.pop("raw_mask") + return ret + + class Config: + arbitrary_types_allowed = True + extra = Extra.ignore + + +class DetectConfig(FrigateBaseModel): + height: int = Field(default=720, title="Height of the stream for the detect role.") + width: int = Field(default=1280, title="Width of the stream for the detect role.") + fps: int = Field( + default=5, title="Number of frames per second to process through detection." + ) + enabled: bool = Field(default=True, title="Detection Enabled.") + max_disappeared: Optional[int] = Field( + title="Maximum number of frames the object can dissapear before detection ends." + ) + + +class FilterConfig(FrigateBaseModel): + min_area: int = Field( + default=0, title="Minimum area of bounding box for object to be counted." + ) + max_area: int = Field( + default=24000000, title="Maximum area of bounding box for object to be counted." + ) + threshold: float = Field( + default=0.7, + title="Average detection confidence threshold for object to be counted.", + ) + min_score: float = Field( + default=0.5, title="Minimum detection confidence for object to be counted." + ) + mask: Optional[Union[str, List[str]]] = Field( + title="Detection area polygon mask for this filter configuration.", + ) + + +class RuntimeFilterConfig(FilterConfig): + mask: Optional[np.ndarray] + raw_mask: Optional[Union[str, List[str]]] + + def __init__(self, **config): + mask = config.get("mask") + config["raw_mask"] = mask + + if mask is not None: + config["mask"] = create_mask(config.get("frame_shape", (1, 1)), mask) + + super().__init__(**config) + + def dict(self, **kwargs): + ret = super().dict(**kwargs) + if "mask" in ret: + ret["mask"] = ret["raw_mask"] + ret.pop("raw_mask") + return ret + + class Config: + arbitrary_types_allowed = True + extra = Extra.ignore + + +# this uses the base model because the color is an extra attribute +class ZoneConfig(BaseModel): + filters: Dict[str, FilterConfig] = Field( + default_factory=dict, title="Zone filters." + ) + coordinates: Union[str, List[str]] = Field( + title="Coordinates polygon for the defined zone." + ) + objects: List[str] = Field( + default_factory=list, + title="List of objects that can trigger the zone.", + ) + _color: Optional[Tuple[int, int, int]] = PrivateAttr() + _contour: np.ndarray = PrivateAttr() @property - def mask(self): - return self._mask - - @property - def threshold(self): - return self._threshold - - @property - def contour_area(self): - return self._contour_area - - @property - def delta_alpha(self): - return self._delta_alpha - - @property - def frame_alpha(self): - return self._frame_alpha - - @property - def frame_height(self): - return self._frame_height - - def to_dict(self): - return { - 'mask': self._raw_mask, - 'threshold': self.threshold, - 'contour_area': self.contour_area, - 'delta_alpha': self.delta_alpha, - 'frame_alpha': self.frame_alpha, - 'frame_height': self.frame_height, - } - - - -class DetectConfig(): - def __init__(self, global_config, config, camera_fps): - self._enabled = config['enabled'] - self._max_disappeared = config.get('max_disappeared', global_config.get('max_disappeared', camera_fps*5)) - - @property - def enabled(self): - return self._enabled - - @property - def max_disappeared(self): - return self._max_disappeared - - def to_dict(self): - return { - 'enabled': self.enabled, - 'max_disappeared': self._max_disappeared, - } - -class ZoneConfig(): - def __init__(self, name, config): - self._coordinates = config['coordinates'] - self._filters = { name: FilterConfig(c, c) for name, c in config['filters'].items() } - - if isinstance(self._coordinates, list): - self._contour = np.array([[int(p.split(',')[0]), int(p.split(',')[1])] for p in self._coordinates]) - elif isinstance(self._coordinates, str): - points = self._coordinates.split(',') - self._contour = np.array([[int(points[i]), int(points[i+1])] for i in range(0, len(points), 2)]) - else: - print(f"Unable to parse zone coordinates for {name}") - self._contour = np.array([]) - - self._color = (0,0,0) - - @property - def coordinates(self): - return self._coordinates - - @property - def contour(self): - return self._contour - - @contour.setter - def contour(self, val): - self._contour = val - - @property - def color(self): + def color(self) -> Tuple[int, int, int]: return self._color - @color.setter - def color(self, val): - self._color = val + @property + def contour(self) -> np.ndarray: + return self._contour + + def __init__(self, **config): + super().__init__(**config) + + self._color = config.get("color", (0, 0, 0)) + coordinates = config["coordinates"] + + if isinstance(coordinates, list): + self._contour = np.array( + [[int(p.split(",")[0]), int(p.split(",")[1])] for p in coordinates] + ) + elif isinstance(coordinates, str): + points = coordinates.split(",") + self._contour = np.array( + [[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)] + ) + else: + self._contour = np.array([]) + + +class ObjectConfig(FrigateBaseModel): + track: List[str] = Field(default=DEFAULT_TRACKED_OBJECTS, title="Objects to track.") + filters: Optional[Dict[str, FilterConfig]] = Field(title="Object filters.") + mask: Union[str, List[str]] = Field(default="", title="Object mask.") + + +class BirdseyeModeEnum(str, Enum): + objects = "objects" + motion = "motion" + continuous = "continuous" + + +class BirdseyeConfig(FrigateBaseModel): + enabled: bool = Field(default=True, title="Enable birdseye view.") + width: int = Field(default=1280, title="Birdseye width.") + height: int = Field(default=720, title="Birdseye height.") + quality: int = Field( + default=8, + title="Encoding quality.", + ge=1, + le=31, + ) + mode: BirdseyeModeEnum = Field( + default=BirdseyeModeEnum.objects, title="Tracking mode." + ) + + +FFMPEG_GLOBAL_ARGS_DEFAULT = ["-hide_banner", "-loglevel", "warning"] +FFMPEG_INPUT_ARGS_DEFAULT = [ + "-avoid_negative_ts", + "make_zero", + "-fflags", + "+genpts+discardcorrupt", + "-rtsp_transport", + "tcp", + "-stimeout", + "5000000", + "-use_wallclock_as_timestamps", + "1", +] +DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-f", "rawvideo", "-pix_fmt", "yuv420p"] +RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT = ["-c", "copy", "-f", "flv"] +RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT = [ + "-f", + "segment", + "-segment_time", + "10", + "-segment_format", + "mp4", + "-reset_timestamps", + "1", + "-strftime", + "1", + "-c", + "copy", + "-an", +] + + +class FfmpegOutputArgsConfig(FrigateBaseModel): + detect: Union[str, List[str]] = Field( + default=DETECT_FFMPEG_OUTPUT_ARGS_DEFAULT, + title="Detect role FFmpeg output arguments.", + ) + record: Union[str, List[str]] = Field( + default=RECORD_FFMPEG_OUTPUT_ARGS_DEFAULT, + title="Record role FFmpeg output arguments.", + ) + rtmp: Union[str, List[str]] = Field( + default=RTMP_FFMPEG_OUTPUT_ARGS_DEFAULT, + title="RTMP role FFmpeg output arguments.", + ) + + +class FfmpegConfig(FrigateBaseModel): + global_args: Union[str, List[str]] = Field( + default=FFMPEG_GLOBAL_ARGS_DEFAULT, title="Global FFmpeg arguments." + ) + hwaccel_args: Union[str, List[str]] = Field( + default_factory=list, title="FFmpeg hardware acceleration arguments." + ) + input_args: Union[str, List[str]] = Field( + default=FFMPEG_INPUT_ARGS_DEFAULT, title="FFmpeg input arguments." + ) + output_args: FfmpegOutputArgsConfig = Field( + default_factory=FfmpegOutputArgsConfig, + title="FFmpeg output arguments per role.", + ) + + +class CameraRoleEnum(str, Enum): + record = "record" + rtmp = "rtmp" + detect = "detect" + + +class CameraInput(FrigateBaseModel): + path: str = Field(title="Camera input path.") + roles: List[CameraRoleEnum] = Field(title="Roles assigned to this input.") + global_args: Union[str, List[str]] = Field( + default_factory=list, title="FFmpeg global arguments." + ) + hwaccel_args: Union[str, List[str]] = Field( + default_factory=list, title="FFmpeg hardware acceleration arguments." + ) + input_args: Union[str, List[str]] = Field( + default_factory=list, title="FFmpeg input arguments." + ) + + +class CameraFfmpegConfig(FfmpegConfig): + inputs: List[CameraInput] = Field(title="Camera inputs.") + + @validator("inputs") + def validate_roles(cls, v): + roles = [role for i in v for role in i.roles] + roles_set = set(roles) + + if len(roles) > len(roles_set): + raise ValueError("Each input role may only be used once.") + + if not "detect" in roles: + raise ValueError("The detect role is required.") + + return v + + +class SnapshotsConfig(FrigateBaseModel): + enabled: bool = Field(default=False, title="Snapshots enabled.") + clean_copy: bool = Field( + default=True, title="Create a clean copy of the snapshot image." + ) + timestamp: bool = Field( + default=False, title="Add a timestamp overlay on the snapshot." + ) + bounding_box: bool = Field( + default=True, title="Add a bounding box overlay on the snapshot." + ) + crop: bool = Field(default=False, title="Crop the snapshot to the detected object.") + required_zones: List[str] = Field( + default_factory=list, + title="List of required zones to be entered in order to save a snapshot.", + ) + height: Optional[int] = Field(title="Snapshot image height.") + retain: RetainConfig = Field( + default_factory=RetainConfig, title="Snapshot retention." + ) + quality: int = Field( + default=70, + title="Quality of the encoded jpeg (0-100).", + ge=0, + le=100, + ) + + +class ColorConfig(FrigateBaseModel): + red: int = Field(default=255, ge=0, le=255, title="Red") + green: int = Field(default=255, ge=0, le=255, title="Green") + blue: int = Field(default=255, ge=0, le=255, title="Blue") + + +class TimestampPositionEnum(str, Enum): + tl = "tl" + tr = "tr" + bl = "bl" + br = "br" + + +class TimestampEffectEnum(str, Enum): + solid = "solid" + shadow = "shadow" + + +class TimestampStyleConfig(FrigateBaseModel): + position: TimestampPositionEnum = Field( + default=TimestampPositionEnum.tl, title="Timestamp position." + ) + format: str = Field(default=DEFAULT_TIME_FORMAT, title="Timestamp format.") + color: ColorConfig = Field(default_factory=ColorConfig, title="Timestamp color.") + thickness: int = Field(default=2, title="Timestamp thickness.") + effect: Optional[TimestampEffectEnum] = Field(title="Timestamp effect.") + + +class CameraMqttConfig(FrigateBaseModel): + enabled: bool = Field(default=True, title="Send image over MQTT.") + timestamp: bool = Field(default=True, title="Add timestamp to MQTT image.") + bounding_box: bool = Field(default=True, title="Add bounding box to MQTT image.") + crop: bool = Field(default=True, title="Crop MQTT image to detected object.") + height: int = Field(default=270, title="MQTT image height.") + required_zones: List[str] = Field( + default_factory=list, + title="List of required zones to be entered in order to send the image.", + ) + quality: int = Field( + default=70, + title="Quality of the encoded jpeg (0-100).", + ge=0, + le=100, + ) + + +class RtmpConfig(FrigateBaseModel): + enabled: bool = Field(default=True, title="RTMP restreaming enabled.") + + +class CameraLiveConfig(FrigateBaseModel): + height: int = Field(default=720, title="Live camera view height") + quality: int = Field(default=8, ge=1, le=31, title="Live camera view quality") + + +class CameraConfig(FrigateBaseModel): + name: Optional[str] = Field(title="Camera name.") + ffmpeg: CameraFfmpegConfig = Field(title="FFmpeg configuration for the camera.") + best_image_timeout: int = Field( + default=60, + title="How long to wait for the image with the highest confidence score.", + ) + zones: Dict[str, ZoneConfig] = Field( + default_factory=dict, title="Zone configuration." + ) + record: RecordConfig = Field( + default_factory=RecordConfig, title="Record configuration." + ) + rtmp: RtmpConfig = Field( + default_factory=RtmpConfig, title="RTMP restreaming configuration." + ) + live: CameraLiveConfig = Field( + default_factory=CameraLiveConfig, title="Live playback settings." + ) + snapshots: SnapshotsConfig = Field( + default_factory=SnapshotsConfig, title="Snapshot configuration." + ) + mqtt: CameraMqttConfig = Field( + default_factory=CameraMqttConfig, title="MQTT configuration." + ) + objects: ObjectConfig = Field( + default_factory=ObjectConfig, title="Object configuration." + ) + motion: Optional[MotionConfig] = Field(title="Motion detection configuration.") + detect: DetectConfig = Field( + default_factory=DetectConfig, title="Object detection configuration." + ) + timestamp_style: TimestampStyleConfig = Field( + default_factory=TimestampStyleConfig, title="Timestamp style configuration." + ) + + def __init__(self, **config): + # Set zone colors + if "zones" in config: + colors = plt.cm.get_cmap("tab10", len(config["zones"])) + config["zones"] = { + name: {**z, "color": tuple(round(255 * c) for c in colors(idx)[:3])} + for idx, (name, z) in enumerate(config["zones"].items()) + } + + super().__init__(**config) @property - def filters(self): - return self._filters + def frame_shape(self) -> Tuple[int, int]: + return self.detect.height, self.detect.width - def to_dict(self): - return { - 'filters': {k: f.to_dict() for k, f in self.filters.items()}, - 'coordinates': self._coordinates - } + @property + def frame_shape_yuv(self) -> Tuple[int, int]: + return self.detect.height * 3 // 2, self.detect.width -class CameraConfig(): - def __init__(self, name, config, global_config): - self._name = name - self._ffmpeg = CameraFfmpegConfig(global_config['ffmpeg'], config['ffmpeg']) - self._height = config.get('height') - self._width = config.get('width') - self._frame_shape = (self._height, self._width) - self._frame_shape_yuv = (self._frame_shape[0]*3//2, self._frame_shape[1]) - self._fps = config.get('fps') - self._best_image_timeout = config['best_image_timeout'] - self._zones = { name: ZoneConfig(name, z) for name, z in config['zones'].items() } - self._clips = CameraClipsConfig(global_config, config['clips']) - self._record = RecordConfig(global_config['record'], config['record']) - self._rtmp = CameraRtmpConfig(global_config, config['rtmp']) - self._snapshots = CameraSnapshotsConfig(global_config, config['snapshots']) - self._mqtt = CameraMqttConfig(config['mqtt']) - self._objects = ObjectConfig(global_config['objects'], config.get('objects', {}), self._frame_shape) - self._motion = MotionConfig(global_config['motion'], config['motion'], self._frame_shape) - self._detect = DetectConfig(global_config['detect'], config['detect'], config.get('fps', 5)) - - self._ffmpeg_cmds = [] - for ffmpeg_input in self._ffmpeg.inputs: + @property + def ffmpeg_cmds(self) -> List[Dict[str, List[str]]]: + ffmpeg_cmds = [] + for ffmpeg_input in self.ffmpeg.inputs: ffmpeg_cmd = self._get_ffmpeg_cmd(ffmpeg_input) if ffmpeg_cmd is None: continue - self._ffmpeg_cmds.append({ - 'roles': ffmpeg_input.roles, - 'cmd': ffmpeg_cmd - }) + ffmpeg_cmds.append({"roles": ffmpeg_input.roles, "cmd": ffmpeg_cmd}) + return ffmpeg_cmds - - self._set_zone_colors(self._zones) - - def _get_ffmpeg_cmd(self, ffmpeg_input): + def _get_ffmpeg_cmd(self, ffmpeg_input: CameraInput): ffmpeg_output_args = [] - if 'detect' in ffmpeg_input.roles: - ffmpeg_output_args = self.ffmpeg.output_args['detect'] + ffmpeg_output_args + ['pipe:'] - if self.fps: - ffmpeg_output_args = ["-r", str(self.fps)] + ffmpeg_output_args - if 'rtmp' in ffmpeg_input.roles and self.rtmp.enabled: - ffmpeg_output_args = self.ffmpeg.output_args['rtmp'] + [ - f"rtmp://127.0.0.1/live/{self.name}" - ] + ffmpeg_output_args - if 'clips' in ffmpeg_input.roles: - ffmpeg_output_args = self.ffmpeg.output_args['clips'] + [ - f"{os.path.join(CACHE_DIR, self.name)}-%Y%m%d%H%M%S.mp4" - ] + ffmpeg_output_args - if 'record' in ffmpeg_input.roles and self.record.enabled: - ffmpeg_output_args = self.ffmpeg.output_args['record'] + [ - f"{os.path.join(RECORD_DIR, self.name)}-%Y%m%d%H%M%S.mp4" - ] + ffmpeg_output_args + if "detect" in ffmpeg_input.roles: + detect_args = ( + self.ffmpeg.output_args.detect + if isinstance(self.ffmpeg.output_args.detect, list) + else self.ffmpeg.output_args.detect.split(" ") + ) + ffmpeg_output_args = ( + [ + "-r", + str(self.detect.fps), + "-s", + f"{self.detect.width}x{self.detect.height}", + ] + + detect_args + + ffmpeg_output_args + + ["pipe:"] + ) + if "rtmp" in ffmpeg_input.roles and self.rtmp.enabled: + rtmp_args = ( + self.ffmpeg.output_args.rtmp + if isinstance(self.ffmpeg.output_args.rtmp, list) + else self.ffmpeg.output_args.rtmp.split(" ") + ) + ffmpeg_output_args = ( + rtmp_args + [f"rtmp://127.0.0.1/live/{self.name}"] + ffmpeg_output_args + ) + if "record" in ffmpeg_input.roles and self.record.enabled: + record_args = ( + self.ffmpeg.output_args.record + if isinstance(self.ffmpeg.output_args.record, list) + else self.ffmpeg.output_args.record.split(" ") + ) + ffmpeg_output_args = ( + record_args + + [f"{os.path.join(CACHE_DIR, self.name)}-%Y%m%d%H%M%S.mp4"] + + ffmpeg_output_args + ) # if there arent any outputs enabled for this input if len(ffmpeg_output_args) == 0: return None - cmd = (['ffmpeg'] + - ffmpeg_input.global_args + - ffmpeg_input.hwaccel_args + - ffmpeg_input.input_args + - ['-i', ffmpeg_input.path] + - ffmpeg_output_args) + global_args = ffmpeg_input.global_args or self.ffmpeg.global_args + hwaccel_args = ffmpeg_input.hwaccel_args or self.ffmpeg.hwaccel_args + input_args = ffmpeg_input.input_args or self.ffmpeg.input_args - return [part for part in cmd if part != ''] + global_args = ( + global_args if isinstance(global_args, list) else global_args.split(" ") + ) + hwaccel_args = ( + hwaccel_args if isinstance(hwaccel_args, list) else hwaccel_args.split(" ") + ) + input_args = ( + input_args if isinstance(input_args, list) else input_args.split(" ") + ) - def _set_zone_colors(self, zones: Dict[str, ZoneConfig]): - # set colors for zones - all_zone_names = zones.keys() - zone_colors = {} - colors = plt.cm.get_cmap('tab10', len(all_zone_names)) - for i, zone in enumerate(all_zone_names): - zone_colors[zone] = tuple(int(round(255 * c)) for c in colors(i)[:3]) + cmd = ( + ["ffmpeg"] + + global_args + + hwaccel_args + + input_args + + ["-i", ffmpeg_input.path] + + ffmpeg_output_args + ) - for name, zone in zones.items(): - zone.color = zone_colors[name] + return [part for part in cmd if part != ""] + + +class DatabaseConfig(FrigateBaseModel): + path: str = Field( + default=os.path.join(BASE_DIR, "frigate.db"), title="Database path." + ) + + +class ModelConfig(FrigateBaseModel): + path: Optional[str] = Field(title="Custom Object detection model path.") + labelmap_path: Optional[str] = Field(title="Label map for custom object detector.") + width: int = Field(default=320, title="Object detection model input width.") + height: int = Field(default=320, title="Object detection model input height.") + labelmap: Dict[int, str] = Field( + default_factory=dict, title="Labelmap customization." + ) + _merged_labelmap: Optional[Dict[int, str]] = PrivateAttr() + _colormap: Dict[int, Tuple[int, int, int]] = PrivateAttr() @property - def name(self): - return self._name + def merged_labelmap(self) -> Dict[int, str]: + return self._merged_labelmap @property - def ffmpeg(self): - return self._ffmpeg + def colormap(self) -> Dict[int, tuple[int, int, int]]: + return self._colormap - @property - def height(self): - return self._height + def __init__(self, **config): + super().__init__(**config) - @property - def width(self): - return self._width - - @property - def fps(self): - return self._fps - - @property - def best_image_timeout(self): - return self._best_image_timeout - - @property - def zones(self)-> Dict[str, ZoneConfig]: - return self._zones - - @property - def clips(self): - return self._clips - - @property - def record(self): - return self._record - - @property - def rtmp(self): - return self._rtmp - - @property - def snapshots(self): - return self._snapshots - - @property - def mqtt(self): - return self._mqtt - - @property - def objects(self): - return self._objects - - @property - def motion(self): - return self._motion - - @property - def detect(self): - return self._detect - - @property - def frame_shape(self): - return self._frame_shape - - @property - def frame_shape_yuv(self): - return self._frame_shape_yuv - - @property - def ffmpeg_cmds(self): - return self._ffmpeg_cmds - - def to_dict(self): - return { - 'name': self.name, - 'height': self.height, - 'width': self.width, - 'fps': self.fps, - 'best_image_timeout': self.best_image_timeout, - 'zones': {k: z.to_dict() for k, z in self.zones.items()}, - 'clips': self.clips.to_dict(), - 'record': self.record.to_dict(), - 'rtmp': self.rtmp.to_dict(), - 'snapshots': self.snapshots.to_dict(), - 'mqtt': self.mqtt.to_dict(), - 'objects': self.objects.to_dict(), - 'motion': self.motion.to_dict(), - 'detect': self.detect.to_dict(), - 'frame_shape': self.frame_shape, - 'ffmpeg_cmds': [{'roles': c['roles'], 'cmd': ' '.join(c['cmd'])} for c in self.ffmpeg_cmds], + self._merged_labelmap = { + **load_labels(config.get("labelmap_path", "/labelmap.txt")), + **config.get("labelmap", {}), } + cmap = plt.cm.get_cmap("tab10", len(self._merged_labelmap.keys())) -class FrigateConfig(): - def __init__(self, config_file=None, config=None): - if config is None and config_file is None: - raise ValueError('config or config_file must be defined') - elif not config_file is None: - config = self._load_file(config_file) + self._colormap = {} + for key, val in self._merged_labelmap.items(): + self._colormap[val] = tuple(int(round(255 * c)) for c in cmap(key)[:3]) - config = FRIGATE_CONFIG_SCHEMA(config) - config = self._sub_env_vars(config) +class LogLevelEnum(str, Enum): + debug = "debug" + info = "info" + warning = "warning" + error = "error" + critical = "critical" - self._database = DatabaseConfig(config['database']) - self._model = ModelConfig(config['model']) - self._detectors = { name: DetectorConfig(d) for name, d in config['detectors'].items() } - self._mqtt = MqttConfig(config['mqtt']) - self._clips = ClipsConfig(config['clips']) - self._snapshots = SnapshotsConfig(config['snapshots']) - self._cameras = { name: CameraConfig(name, c, config) for name, c in config['cameras'].items() } - self._logger = LoggerConfig(config['logger']) - self._environment_vars = config['environment_vars'] - def _sub_env_vars(self, config): - frigate_env_vars = {k: v for k, v in os.environ.items() if k.startswith('FRIGATE_')} +class LoggerConfig(FrigateBaseModel): + default: LogLevelEnum = Field( + default=LogLevelEnum.info, title="Default logging level." + ) + logs: Dict[str, LogLevelEnum] = Field( + default_factory=dict, title="Log level for specified processes." + ) - if 'password' in config['mqtt']: - config['mqtt']['password'] = config['mqtt']['password'].format(**frigate_env_vars) - for camera in config['cameras'].values(): - for i in camera['ffmpeg']['inputs']: - i['path'] = i['path'].format(**frigate_env_vars) +class FrigateConfig(FrigateBaseModel): + mqtt: MqttConfig = Field(title="MQTT Configuration.") + database: DatabaseConfig = Field( + default_factory=DatabaseConfig, title="Database configuration." + ) + environment_vars: Dict[str, str] = Field( + default_factory=dict, title="Frigate environment variables." + ) + model: ModelConfig = Field( + default_factory=ModelConfig, title="Detection model configuration." + ) + detectors: Dict[str, DetectorConfig] = Field( + default={name: DetectorConfig(**d) for name, d in DEFAULT_DETECTORS.items()}, + title="Detector hardware configuration.", + ) + logger: LoggerConfig = Field( + default_factory=LoggerConfig, title="Logging configuration." + ) + record: RecordConfig = Field( + default_factory=RecordConfig, title="Global record configuration." + ) + snapshots: SnapshotsConfig = Field( + default_factory=SnapshotsConfig, title="Global snapshots configuration." + ) + live: CameraLiveConfig = Field( + default_factory=CameraLiveConfig, title="Global live configuration." + ) + rtmp: RtmpConfig = Field( + default_factory=RtmpConfig, title="Global RTMP restreaming configuration." + ) + birdseye: BirdseyeConfig = Field( + default_factory=BirdseyeConfig, title="Birdseye configuration." + ) + ffmpeg: FfmpegConfig = Field( + default_factory=FfmpegConfig, title="Global FFmpeg configuration." + ) + objects: ObjectConfig = Field( + default_factory=ObjectConfig, title="Global object configuration." + ) + motion: Optional[MotionConfig] = Field( + title="Global motion detection configuration." + ) + detect: DetectConfig = Field( + default_factory=DetectConfig, title="Global object tracking configuration." + ) + cameras: Dict[str, CameraConfig] = Field(title="Camera configuration.") + timestamp_style: TimestampStyleConfig = Field( + default_factory=TimestampStyleConfig, + title="Global timestamp style configuration.", + ) + + @property + def runtime_config(self) -> FrigateConfig: + """Merge camera config with globals.""" + config = self.copy(deep=True) + + # MQTT password substitution + if config.mqtt.password: + config.mqtt.password = config.mqtt.password.format(**FRIGATE_ENV_VARS) + + # Global config to propegate down to camera level + global_config = config.dict( + include={ + "record": ..., + "snapshots": ..., + "live": ..., + "rtmp": ..., + "objects": ..., + "motion": ..., + "detect": ..., + "ffmpeg": ..., + "timestamp_style": ..., + }, + exclude_unset=True, + ) + + for name, camera in config.cameras.items(): + merged_config = deep_merge(camera.dict(exclude_unset=True), global_config) + camera_config: CameraConfig = CameraConfig.parse_obj( + {"name": name, **merged_config} + ) + + # Default max_disappeared configuration + max_disappeared = camera_config.detect.fps * 5 + if camera_config.detect.max_disappeared is None: + camera_config.detect.max_disappeared = max_disappeared + + # FFMPEG input substitution + for input in camera_config.ffmpeg.inputs: + input.path = input.path.format(**FRIGATE_ENV_VARS) + + # Add default filters + object_keys = camera_config.objects.track + if camera_config.objects.filters is None: + camera_config.objects.filters = {} + object_keys = object_keys - camera_config.objects.filters.keys() + for key in object_keys: + camera_config.objects.filters[key] = FilterConfig() + + # Apply global object masks and convert masks to numpy array + for object, filter in camera_config.objects.filters.items(): + if camera_config.objects.mask: + filter_mask = [] + if filter.mask is not None: + filter_mask = ( + filter.mask + if isinstance(filter.mask, list) + else [filter.mask] + ) + object_mask = ( + camera_config.objects.mask + if isinstance(camera_config.objects.mask, list) + else [camera_config.objects.mask] + ) + filter.mask = filter_mask + object_mask + + # Set runtime filter to create masks + camera_config.objects.filters[object] = RuntimeFilterConfig( + frame_shape=camera_config.frame_shape, + **filter.dict(exclude_unset=True), + ) + + # Convert motion configuration + if camera_config.motion is None: + camera_config.motion = RuntimeMotionConfig( + frame_shape=camera_config.frame_shape + ) + else: + camera_config.motion = RuntimeMotionConfig( + frame_shape=camera_config.frame_shape, + raw_mask=camera_config.motion.mask, + **camera_config.motion.dict(exclude_unset=True), + ) + + config.cameras[name] = camera_config return config - def _load_file(self, config_file): + @validator("cameras") + def ensure_zones_and_cameras_have_different_names(cls, v: Dict[str, CameraConfig]): + zones = [zone for camera in v.values() for zone in camera.zones.keys()] + for zone in zones: + if zone in v.keys(): + raise ValueError("Zones cannot share names with cameras") + return v + + @classmethod + def parse_file(cls, config_file): with open(config_file) as f: raw_config = f.read() @@ -1060,53 +809,4 @@ class FrigateConfig(): elif config_file.endswith(".json"): config = json.loads(raw_config) - return config - - def to_dict(self): - return { - 'database': self.database.to_dict(), - 'model': self.model.to_dict(), - 'detectors': {k: d.to_dict() for k, d in self.detectors.items()}, - 'mqtt': self.mqtt.to_dict(), - 'clips': self.clips.to_dict(), - 'snapshots': self.snapshots.to_dict(), - 'cameras': {k: c.to_dict() for k, c in self.cameras.items()}, - 'logger': self.logger.to_dict(), - 'environment_vars': self._environment_vars - } - - @property - def database(self): - return self._database - - @property - def model(self): - return self._model - - @property - def detectors(self) -> Dict[str, DetectorConfig]: - return self._detectors - - @property - def logger(self): - return self._logger - - @property - def mqtt(self): - return self._mqtt - - @property - def clips(self): - return self._clips - - @property - def snapshots(self): - return self._snapshots - - @property - def cameras(self) -> Dict[str, CameraConfig]: - return self._cameras - - @property - def environment_vars(self): - return self._environment_vars + return cls.parse_obj(config) diff --git a/frigate/const.py b/frigate/const.py index 2ea9f9f68..c2b0f8e9d 100644 --- a/frigate/const.py +++ b/frigate/const.py @@ -1,3 +1,4 @@ -CLIPS_DIR = '/media/frigate/clips' -RECORD_DIR = '/media/frigate/recordings' -CACHE_DIR = '/tmp/cache' \ No newline at end of file +BASE_DIR = "/media/frigate" +CLIPS_DIR = f"{BASE_DIR}/clips" +RECORD_DIR = f"{BASE_DIR}/recordings" +CACHE_DIR = "/tmp/cache" diff --git a/frigate/edgetpu.py b/frigate/edgetpu.py index d65ce523b..1992c6b35 100644 --- a/frigate/edgetpu.py +++ b/frigate/edgetpu.py @@ -1,50 +1,51 @@ import datetime -import hashlib import logging import multiprocessing as mp import os import queue -import threading import signal +import threading from abc import ABC, abstractmethod -from multiprocessing.connection import Connection -from setproctitle import setproctitle from typing import Dict import numpy as np import tflite_runtime.interpreter as tflite +from setproctitle import setproctitle from tflite_runtime.interpreter import load_delegate from frigate.util import EventsPerSecond, SharedMemoryFrameManager, listen logger = logging.getLogger(__name__) -def load_labels(path, encoding='utf-8'): - """Loads labels from file (with or without index numbers). - Args: - path: path to label file. - encoding: label file encoding. - Returns: - Dictionary mapping indices to labels. - """ - with open(path, 'r', encoding=encoding) as f: - lines = f.readlines() - if not lines: - return {} - if lines[0].split(' ', maxsplit=1)[0].isdigit(): - pairs = [line.split(' ', maxsplit=1) for line in lines] - return {int(index): label.strip() for index, label in pairs} - else: - return {index: line.strip() for index, line in enumerate(lines)} +def load_labels(path, encoding="utf-8"): + """Loads labels from file (with or without index numbers). + Args: + path: path to label file. + encoding: label file encoding. + Returns: + Dictionary mapping indices to labels. + """ + with open(path, "r", encoding=encoding) as f: + lines = f.readlines() + if not lines: + return {} + + if lines[0].split(" ", maxsplit=1)[0].isdigit(): + pairs = [line.split(" ", maxsplit=1) for line in lines] + return {int(index): label.strip() for index, label in pairs} + else: + return {index: line.strip() for index, line in enumerate(lines)} + class ObjectDetector(ABC): @abstractmethod - def detect(self, tensor_input, threshold = .4): + def detect(self, tensor_input, threshold=0.4): pass + class LocalObjectDetector(ObjectDetector): - def __init__(self, tf_device=None, num_threads=3, labels=None): + def __init__(self, tf_device=None, model_path=None, num_threads=3, labels=None): self.fps = EventsPerSecond() if labels is None: self.labels = {} @@ -57,27 +58,34 @@ class LocalObjectDetector(ObjectDetector): edge_tpu_delegate = None - if tf_device != 'cpu': + if tf_device != "cpu": try: logger.info(f"Attempting to load TPU as {device_config['device']}") - edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', device_config) + edge_tpu_delegate = load_delegate("libedgetpu.so.1.0", device_config) logger.info("TPU found") self.interpreter = tflite.Interpreter( - model_path='/edgetpu_model.tflite', - experimental_delegates=[edge_tpu_delegate]) + model_path=model_path or "/edgetpu_model.tflite", + experimental_delegates=[edge_tpu_delegate], + ) except ValueError: - logger.info("No EdgeTPU detected.") + logger.error( + "No EdgeTPU was detected. If you do not have a Coral device yet, you must configure CPU detectors." + ) raise else: + logger.warning( + "CPU detectors are not recommended and should only be used for testing or for trial purposes." + ) self.interpreter = tflite.Interpreter( - model_path='/cpu_model.tflite', num_threads=num_threads) - + model_path=model_path or "/cpu_model.tflite", num_threads=num_threads + ) + self.interpreter.allocate_tensors() self.tensor_input_details = self.interpreter.get_input_details() self.tensor_output_details = self.interpreter.get_output_details() - - def detect(self, tensor_input, threshold=.4): + + def detect(self, tensor_input, threshold=0.4): detections = [] raw_detections = self.detect_raw(tensor_input) @@ -85,28 +93,51 @@ class LocalObjectDetector(ObjectDetector): for d in raw_detections: if d[1] < threshold: break - detections.append(( - self.labels[int(d[0])], - float(d[1]), - (d[2], d[3], d[4], d[5]) - )) + detections.append( + (self.labels[int(d[0])], float(d[1]), (d[2], d[3], d[4], d[5])) + ) self.fps.update() return detections def detect_raw(self, tensor_input): - self.interpreter.set_tensor(self.tensor_input_details[0]['index'], tensor_input) + self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input) self.interpreter.invoke() - boxes = np.squeeze(self.interpreter.get_tensor(self.tensor_output_details[0]['index'])) - label_codes = np.squeeze(self.interpreter.get_tensor(self.tensor_output_details[1]['index'])) - scores = np.squeeze(self.interpreter.get_tensor(self.tensor_output_details[2]['index'])) - detections = np.zeros((20,6), np.float32) - for i, score in enumerate(scores): - detections[i] = [label_codes[i], score, boxes[i][0], boxes[i][1], boxes[i][2], boxes[i][3]] - + boxes = self.interpreter.tensor(self.tensor_output_details[0]["index"])()[0] + class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0] + scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0] + count = int( + self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0] + ) + + detections = np.zeros((20, 6), np.float32) + + for i in range(count): + if scores[i] < 0.4 or i == 20: + break + detections[i] = [ + class_ids[i], + float(scores[i]), + boxes[i][0], + boxes[i][1], + boxes[i][2], + boxes[i][3], + ] + return detections -def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp.Event], avg_speed, start, model_shape, tf_device, num_threads): + +def run_detector( + name: str, + detection_queue: mp.Queue, + out_events: Dict[str, mp.Event], + avg_speed, + start, + model_path, + model_shape, + tf_device, + num_threads, +): threading.current_thread().name = f"detector:{name}" logger = logging.getLogger(f"detector.{name}") logger.info(f"Starting detection process: {os.getpid()}") @@ -114,33 +145,32 @@ def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp. listen() stop_event = mp.Event() + def receiveSignal(signalNumber, frame): stop_event.set() - + signal.signal(signal.SIGTERM, receiveSignal) signal.signal(signal.SIGINT, receiveSignal) frame_manager = SharedMemoryFrameManager() - object_detector = LocalObjectDetector(tf_device=tf_device, num_threads=num_threads) + object_detector = LocalObjectDetector( + tf_device=tf_device, model_path=model_path, num_threads=num_threads + ) outputs = {} for name in out_events.keys(): out_shm = mp.shared_memory.SharedMemory(name=f"out-{name}", create=False) - out_np = np.ndarray((20,6), dtype=np.float32, buffer=out_shm.buf) - outputs[name] = { - 'shm': out_shm, - 'np': out_np - } - - while True: - if stop_event.is_set(): - break + out_np = np.ndarray((20, 6), dtype=np.float32, buffer=out_shm.buf) + outputs[name] = {"shm": out_shm, "np": out_np} + while not stop_event.is_set(): try: connection_id = detection_queue.get(timeout=5) except queue.Empty: continue - input_frame = frame_manager.get(connection_id, (1,model_shape[0],model_shape[1],3)) + input_frame = frame_manager.get( + connection_id, (1, model_shape[0], model_shape[1], 3) + ) if input_frame is None: continue @@ -148,26 +178,37 @@ def run_detector(name: str, detection_queue: mp.Queue, out_events: Dict[str, mp. # detect and send the output start.value = datetime.datetime.now().timestamp() detections = object_detector.detect_raw(input_frame) - duration = datetime.datetime.now().timestamp()-start.value - outputs[connection_id]['np'][:] = detections[:] + duration = datetime.datetime.now().timestamp() - start.value + outputs[connection_id]["np"][:] = detections[:] out_events[connection_id].set() start.value = 0.0 - avg_speed.value = (avg_speed.value*9 + duration)/10 - -class EdgeTPUProcess(): - def __init__(self, name, detection_queue, out_events, model_shape, tf_device=None, num_threads=3): + avg_speed.value = (avg_speed.value * 9 + duration) / 10 + + +class EdgeTPUProcess: + def __init__( + self, + name, + detection_queue, + out_events, + model_path, + model_shape, + tf_device=None, + num_threads=3, + ): self.name = name self.out_events = out_events self.detection_queue = detection_queue - self.avg_inference_speed = mp.Value('d', 0.01) - self.detection_start = mp.Value('d', 0.0) + self.avg_inference_speed = mp.Value("d", 0.01) + self.detection_start = mp.Value("d", 0.0) self.detect_process = None + self.model_path = model_path self.model_shape = model_shape self.tf_device = tf_device self.num_threads = num_threads self.start_or_restart() - + def stop(self): self.detect_process.terminate() logging.info("Waiting for detection process to exit gracefully...") @@ -181,23 +222,42 @@ class EdgeTPUProcess(): self.detection_start.value = 0.0 if (not self.detect_process is None) and self.detect_process.is_alive(): self.stop() - self.detect_process = mp.Process(target=run_detector, name=f"detector:{self.name}", args=(self.name, self.detection_queue, self.out_events, self.avg_inference_speed, self.detection_start, self.model_shape, self.tf_device, self.num_threads)) + self.detect_process = mp.Process( + target=run_detector, + name=f"detector:{self.name}", + args=( + self.name, + self.detection_queue, + self.out_events, + self.avg_inference_speed, + self.detection_start, + self.model_path, + self.model_shape, + self.tf_device, + self.num_threads, + ), + ) self.detect_process.daemon = True self.detect_process.start() -class RemoteObjectDetector(): + +class RemoteObjectDetector: def __init__(self, name, labels, detection_queue, event, model_shape): - self.labels = load_labels(labels) + self.labels = labels self.name = name self.fps = EventsPerSecond() self.detection_queue = detection_queue self.event = event self.shm = mp.shared_memory.SharedMemory(name=self.name, create=False) - self.np_shm = np.ndarray((1,model_shape[0],model_shape[1],3), dtype=np.uint8, buffer=self.shm.buf) - self.out_shm = mp.shared_memory.SharedMemory(name=f"out-{self.name}", create=False) - self.out_np_shm = np.ndarray((20,6), dtype=np.float32, buffer=self.out_shm.buf) - - def detect(self, tensor_input, threshold=.4): + self.np_shm = np.ndarray( + (1, model_shape[0], model_shape[1], 3), dtype=np.uint8, buffer=self.shm.buf + ) + self.out_shm = mp.shared_memory.SharedMemory( + name=f"out-{self.name}", create=False + ) + self.out_np_shm = np.ndarray((20, 6), dtype=np.float32, buffer=self.out_shm.buf) + + def detect(self, tensor_input, threshold=0.4): detections = [] # copy input to shared memory @@ -213,14 +273,12 @@ class RemoteObjectDetector(): for d in self.out_np_shm: if d[1] < threshold: break - detections.append(( - self.labels[int(d[0])], - float(d[1]), - (d[2], d[3], d[4], d[5]) - )) + detections.append( + (self.labels[int(d[0])], float(d[1]), (d[2], d[3], d[4], d[5])) + ) self.fps.update() return detections - + def cleanup(self): self.shm.unlink() self.out_shm.unlink() diff --git a/frigate/events.py b/frigate/events.py index 2430d9db3..86fd2082b 100644 --- a/frigate/events.py +++ b/frigate/events.py @@ -1,29 +1,26 @@ import datetime -import json import logging import os import queue -import subprocess as sp import threading import time -from collections import defaultdict from pathlib import Path -import psutil -import shutil - -from frigate.config import FrigateConfig -from frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR -from frigate.models import Event - from peewee import fn +from frigate.config import EventsConfig, FrigateConfig, RecordConfig +from frigate.const import CLIPS_DIR +from frigate.models import Event + logger = logging.getLogger(__name__) + class EventProcessor(threading.Thread): - def __init__(self, config, camera_processes, event_queue, event_processed_queue, stop_event): + def __init__( + self, config, camera_processes, event_queue, event_processed_queue, stop_event + ): threading.Thread.__init__(self) - self.name = 'event_processor' + self.name = "event_processor" self.config = config self.camera_processes = camera_processes self.cached_clips = {} @@ -32,292 +29,153 @@ class EventProcessor(threading.Thread): self.events_in_process = {} self.stop_event = stop_event - def should_create_clip(self, camera, event_data): - if event_data['false_positive']: - return False - - # if there are required zones and there is no overlap - required_zones = self.config.cameras[camera].clips.required_zones - if len(required_zones) > 0 and not set(event_data['entered_zones']) & set(required_zones): - logger.debug(f"Not creating clip for {event_data['id']} because it did not enter required zones") - return False - - return True - - def refresh_cache(self): - cached_files = os.listdir(CACHE_DIR) - - files_in_use = [] - for process in psutil.process_iter(): - try: - if process.name() != 'ffmpeg': - continue - - flist = process.open_files() - if flist: - for nt in flist: - if nt.path.startswith(CACHE_DIR): - files_in_use.append(nt.path.split('/')[-1]) - except: - continue - - for f in cached_files: - if f in files_in_use or f in self.cached_clips: - continue - - camera = '-'.join(f.split('-')[:-1]) - start_time = datetime.datetime.strptime(f.split('-')[-1].split('.')[0], '%Y%m%d%H%M%S') - - ffprobe_cmd = " ".join([ - 'ffprobe', - '-v', - 'error', - '-show_entries', - 'format=duration', - '-of', - 'default=noprint_wrappers=1:nokey=1', - f"{os.path.join(CACHE_DIR,f)}" - ]) - p = sp.Popen(ffprobe_cmd, stdout=sp.PIPE, shell=True) - (output, err) = p.communicate() - p_status = p.wait() - if p_status == 0: - duration = float(output.decode('utf-8').strip()) - else: - logger.info(f"bad file: {f}") - os.remove(os.path.join(CACHE_DIR,f)) - continue - - self.cached_clips[f] = { - 'path': f, - 'camera': camera, - 'start_time': start_time.timestamp(), - 'duration': duration - } - - if len(self.events_in_process) > 0: - earliest_event = min(self.events_in_process.values(), key=lambda x:x['start_time'])['start_time'] - else: - earliest_event = datetime.datetime.now().timestamp() - - # if the earliest event exceeds the max seconds, cap it - max_seconds = self.config.clips.max_seconds - if datetime.datetime.now().timestamp()-earliest_event > max_seconds: - earliest_event = datetime.datetime.now().timestamp()-max_seconds - - for f, data in list(self.cached_clips.items()): - if earliest_event-90 > data['start_time']+data['duration']: - del self.cached_clips[f] - logger.debug(f"Cleaning up cached file {f}") - os.remove(os.path.join(CACHE_DIR,f)) - - # if we are still using more than 90% of the cache, proactively cleanup - cache_usage = shutil.disk_usage("/tmp/cache") - if cache_usage.used/cache_usage.total > .9 and cache_usage.free < 200000000 and len(self.cached_clips) > 0: - logger.warning("More than 90% of the cache is used.") - logger.warning("Consider increasing space available at /tmp/cache or reducing max_seconds in your clips config.") - logger.warning("Proactively cleaning up the cache...") - while cache_usage.used/cache_usage.total > .9: - oldest_clip = min(self.cached_clips.values(), key=lambda x:x['start_time']) - del self.cached_clips[oldest_clip['path']] - os.remove(os.path.join(CACHE_DIR,oldest_clip['path'])) - cache_usage = shutil.disk_usage("/tmp/cache") - - def create_clip(self, camera, event_data, pre_capture, post_capture): - # get all clips from the camera with the event sorted - sorted_clips = sorted([c for c in self.cached_clips.values() if c['camera'] == camera], key = lambda i: i['start_time']) - - # if there are no clips in the cache or we are still waiting on a needed file check every 5 seconds - wait_count = 0 - while len(sorted_clips) == 0 or sorted_clips[-1]['start_time'] + sorted_clips[-1]['duration'] < event_data['end_time']+post_capture: - if wait_count > 4: - logger.warning(f"Unable to create clip for {camera} and event {event_data['id']}. There were no cache files for this event.") - return False - logger.debug(f"No cache clips for {camera}. Waiting...") - time.sleep(5) - self.refresh_cache() - # get all clips from the camera with the event sorted - sorted_clips = sorted([c for c in self.cached_clips.values() if c['camera'] == camera], key = lambda i: i['start_time']) - wait_count += 1 - - playlist_start = event_data['start_time']-pre_capture - playlist_end = event_data['end_time']+post_capture - playlist_lines = [] - for clip in sorted_clips: - # clip ends before playlist start time, skip - if clip['start_time']+clip['duration'] < playlist_start: - continue - # clip starts after playlist ends, finish - if clip['start_time'] > playlist_end: - break - playlist_lines.append(f"file '{os.path.join(CACHE_DIR,clip['path'])}'") - # if this is the starting clip, add an inpoint - if clip['start_time'] < playlist_start: - playlist_lines.append(f"inpoint {int(playlist_start-clip['start_time'])}") - # if this is the ending clip, add an outpoint - if clip['start_time']+clip['duration'] > playlist_end: - playlist_lines.append(f"outpoint {int(playlist_end-clip['start_time'])}") - - clip_name = f"{camera}-{event_data['id']}" - ffmpeg_cmd = [ - 'ffmpeg', - '-y', - '-protocol_whitelist', - 'pipe,file', - '-f', - 'concat', - '-safe', - '0', - '-i', - '-', - '-c', - 'copy', - '-movflags', - '+faststart', - f"{os.path.join(CLIPS_DIR, clip_name)}.mp4" - ] - - p = sp.run(ffmpeg_cmd, input="\n".join(playlist_lines), encoding='ascii', capture_output=True) - if p.returncode != 0: - logger.error(p.stderr) - return False - return True - def run(self): - while True: - if self.stop_event.is_set(): - logger.info(f"Exiting event processor...") - break - + while not self.stop_event.is_set(): try: event_type, camera, event_data = self.event_queue.get(timeout=10) except queue.Empty: - if not self.stop_event.is_set(): - self.refresh_cache() continue logger.debug(f"Event received: {event_type} {camera} {event_data['id']}") - self.refresh_cache() - if event_type == 'start': - self.events_in_process[event_data['id']] = event_data + if event_type == "start": + self.events_in_process[event_data["id"]] = event_data - if event_type == 'end': - clips_config = self.config.cameras[camera].clips + if event_type == "end": + event_config: EventsConfig = self.config.cameras[camera].record.events - clip_created = False - if self.should_create_clip(camera, event_data): - if clips_config.enabled and (clips_config.objects is None or event_data['label'] in clips_config.objects): - clip_created = self.create_clip(camera, event_data, clips_config.pre_capture, clips_config.post_capture) - - if clip_created or event_data['has_snapshot']: + if event_data["has_clip"] or event_data["has_snapshot"]: Event.create( - id=event_data['id'], - label=event_data['label'], + id=event_data["id"], + label=event_data["label"], camera=camera, - start_time=event_data['start_time'], - end_time=event_data['end_time'], - top_score=event_data['top_score'], - false_positive=event_data['false_positive'], - zones=list(event_data['entered_zones']), - thumbnail=event_data['thumbnail'], - has_clip=clip_created, - has_snapshot=event_data['has_snapshot'], + start_time=event_data["start_time"] - event_config.pre_capture, + end_time=event_data["end_time"] + event_config.post_capture, + top_score=event_data["top_score"], + false_positive=event_data["false_positive"], + zones=list(event_data["entered_zones"]), + thumbnail=event_data["thumbnail"], + region=event_data["region"], + box=event_data["box"], + area=event_data["area"], + has_clip=event_data["has_clip"], + has_snapshot=event_data["has_snapshot"], ) - del self.events_in_process[event_data['id']] - self.event_processed_queue.put((event_data['id'], camera)) + + del self.events_in_process[event_data["id"]] + self.event_processed_queue.put((event_data["id"], camera)) + + logger.info(f"Exiting event processor...") + class EventCleanup(threading.Thread): def __init__(self, config: FrigateConfig, stop_event): threading.Thread.__init__(self) - self.name = 'event_cleanup' + self.name = "event_cleanup" self.config = config self.stop_event = stop_event self.camera_keys = list(self.config.cameras.keys()) - def expire(self, media): + def expire(self, media_type): ## Expire events from unlisted cameras based on the global config - if media == 'clips': - retain_config = self.config.clips.retain - file_extension = 'mp4' - update_params = {'has_clip': False} + if media_type == "clips": + retain_config = self.config.record.events.retain + file_extension = "mp4" + update_params = {"has_clip": False} else: retain_config = self.config.snapshots.retain - file_extension = 'jpg' - update_params = {'has_snapshot': False} - - distinct_labels = (Event.select(Event.label) - .where(Event.camera.not_in(self.camera_keys)) - .distinct()) - + file_extension = "jpg" + update_params = {"has_snapshot": False} + + distinct_labels = ( + Event.select(Event.label) + .where(Event.camera.not_in(self.camera_keys)) + .distinct() + ) + # loop over object types in db for l in distinct_labels: # get expiration time for this label expire_days = retain_config.objects.get(l.label, retain_config.default) - expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp() + expire_after = ( + datetime.datetime.now() - datetime.timedelta(days=expire_days) + ).timestamp() # grab all events after specific time - expired_events = ( - Event.select() - .where(Event.camera.not_in(self.camera_keys), - Event.start_time < expire_after, - Event.label == l.label) + expired_events = Event.select().where( + Event.camera.not_in(self.camera_keys), + Event.start_time < expire_after, + Event.label == l.label, ) # delete the media from disk for event in expired_events: media_name = f"{event.camera}-{event.id}" - media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}") - media.unlink(missing_ok=True) + media_path = Path( + f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}" + ) + media_path.unlink(missing_ok=True) + if file_extension == "jpg": + media_path = Path( + f"{os.path.join(CLIPS_DIR, media_name)}-clean.png" + ) + media_path.unlink(missing_ok=True) + # update the clips attribute for the db entry - update_query = ( - Event.update(update_params) - .where(Event.camera.not_in(self.camera_keys), - Event.start_time < expire_after, - Event.label == l.label) + update_query = Event.update(update_params).where( + Event.camera.not_in(self.camera_keys), + Event.start_time < expire_after, + Event.label == l.label, ) update_query.execute() ## Expire events from cameras based on the camera config for name, camera in self.config.cameras.items(): - if media == 'clips': - retain_config = camera.clips.retain + if media_type == "clips": + retain_config = camera.record.events.retain else: retain_config = camera.snapshots.retain # get distinct objects in database for this camera - distinct_labels = (Event.select(Event.label) - .where(Event.camera == name) - .distinct()) + distinct_labels = ( + Event.select(Event.label).where(Event.camera == name).distinct() + ) # loop over object types in db for l in distinct_labels: # get expiration time for this label expire_days = retain_config.objects.get(l.label, retain_config.default) - expire_after = (datetime.datetime.now() - datetime.timedelta(days=expire_days)).timestamp() + expire_after = ( + datetime.datetime.now() - datetime.timedelta(days=expire_days) + ).timestamp() # grab all events after specific time - expired_events = ( - Event.select() - .where(Event.camera == name, - Event.start_time < expire_after, - Event.label == l.label) + expired_events = Event.select().where( + Event.camera == name, + Event.start_time < expire_after, + Event.label == l.label, ) # delete the grabbed clips from disk for event in expired_events: media_name = f"{event.camera}-{event.id}" - media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}") - media.unlink(missing_ok=True) + media_path = Path( + f"{os.path.join(CLIPS_DIR, media_name)}.{file_extension}" + ) + media_path.unlink(missing_ok=True) + if file_extension == "jpg": + media_path = Path( + f"{os.path.join(CLIPS_DIR, media_name)}-clean.png" + ) + media_path.unlink(missing_ok=True) # update the clips attribute for the db entry - update_query = ( - Event.update(update_params) - .where( Event.camera == name, - Event.start_time < expire_after, - Event.label == l.label) + update_query = Event.update(update_params).where( + Event.camera == name, + Event.start_time < expire_after, + Event.label == l.label, ) update_query.execute() def purge_duplicates(self): duplicate_query = """with grouped_events as ( select id, - label, - camera, + label, + camera, has_snapshot, has_clip, row_number() over ( @@ -327,46 +185,37 @@ class EventCleanup(threading.Thread): from event ) - select distinct id, camera, has_snapshot, has_clip from grouped_events + select distinct id, camera, has_snapshot, has_clip from grouped_events where copy_number > 1;""" duplicate_events = Event.raw(duplicate_query) for event in duplicate_events: logger.debug(f"Removing duplicate: {event.id}") media_name = f"{event.camera}-{event.id}" - if event.has_snapshot: - media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg") - media.unlink(missing_ok=True) - if event.has_clip: - media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4") - media.unlink(missing_ok=True) + media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg") + media_path.unlink(missing_ok=True) + media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}-clean.png") + media_path.unlink(missing_ok=True) + media_path = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4") + media_path.unlink(missing_ok=True) + + ( + Event.delete() + .where(Event.id << [event.id for event in duplicate_events]) + .execute() + ) - (Event.delete() - .where( Event.id << [event.id for event in duplicate_events] ) - .execute()) - def run(self): - counter = 0 - while(True): - if self.stop_event.is_set(): - logger.info(f"Exiting event cleanup...") - break - - # only expire events every 5 minutes, but check for stop events every 10 seconds - time.sleep(10) - counter = counter + 1 - if counter < 30: - continue - counter = 0 - - self.expire('clips') - self.expire('snapshots') + # only expire events every 5 minutes + while not self.stop_event.wait(300): + self.expire("clips") + self.expire("snapshots") self.purge_duplicates() # drop events from db where has_clip and has_snapshot are false - delete_query = ( - Event.delete() - .where( Event.has_clip == False, - Event.has_snapshot == False) + delete_query = Event.delete().where( + Event.has_clip == False, Event.has_snapshot == False ) delete_query.execute() + + logger.info(f"Exiting event cleanup...") diff --git a/frigate/http.py b/frigate/http.py index 4d818d37c..1ef35dd92 100644 --- a/frigate/http.py +++ b/frigate/http.py @@ -1,92 +1,56 @@ import base64 -import datetime +from collections import OrderedDict +from datetime import datetime, timedelta import json +import glob import logging import os +import re +import subprocess as sp import time from functools import reduce +from pathlib import Path import cv2 -import gevent +from flask.helpers import send_file + import numpy as np -from flask import (Blueprint, Flask, Response, current_app, jsonify, - make_response, request) -from flask_sockets import Sockets -from peewee import SqliteDatabase, operator, fn, DoesNotExist +from flask import ( + Blueprint, + Flask, + Response, + current_app, + jsonify, + make_response, + request, +) + +from peewee import SqliteDatabase, operator, fn, DoesNotExist, Value from playhouse.shortcuts import model_to_dict -from frigate.const import CLIPS_DIR -from frigate.models import Event +from frigate.const import CLIPS_DIR, RECORD_DIR +from frigate.models import Event, Recordings from frigate.stats import stats_snapshot from frigate.util import calculate_region from frigate.version import VERSION logger = logging.getLogger(__name__) -bp = Blueprint('frigate', __name__) -ws = Blueprint('ws', __name__) +bp = Blueprint("frigate", __name__) -class MqttBackend(): - """Interface for registering and updating WebSocket clients.""" - def __init__(self, mqtt_client, topic_prefix): - self.clients = list() - self.mqtt_client = mqtt_client - self.topic_prefix = topic_prefix - - def register(self, client): - """Register a WebSocket connection for Mqtt updates.""" - self.clients.append(client) - - def publish(self, message): - try: - json_message = json.loads(message) - json_message = { - 'topic': f"{self.topic_prefix}/{json_message['topic']}", - 'payload': json_message['payload'], - 'retain': json_message.get('retain', False) - } - except: - logger.warning("Unable to parse websocket message as valid json.") - return - - logger.debug(f"Publishing mqtt message from websockets at {json_message['topic']}.") - self.mqtt_client.publish(json_message['topic'], json_message['payload'], retain=json_message['retain']) - - def run(self): - def send(client, userdata, message): - """Sends mqtt messages to clients.""" - try: - logger.debug(f"Received mqtt message on {message.topic}.") - ws_message = json.dumps({ - 'topic': message.topic.replace(f"{self.topic_prefix}/",""), - 'payload': message.payload.decode() - }) - except: - # if the payload can't be decoded don't relay to clients - logger.debug(f"MQTT payload for {message.topic} wasn't text. Skipping...") - return - - for client in self.clients: - try: - client.send(ws_message) - except: - logger.debug("Removing websocket client due to a closed connection.") - self.clients.remove(client) - - self.mqtt_client.message_callback_add(f"{self.topic_prefix}/#", send) - - def start(self): - """Maintains mqtt subscription in the background.""" - gevent.spawn(self.run) - -def create_app(frigate_config, database: SqliteDatabase, stats_tracking, detected_frames_processor, mqtt_client): +def create_app( + frigate_config, + database: SqliteDatabase, + stats_tracking, + detected_frames_processor, +): app = Flask(__name__) - sockets = Sockets(app) @app.before_request def _db_connect(): - database.connect() + if database.is_closed(): + database.connect() @app.teardown_request def _db_close(exc): @@ -98,21 +62,19 @@ def create_app(frigate_config, database: SqliteDatabase, stats_tracking, detecte app.detected_frames_processor = detected_frames_processor app.register_blueprint(bp) - sockets.register_blueprint(ws) - - app.mqtt_backend = MqttBackend(mqtt_client, frigate_config.mqtt.topic_prefix) - app.mqtt_backend.start() return app -@bp.route('/') + +@bp.route("/") def is_healthy(): return "Frigate is running. Alive and healthy!" -@bp.route('/events/summary') + +@bp.route("/events/summary") def events_summary(): - has_clip = request.args.get('has_clip', type=int) - has_snapshot = request.args.get('has_snapshot', type=int) + has_clip = request.args.get("has_clip", type=int) + has_snapshot = request.args.get("has_snapshot", type=int) clauses = [] @@ -123,38 +85,66 @@ def events_summary(): clauses.append((Event.has_snapshot == has_snapshot)) if len(clauses) == 0: - clauses.append((1 == 1)) + clauses.append((True)) groups = ( - Event - .select( - Event.camera, - Event.label, - fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')).alias('day'), - Event.zones, - fn.COUNT(Event.id).alias('count') - ) - .where(reduce(operator.and_, clauses)) - .group_by( - Event.camera, - Event.label, - fn.strftime('%Y-%m-%d', fn.datetime(Event.start_time, 'unixepoch', 'localtime')), - Event.zones - ) + Event.select( + Event.camera, + Event.label, + fn.strftime( + "%Y-%m-%d", fn.datetime(Event.start_time, "unixepoch", "localtime") + ).alias("day"), + Event.zones, + fn.COUNT(Event.id).alias("count"), ) + .where(reduce(operator.and_, clauses)) + .group_by( + Event.camera, + Event.label, + fn.strftime( + "%Y-%m-%d", fn.datetime(Event.start_time, "unixepoch", "localtime") + ), + Event.zones, + ) + ) return jsonify([e for e in groups.dicts()]) -@bp.route('/events/') + +@bp.route("/events/", methods=("GET",)) def event(id): try: return model_to_dict(Event.get(Event.id == id)) except DoesNotExist: return "Event not found", 404 -@bp.route('/events//thumbnail.jpg') + +@bp.route("/events/", methods=("DELETE",)) +def delete_event(id): + try: + event = Event.get(Event.id == id) + except DoesNotExist: + return make_response( + jsonify({"success": False, "message": "Event" + id + " not found"}), 404 + ) + + media_name = f"{event.camera}-{event.id}" + if event.has_snapshot: + media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.jpg") + media.unlink(missing_ok=True) + if event.has_clip: + media = Path(f"{os.path.join(CLIPS_DIR, media_name)}.mp4") + media.unlink(missing_ok=True) + + event.delete_instance() + return make_response( + jsonify({"success": True, "message": "Event" + id + " deleted"}), 200 + ) + + +@bp.route("/events//thumbnail.jpg") def event_thumbnail(id): - format = request.args.get('format', 'ios') + format = request.args.get("format", "ios") thumbnail_bytes = None try: event = Event.get(Event.id == id) @@ -162,7 +152,8 @@ def event_thumbnail(id): except DoesNotExist: # see if the object is currently being tracked try: - for camera_state in current_app.detected_frames_processor.camera_states.values(): + camera_states = current_app.detected_frames_processor.camera_states.values() + for camera_state in camera_states: if id in camera_state.tracked_objects: tracked_obj = camera_state.tracked_objects.get(id) if not tracked_obj is None: @@ -174,60 +165,114 @@ def event_thumbnail(id): return "Event not found", 404 # android notifications prefer a 2:1 ratio - if format == 'android': + if format == "android": jpg_as_np = np.frombuffer(thumbnail_bytes, dtype=np.uint8) img = cv2.imdecode(jpg_as_np, flags=1) - thumbnail = cv2.copyMakeBorder(img, 0, 0, int(img.shape[1]*0.5), int(img.shape[1]*0.5), cv2.BORDER_CONSTANT, (0,0,0)) - ret, jpg = cv2.imencode('.jpg', thumbnail, [int(cv2.IMWRITE_JPEG_QUALITY), 70]) + thumbnail = cv2.copyMakeBorder( + img, + 0, + 0, + int(img.shape[1] * 0.5), + int(img.shape[1] * 0.5), + cv2.BORDER_CONSTANT, + (0, 0, 0), + ) + ret, jpg = cv2.imencode(".jpg", thumbnail, [int(cv2.IMWRITE_JPEG_QUALITY), 70]) thumbnail_bytes = jpg.tobytes() response = make_response(thumbnail_bytes) - response.headers['Content-Type'] = 'image/jpg' + response.headers["Content-Type"] = "image/jpg" return response -@bp.route('/events//snapshot.jpg') + +@bp.route("/events//snapshot.jpg") def event_snapshot(id): + download = request.args.get("download", type=bool) jpg_bytes = None try: event = Event.get(Event.id == id) if not event.has_snapshot: return "Snapshot not available", 404 # read snapshot from disk - with open(os.path.join(CLIPS_DIR, f"{event.camera}-{id}.jpg"), 'rb') as image_file: + with open( + os.path.join(CLIPS_DIR, f"{event.camera}-{id}.jpg"), "rb" + ) as image_file: jpg_bytes = image_file.read() except DoesNotExist: # see if the object is currently being tracked try: - for camera_state in current_app.detected_frames_processor.camera_states.values(): + camera_states = current_app.detected_frames_processor.camera_states.values() + for camera_state in camera_states: if id in camera_state.tracked_objects: tracked_obj = camera_state.tracked_objects.get(id) if not tracked_obj is None: jpg_bytes = tracked_obj.get_jpg_bytes( - timestamp=request.args.get('timestamp', type=int), - bounding_box=request.args.get('bbox', type=int), - crop=request.args.get('crop', type=int), - height=request.args.get('h', type=int) + timestamp=request.args.get("timestamp", type=int), + bounding_box=request.args.get("bbox", type=int), + crop=request.args.get("crop", type=int), + height=request.args.get("h", type=int), + quality=request.args.get("quality", default=70, type=int), ) except: return "Event not found", 404 except: return "Event not found", 404 + if jpg_bytes is None: + return "Event not found", 404 + response = make_response(jpg_bytes) - response.headers['Content-Type'] = 'image/jpg' + response.headers["Content-Type"] = "image/jpg" + if download: + response.headers[ + "Content-Disposition" + ] = f"attachment; filename=snapshot-{id}.jpg" return response -@bp.route('/events') + +@bp.route("/events//clip.mp4") +def event_clip(id): + download = request.args.get("download", type=bool) + + try: + event: Event = Event.get(Event.id == id) + except DoesNotExist: + return "Event not found.", 404 + + if not event.has_clip: + return "Clip not available", 404 + + file_name = f"{event.camera}-{id}.mp4" + clip_path = os.path.join(CLIPS_DIR, file_name) + + if not os.path.isfile(clip_path): + return recording_clip(event.camera, event.start_time, event.end_time) + + response = make_response() + response.headers["Content-Description"] = "File Transfer" + response.headers["Cache-Control"] = "no-cache" + response.headers["Content-Type"] = "video/mp4" + if download: + response.headers["Content-Disposition"] = "attachment; filename=%s" % file_name + response.headers["Content-Length"] = os.path.getsize(clip_path) + response.headers[ + "X-Accel-Redirect" + ] = f"/clips/{file_name}" # nginx: http://wiki.nginx.org/NginxXSendfile + + return response + + +@bp.route("/events") def events(): - limit = request.args.get('limit', 100) - camera = request.args.get('camera') - label = request.args.get('label') - zone = request.args.get('zone') - after = request.args.get('after', type=float) - before = request.args.get('before', type=float) - has_clip = request.args.get('has_clip', type=int) - has_snapshot = request.args.get('has_snapshot', type=int) - include_thumbnails = request.args.get('include_thumbnails', default=1, type=int) + limit = request.args.get("limit", 100) + camera = request.args.get("camera") + label = request.args.get("label") + zone = request.args.get("zone") + after = request.args.get("after", type=float) + before = request.args.get("before", type=float) + has_clip = request.args.get("has_clip", type=int) + has_snapshot = request.args.get("has_snapshot", type=int) + include_thumbnails = request.args.get("include_thumbnails", default=1, type=int) clauses = [] excluded_fields = [] @@ -239,7 +284,7 @@ def events(): clauses.append((Event.label == label)) if zone: - clauses.append((Event.zones.cast('text') % f"*\"{zone}\"*")) + clauses.append((Event.zones.cast("text") % f'*"{zone}"*')) if after: clauses.append((Event.start_time >= after)) @@ -257,125 +302,427 @@ def events(): excluded_fields.append(Event.thumbnail) if len(clauses) == 0: - clauses.append((1 == 1)) + clauses.append((True)) - events = (Event.select() - .where(reduce(operator.and_, clauses)) - .order_by(Event.start_time.desc()) - .limit(limit)) + events = ( + Event.select() + .where(reduce(operator.and_, clauses)) + .order_by(Event.start_time.desc()) + .limit(limit) + ) return jsonify([model_to_dict(e, exclude=excluded_fields) for e in events]) -@bp.route('/config') -def config(): - return jsonify(current_app.frigate_config.to_dict()) -@bp.route('/version') +@bp.route("/config") +def config(): + config = current_app.frigate_config.dict() + + # add in the ffmpeg_cmds + for camera_name, camera in current_app.frigate_config.cameras.items(): + camera_dict = config["cameras"][camera_name] + camera_dict["ffmpeg_cmds"] = camera.ffmpeg_cmds + for cmd in camera_dict["ffmpeg_cmds"]: + cmd["cmd"] = " ".join(cmd["cmd"]) + + return jsonify(config) + + +@bp.route("/config/schema") +def config_schema(): + return current_app.response_class( + current_app.frigate_config.schema_json(), mimetype="application/json" + ) + + +@bp.route("/version") def version(): return VERSION -@bp.route('/stats') + +@bp.route("/stats") def stats(): stats = stats_snapshot(current_app.stats_tracking) return jsonify(stats) -@bp.route('//