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| Author | SHA1 | Date | |
|---|---|---|---|
|
012ab2b6a9 |
5
.github/copilot-instructions.md
vendored
5
.github/copilot-instructions.md
vendored
@ -1,3 +1,2 @@
|
||||
- For Frigate NVR, never write strings in the frontend directly. Since the project uses `react-i18next`, use `t()` and write the English string in the relevant translations file in `web/public/locales/en`.
|
||||
- Always conform new and refactored code to the existing coding style in the project.
|
||||
- Always have a way to test your work and confirm your changes. When running backend tests, use `python3 -u -m unittest`.
|
||||
Never write strings in the frontend directly, always write to and reference the relevant translations file.
|
||||
Always conform new and refactored code to the existing coding style in the project.
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||||
|
||||
@ -47,7 +47,7 @@ onnxruntime == 1.22.*
|
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# Embeddings
|
||||
transformers == 4.45.*
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||||
# Generative AI
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||||
google-genai == 1.58.*
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||||
google-generativeai == 0.8.*
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||||
ollama == 0.6.*
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openai == 1.65.*
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||||
# push notifications
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||||
|
||||
@ -69,15 +69,15 @@ function setup_homekit_config() {
|
||||
local cleaned_json="/tmp/cache/homekit_cleaned.json"
|
||||
jq '
|
||||
# Keep only the homekit section if it exists, otherwise empty object
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||||
if has("homekit") then {homekit: .homekit} else {} end
|
||||
if has("homekit") then {homekit: .homekit} else {homekit: {}} end
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||||
' "${temp_json}" > "${cleaned_json}" 2>/dev/null || {
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||||
echo '{}' > "${cleaned_json}"
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||||
echo '{"homekit": {}}' > "${cleaned_json}"
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||||
}
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||||
|
||||
# Convert back to YAML and write to the config file
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||||
yq eval -P "${cleaned_json}" > "${config_path}" 2>/dev/null || {
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||||
echo "[WARNING] Failed to convert cleaned config to YAML, creating minimal config"
|
||||
echo '{}' > "${config_path}"
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||||
echo 'homekit: {}' > "${config_path}"
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||||
}
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||||
|
||||
# Clean up temp files
|
||||
|
||||
@ -79,12 +79,6 @@ cameras:
|
||||
|
||||
If the ONVIF connection is successful, PTZ controls will be available in the camera's WebUI.
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||||
|
||||
:::note
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||||
|
||||
Some cameras use a separate ONVIF/service account that is distinct from the device administrator credentials. If ONVIF authentication fails with the admin account, try creating or using an ONVIF/service user in the camera's firmware. Refer to your camera manufacturer's documentation for more.
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||||
|
||||
:::
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||||
|
||||
:::tip
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||||
|
||||
If your ONVIF camera does not require authentication credentials, you may still need to specify an empty string for `user` and `password`, eg: `user: ""` and `password: ""`.
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||||
@ -101,7 +95,7 @@ The FeatureList on the [ONVIF Conformant Products Database](https://www.onvif.or
|
||||
|
||||
| Brand or specific camera | PTZ Controls | Autotracking | Notes |
|
||||
| ---------------------------- | :----------: | :----------: | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| Amcrest | ✅ | ✅ | ⛔️ Generally, Amcrest should work, but some older models (like the common IP2M-841) don't support autotracking |
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||||
| Amcrest | ✅ | ✅ | ⛔️ Generally, Amcrest should work, but some older models (like the common IP2M-841) don't support autotracking |
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||||
| Amcrest ASH21 | ✅ | ❌ | ONVIF service port: 80 |
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||||
| Amcrest IP4M-S2112EW-AI | ✅ | ❌ | FOV relative movement not supported. |
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||||
| Amcrest IP5M-1190EW | ✅ | ❌ | ONVIF Port: 80. FOV relative movement not supported. |
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||||
|
||||
@ -66,6 +66,8 @@ Some models are labeled as **hybrid** (capable of both thinking and instruct tas
|
||||
**Recommendation:**
|
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Always select the `-instruct` or documented instruct/tagged variant of any model you use in your Frigate configuration. If in doubt, refer to your model provider’s documentation or model library for guidance on the correct model variant to use.
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||||
|
||||
|
||||
|
||||
### Supported Models
|
||||
|
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You must use a vision capable model with Frigate. Current model variants can be found [in their model library](https://ollama.com/search?c=vision). Note that Frigate will not automatically download the model you specify in your config, you must download the model to your local instance of Ollama first i.e. by running `ollama pull qwen3-vl:2b-instruct` on your Ollama server/Docker container. Note that the model specified in Frigate's config must match the downloaded model tag.
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||||
@ -91,7 +93,7 @@ genai:
|
||||
|
||||
## Google Gemini
|
||||
|
||||
Google Gemini has a [free tier](https://ai.google.dev/pricing) for the API, however the limits may not be sufficient for standard Frigate usage. Choose a plan appropriate for your installation.
|
||||
Google Gemini has a free tier allowing [15 queries per minute](https://ai.google.dev/pricing) to the API, which is more than sufficient for standard Frigate usage.
|
||||
|
||||
### Supported Models
|
||||
|
||||
@ -112,7 +114,7 @@ To start using Gemini, you must first get an API key from [Google AI Studio](htt
|
||||
genai:
|
||||
provider: gemini
|
||||
api_key: "{FRIGATE_GEMINI_API_KEY}"
|
||||
model: gemini-2.5-flash
|
||||
model: gemini-2.0-flash
|
||||
```
|
||||
|
||||
:::note
|
||||
|
||||
@ -125,10 +125,10 @@ review:
|
||||
|
||||
## Review Reports
|
||||
|
||||
Along with individual review item summaries, Generative AI can also produce a single report of review items from all cameras marked "suspicious" over a specified time period (for example, a daily summary of suspicious activity while you're on vacation).
|
||||
Along with individual review item summaries, Generative AI provides the ability to request a report of a given time period. For example, you can get a daily report while on a vacation of any suspicious activity or other concerns that may require review.
|
||||
|
||||
### Requesting Reports Programmatically
|
||||
|
||||
Review reports can be requested via the [API](/integrations/api/generate-review-summary-review-summarize-start-start-ts-end-end-ts-post) by sending a POST request to `/api/review/summarize/start/{start_ts}/end/{end_ts}` with Unix timestamps.
|
||||
Review reports can be requested via the [API](/integrations/api#review-summarization) by sending a POST request to `/api/review/summarize/start/{start_ts}/end/{end_ts}` with Unix timestamps.
|
||||
|
||||
For Home Assistant users, there is a built-in service (`frigate.review_summarize`) that makes it easy to request review reports as part of automations or scripts. This allows you to automatically generate daily summaries, vacation reports, or custom time period reports based on your specific needs.
|
||||
|
||||
@ -68,8 +68,8 @@ Fine-tune the LPR feature using these optional parameters at the global level of
|
||||
- Default: `1000` pixels. Note: this is intentionally set very low as it is an _area_ measurement (length x width). For reference, 1000 pixels represents a ~32x32 pixel square in your camera image.
|
||||
- Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant plates.
|
||||
- **`device`**: Device to use to run license plate detection _and_ recognition models.
|
||||
- Default: `None`
|
||||
- This is auto-selected by Frigate and can be `CPU`, `GPU`, or the GPU's device number. For users without a model that detects license plates natively, using a GPU may increase performance of the YOLOv9 license plate detector model. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation. However, for users who run a model that detects `license_plate` natively, there is little to no performance gain reported with running LPR on GPU compared to the CPU.
|
||||
- Default: `CPU`
|
||||
- This can be `CPU`, `GPU`, or the GPU's device number. For users without a model that detects license plates natively, using a GPU may increase performance of the YOLOv9 license plate detector model. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation. However, for users who run a model that detects `license_plate` natively, there is little to no performance gain reported with running LPR on GPU compared to the CPU.
|
||||
- **`model_size`**: The size of the model used to identify regions of text on plates.
|
||||
- Default: `small`
|
||||
- This can be `small` or `large`.
|
||||
@ -432,6 +432,6 @@ If you are using a model that natively detects `license_plate`, add an _object m
|
||||
|
||||
If you are not using a model that natively detects `license_plate` or you are using dedicated LPR camera mode, only a _motion mask_ over your text is required.
|
||||
|
||||
### I see "Error running ... model" in my logs, or my inference time is very high. How can I fix this?
|
||||
### I see "Error running ... model" in my logs. How can I fix this?
|
||||
|
||||
This usually happens when your GPU is unable to compile or use one of the LPR models. Set your `device` to `CPU` and try again. GPU acceleration only provides a slight performance increase, and the models are lightweight enough to run without issue on most CPUs.
|
||||
|
||||
@ -11,12 +11,6 @@ Cameras configured to output H.264 video and AAC audio will offer the most compa
|
||||
|
||||
- **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.
|
||||
|
||||
:::tip
|
||||
|
||||
For the best experience in Frigate's UI, configure your camera so that the detection and recording streams use the same aspect ratio. For example, if your main stream is 3840x2160 (16:9), set your substream to 640x360 (also 16:9) instead of 640x480 (4:3). While not strictly required, matching aspect ratios helps ensure seamless live stream display and preview/recordings playback.
|
||||
|
||||
:::
|
||||
|
||||
### 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.
|
||||
|
||||
@ -42,7 +42,7 @@ If the EQ13 is out of stock, the link below may take you to a suggested alternat
|
||||
| ------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | --------------------------------------------------- |
|
||||
| Beelink EQ13 (<a href="https://amzn.to/4jn2qVr" target="_blank" rel="nofollow noopener sponsored">Amazon</a>) | Can run object detection on several 1080p cameras with low-medium activity | Dual gigabit NICs for easy isolated camera network. |
|
||||
| Intel 1120p ([Amazon](https://www.amazon.com/Beelink-i3-1220P-Computer-Display-Gigabit/dp/B0DDCKT9YP) | Can handle a large number of 1080p cameras with high activity | |
|
||||
| Intel 125H ([Amazon](https://www.amazon.com/MINISFORUM-Pro-125H-Barebone-Computer-HDMI2-1/dp/B0FH21FSZM) | Can handle a significant number of 1080p cameras with high activity | Includes NPU for more efficient detection in 0.17+ |
|
||||
| Intel 125H ([Amazon](https://www.amazon.com/MINISFORUM-Pro-125H-Barebone-Computer-HDMI2-1/dp/B0FH21FSZM) | Can handle a significant number of 1080p cameras with high activity | Includes NPU for more efficient detection in 0.17+ |
|
||||
|
||||
## Detectors
|
||||
|
||||
@ -55,10 +55,12 @@ Frigate supports multiple different detectors that work on different types of ha
|
||||
**Most Hardware**
|
||||
|
||||
- [Hailo](#hailo-8): The Hailo8 and Hailo8L AI Acceleration module is available in m.2 format with a HAT for RPi devices offering a wide range of compatibility with devices.
|
||||
|
||||
- [Supports many model architectures](../../configuration/object_detectors#configuration)
|
||||
- Runs best with tiny or small size models
|
||||
|
||||
- [Google Coral EdgeTPU](#google-coral-tpu): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices.
|
||||
|
||||
- [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#edge-tpu-detector)
|
||||
|
||||
- <CommunityBadge /> [MemryX](#memryx-mx3): The MX3 M.2 accelerator module is available in m.2 format allowing for a wide range of compatibility with devices.
|
||||
@ -87,6 +89,7 @@ Frigate supports multiple different detectors that work on different types of ha
|
||||
**Nvidia**
|
||||
|
||||
- [TensortRT](#tensorrt---nvidia-gpu): TensorRT can run on Nvidia GPUs to provide efficient object detection.
|
||||
|
||||
- [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx-supported-models)
|
||||
- Runs well with any size models including large
|
||||
|
||||
@ -149,7 +152,9 @@ The OpenVINO detector type is able to run on:
|
||||
|
||||
:::note
|
||||
|
||||
Intel B-series (Battlemage) GPUs are not officially supported with Frigate 0.17, though a user has [provided steps to rebuild the Frigate container](https://github.com/blakeblackshear/frigate/discussions/21257) with support for them.
|
||||
Intel NPUs have seen [limited success in community deployments](https://github.com/blakeblackshear/frigate/discussions/13248#discussioncomment-12347357), although they remain officially unsupported.
|
||||
|
||||
In testing, the NPU delivered performance that was only comparable to — or in some cases worse than — the integrated GPU.
|
||||
|
||||
:::
|
||||
|
||||
|
||||
@ -37,7 +37,7 @@ cameras:
|
||||
|
||||
## Steps
|
||||
|
||||
1. Export or copy the clip you want to replay to the Frigate host (e.g., `/media/frigate/` or `debug/clips/`). Depending on what you are looking to debug, it is often helpful to add some "pre-capture" time (where the tracked object is not yet visible) to the clip when exporting.
|
||||
1. Export or copy the clip you want to replay to the Frigate host (e.g., `/media/frigate/` or `debug/clips/`).
|
||||
2. Add the temporary camera to `config/config.yml` (example above). Use a unique name such as `test` or `replay_camera` so it's easy to remove later.
|
||||
- If you're debugging a specific camera, copy the settings from that camera (frame rate, model/enrichment settings, zones, etc.) into the temporary camera so the replay closely matches the original environment. Leave `record` and `snapshots` disabled unless you are specifically debugging recording or snapshot behavior.
|
||||
3. Restart Frigate.
|
||||
|
||||
@ -23,12 +23,7 @@ from markupsafe import escape
|
||||
from peewee import SQL, fn, operator
|
||||
from pydantic import ValidationError
|
||||
|
||||
from frigate.api.auth import (
|
||||
allow_any_authenticated,
|
||||
allow_public,
|
||||
get_allowed_cameras_for_filter,
|
||||
require_role,
|
||||
)
|
||||
from frigate.api.auth import allow_any_authenticated, allow_public, require_role
|
||||
from frigate.api.defs.query.app_query_parameters import AppTimelineHourlyQueryParameters
|
||||
from frigate.api.defs.request.app_body import AppConfigSetBody
|
||||
from frigate.api.defs.tags import Tags
|
||||
@ -692,19 +687,13 @@ def plusModels(request: Request, filterByCurrentModelDetector: bool = False):
|
||||
@router.get(
|
||||
"/recognized_license_plates", dependencies=[Depends(allow_any_authenticated())]
|
||||
)
|
||||
def get_recognized_license_plates(
|
||||
split_joined: Optional[int] = None,
|
||||
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
|
||||
):
|
||||
def get_recognized_license_plates(split_joined: Optional[int] = None):
|
||||
try:
|
||||
query = (
|
||||
Event.select(
|
||||
SQL("json_extract(data, '$.recognized_license_plate') AS plate")
|
||||
)
|
||||
.where(
|
||||
(SQL("json_extract(data, '$.recognized_license_plate') IS NOT NULL"))
|
||||
& (Event.camera << allowed_cameras)
|
||||
)
|
||||
.where(SQL("json_extract(data, '$.recognized_license_plate') IS NOT NULL"))
|
||||
.distinct()
|
||||
)
|
||||
recognized_license_plates = [row[0] for row in query.tuples()]
|
||||
|
||||
@ -848,10 +848,9 @@ async def onvif_probe(
|
||||
try:
|
||||
if isinstance(uri, str) and uri.startswith("rtsp://"):
|
||||
if username and password and "@" not in uri:
|
||||
# Inject raw credentials and add only the
|
||||
# authenticated version. The credentials will be encoded
|
||||
# later by ffprobe_stream or the config system.
|
||||
cred = f"{username}:{password}@"
|
||||
# Inject URL-encoded credentials and add only the
|
||||
# authenticated version.
|
||||
cred = f"{quote_plus(username)}:{quote_plus(password)}@"
|
||||
injected = uri.replace(
|
||||
"rtsp://", f"rtsp://{cred}", 1
|
||||
)
|
||||
@ -904,8 +903,12 @@ async def onvif_probe(
|
||||
"/cam/realmonitor?channel=1&subtype=0",
|
||||
"/11",
|
||||
]
|
||||
# Use raw credentials for pattern fallback URIs when provided
|
||||
auth_str = f"{username}:{password}@" if username and password else ""
|
||||
# Use URL-encoded credentials for pattern fallback URIs when provided
|
||||
auth_str = (
|
||||
f"{quote_plus(username)}:{quote_plus(password)}@"
|
||||
if username and password
|
||||
else ""
|
||||
)
|
||||
rtsp_port = 554
|
||||
for path in common_paths:
|
||||
uri = f"rtsp://{auth_str}{host}:{rtsp_port}{path}"
|
||||
@ -927,7 +930,7 @@ async def onvif_probe(
|
||||
and uri.startswith("rtsp://")
|
||||
and "@" not in uri
|
||||
):
|
||||
cred = f"{username}:{password}@"
|
||||
cred = f"{quote_plus(username)}:{quote_plus(password)}@"
|
||||
cred_uri = uri.replace("rtsp://", f"rtsp://{cred}", 1)
|
||||
if cred_uri not in to_test:
|
||||
to_test.append(cred_uri)
|
||||
|
||||
@ -662,13 +662,6 @@ class FrigateConfig(FrigateBaseModel):
|
||||
# generate zone contours
|
||||
if len(camera_config.zones) > 0:
|
||||
for zone in camera_config.zones.values():
|
||||
if zone.filters:
|
||||
for object_name, filter_config in zone.filters.items():
|
||||
zone.filters[object_name] = RuntimeFilterConfig(
|
||||
frame_shape=camera_config.frame_shape,
|
||||
**filter_config.model_dump(exclude_unset=True),
|
||||
)
|
||||
|
||||
zone.generate_contour(camera_config.frame_shape)
|
||||
|
||||
# Set live view stream if none is set
|
||||
|
||||
@ -2,7 +2,6 @@
|
||||
|
||||
import logging
|
||||
import os
|
||||
import threading
|
||||
import warnings
|
||||
|
||||
from transformers import AutoFeatureExtractor, AutoTokenizer
|
||||
@ -55,7 +54,6 @@ class JinaV1TextEmbedding(BaseEmbedding):
|
||||
self.tokenizer = None
|
||||
self.feature_extractor = None
|
||||
self.runner = None
|
||||
self._lock = threading.Lock()
|
||||
files_names = list(self.download_urls.keys()) + [self.tokenizer_file]
|
||||
|
||||
if not all(
|
||||
@ -136,18 +134,17 @@ class JinaV1TextEmbedding(BaseEmbedding):
|
||||
)
|
||||
|
||||
def _preprocess_inputs(self, raw_inputs):
|
||||
with self._lock:
|
||||
max_length = max(len(self.tokenizer.encode(text)) for text in raw_inputs)
|
||||
return [
|
||||
self.tokenizer(
|
||||
text,
|
||||
padding="max_length",
|
||||
truncation=True,
|
||||
max_length=max_length,
|
||||
return_tensors="np",
|
||||
)
|
||||
for text in raw_inputs
|
||||
]
|
||||
max_length = max(len(self.tokenizer.encode(text)) for text in raw_inputs)
|
||||
return [
|
||||
self.tokenizer(
|
||||
text,
|
||||
padding="max_length",
|
||||
truncation=True,
|
||||
max_length=max_length,
|
||||
return_tensors="np",
|
||||
)
|
||||
for text in raw_inputs
|
||||
]
|
||||
|
||||
|
||||
class JinaV1ImageEmbedding(BaseEmbedding):
|
||||
@ -177,7 +174,6 @@ class JinaV1ImageEmbedding(BaseEmbedding):
|
||||
self.download_path = os.path.join(MODEL_CACHE_DIR, self.model_name)
|
||||
self.feature_extractor = None
|
||||
self.runner: BaseModelRunner | None = None
|
||||
self._lock = threading.Lock()
|
||||
files_names = list(self.download_urls.keys())
|
||||
if not all(
|
||||
os.path.exists(os.path.join(self.download_path, n)) for n in files_names
|
||||
@ -220,9 +216,8 @@ class JinaV1ImageEmbedding(BaseEmbedding):
|
||||
)
|
||||
|
||||
def _preprocess_inputs(self, raw_inputs):
|
||||
with self._lock:
|
||||
processed_images = [self._process_image(img) for img in raw_inputs]
|
||||
return [
|
||||
self.feature_extractor(images=image, return_tensors="np")
|
||||
for image in processed_images
|
||||
]
|
||||
processed_images = [self._process_image(img) for img in raw_inputs]
|
||||
return [
|
||||
self.feature_extractor(images=image, return_tensors="np")
|
||||
for image in processed_images
|
||||
]
|
||||
|
||||
@ -3,8 +3,8 @@
|
||||
import logging
|
||||
from typing import Optional
|
||||
|
||||
from google import genai
|
||||
from google.genai import errors, types
|
||||
import google.generativeai as genai
|
||||
from google.api_core.exceptions import GoogleAPICallError
|
||||
|
||||
from frigate.config import GenAIProviderEnum
|
||||
from frigate.genai import GenAIClient, register_genai_provider
|
||||
@ -16,59 +16,44 @@ logger = logging.getLogger(__name__)
|
||||
class GeminiClient(GenAIClient):
|
||||
"""Generative AI client for Frigate using Gemini."""
|
||||
|
||||
provider: genai.Client
|
||||
provider: genai.GenerativeModel
|
||||
|
||||
def _init_provider(self):
|
||||
"""Initialize the client."""
|
||||
# Merge provider_options into HttpOptions
|
||||
http_options_dict = {
|
||||
"api_version": "v1",
|
||||
"timeout": int(self.timeout * 1000), # requires milliseconds
|
||||
"retry_options": types.HttpRetryOptions(
|
||||
attempts=3,
|
||||
initial_delay=1.0,
|
||||
max_delay=60.0,
|
||||
exp_base=2.0,
|
||||
jitter=1.0,
|
||||
http_status_codes=[429, 500, 502, 503, 504],
|
||||
),
|
||||
}
|
||||
|
||||
if isinstance(self.genai_config.provider_options, dict):
|
||||
http_options_dict.update(self.genai_config.provider_options)
|
||||
|
||||
return genai.Client(
|
||||
api_key=self.genai_config.api_key,
|
||||
http_options=types.HttpOptions(**http_options_dict),
|
||||
genai.configure(api_key=self.genai_config.api_key)
|
||||
return genai.GenerativeModel(
|
||||
self.genai_config.model, **self.genai_config.provider_options
|
||||
)
|
||||
|
||||
def _send(self, prompt: str, images: list[bytes]) -> Optional[str]:
|
||||
"""Submit a request to Gemini."""
|
||||
contents = [
|
||||
types.Part.from_bytes(data=img, mime_type="image/jpeg") for img in images
|
||||
data = [
|
||||
{
|
||||
"mime_type": "image/jpeg",
|
||||
"data": img,
|
||||
}
|
||||
for img in images
|
||||
] + [prompt]
|
||||
try:
|
||||
# Merge runtime_options into generation_config if provided
|
||||
generation_config_dict = {"candidate_count": 1}
|
||||
generation_config_dict.update(self.genai_config.runtime_options)
|
||||
|
||||
response = self.provider.models.generate_content(
|
||||
model=self.genai_config.model,
|
||||
contents=contents,
|
||||
config=types.GenerateContentConfig(
|
||||
**generation_config_dict,
|
||||
response = self.provider.generate_content(
|
||||
data,
|
||||
generation_config=genai.types.GenerationConfig(
|
||||
**generation_config_dict
|
||||
),
|
||||
request_options=genai.types.RequestOptions(
|
||||
timeout=self.timeout,
|
||||
),
|
||||
)
|
||||
except errors.APIError as e:
|
||||
except GoogleAPICallError as e:
|
||||
logger.warning("Gemini returned an error: %s", str(e))
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.warning("An unexpected error occurred with Gemini: %s", str(e))
|
||||
return None
|
||||
|
||||
try:
|
||||
description = response.text.strip()
|
||||
except (ValueError, AttributeError):
|
||||
except ValueError:
|
||||
# No description was generated
|
||||
return None
|
||||
return description
|
||||
|
||||
@ -89,7 +89,6 @@ def apply_log_levels(default: str, log_levels: dict[str, LogLevel]) -> None:
|
||||
"ws4py": LogLevel.error,
|
||||
"PIL": LogLevel.warning,
|
||||
"numba": LogLevel.warning,
|
||||
"google_genai.models": LogLevel.warning,
|
||||
**log_levels,
|
||||
}
|
||||
|
||||
|
||||
@ -97,7 +97,6 @@ class RecordingMaintainer(threading.Thread):
|
||||
self.object_recordings_info: dict[str, list] = defaultdict(list)
|
||||
self.audio_recordings_info: dict[str, list] = defaultdict(list)
|
||||
self.end_time_cache: dict[str, Tuple[datetime.datetime, float]] = {}
|
||||
self.unexpected_cache_files_logged: bool = False
|
||||
|
||||
async def move_files(self) -> None:
|
||||
cache_files = [
|
||||
@ -113,14 +112,7 @@ class RecordingMaintainer(threading.Thread):
|
||||
for cache in cache_files:
|
||||
cache_path = os.path.join(CACHE_DIR, cache)
|
||||
basename = os.path.splitext(cache)[0]
|
||||
try:
|
||||
camera, date = basename.rsplit("@", maxsplit=1)
|
||||
except ValueError:
|
||||
if not self.unexpected_cache_files_logged:
|
||||
logger.warning("Skipping unexpected files in cache")
|
||||
self.unexpected_cache_files_logged = True
|
||||
continue
|
||||
|
||||
camera, date = basename.rsplit("@", maxsplit=1)
|
||||
start_time = datetime.datetime.strptime(
|
||||
date, CACHE_SEGMENT_FORMAT
|
||||
).astimezone(datetime.timezone.utc)
|
||||
@ -172,13 +164,7 @@ class RecordingMaintainer(threading.Thread):
|
||||
|
||||
cache_path = os.path.join(CACHE_DIR, cache)
|
||||
basename = os.path.splitext(cache)[0]
|
||||
try:
|
||||
camera, date = basename.rsplit("@", maxsplit=1)
|
||||
except ValueError:
|
||||
if not self.unexpected_cache_files_logged:
|
||||
logger.warning("Skipping unexpected files in cache")
|
||||
self.unexpected_cache_files_logged = True
|
||||
continue
|
||||
camera, date = basename.rsplit("@", maxsplit=1)
|
||||
|
||||
# important that start_time is utc because recordings are stored and compared in utc
|
||||
start_time = datetime.datetime.strptime(
|
||||
|
||||
@ -632,49 +632,6 @@ class TestConfig(unittest.TestCase):
|
||||
)
|
||||
assert frigate_config.cameras["back"].zones["test"].color != (0, 0, 0)
|
||||
|
||||
def test_zone_filter_area_percent_converts_to_pixels(self):
|
||||
config = {
|
||||
"mqtt": {"host": "mqtt"},
|
||||
"record": {
|
||||
"alerts": {
|
||||
"retain": {
|
||||
"days": 20,
|
||||
}
|
||||
}
|
||||
},
|
||||
"cameras": {
|
||||
"back": {
|
||||
"ffmpeg": {
|
||||
"inputs": [
|
||||
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
|
||||
]
|
||||
},
|
||||
"detect": {
|
||||
"height": 1080,
|
||||
"width": 1920,
|
||||
"fps": 5,
|
||||
},
|
||||
"zones": {
|
||||
"notification": {
|
||||
"coordinates": "0.03,1,0.025,0,0.626,0,0.643,1",
|
||||
"objects": ["person"],
|
||||
"filters": {"person": {"min_area": 0.1}},
|
||||
}
|
||||
},
|
||||
}
|
||||
},
|
||||
}
|
||||
|
||||
frigate_config = FrigateConfig(**config)
|
||||
expected_min_area = int(1080 * 1920 * 0.1)
|
||||
assert (
|
||||
frigate_config.cameras["back"]
|
||||
.zones["notification"]
|
||||
.filters["person"]
|
||||
.min_area
|
||||
== expected_min_area
|
||||
)
|
||||
|
||||
def test_zone_relative_matches_explicit(self):
|
||||
config = {
|
||||
"mqtt": {"host": "mqtt"},
|
||||
|
||||
@ -1,66 +0,0 @@
|
||||
import sys
|
||||
import unittest
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
# Mock complex imports before importing maintainer
|
||||
sys.modules["frigate.comms.inter_process"] = MagicMock()
|
||||
sys.modules["frigate.comms.detections_updater"] = MagicMock()
|
||||
sys.modules["frigate.comms.recordings_updater"] = MagicMock()
|
||||
sys.modules["frigate.config.camera.updater"] = MagicMock()
|
||||
|
||||
# Now import the class under test
|
||||
from frigate.config import FrigateConfig # noqa: E402
|
||||
from frigate.record.maintainer import RecordingMaintainer # noqa: E402
|
||||
|
||||
|
||||
class TestMaintainer(unittest.IsolatedAsyncioTestCase):
|
||||
async def test_move_files_survives_bad_filename(self):
|
||||
config = MagicMock(spec=FrigateConfig)
|
||||
config.cameras = {}
|
||||
stop_event = MagicMock()
|
||||
|
||||
maintainer = RecordingMaintainer(config, stop_event)
|
||||
|
||||
# We need to mock end_time_cache to avoid key errors if logic proceeds
|
||||
maintainer.end_time_cache = {}
|
||||
|
||||
# Mock filesystem
|
||||
# One bad file, one good file
|
||||
files = ["bad_filename.mp4", "camera@20210101000000+0000.mp4"]
|
||||
|
||||
with patch("os.listdir", return_value=files):
|
||||
with patch("os.path.isfile", return_value=True):
|
||||
with patch(
|
||||
"frigate.record.maintainer.psutil.process_iter", return_value=[]
|
||||
):
|
||||
with patch("frigate.record.maintainer.logger.warning") as warn:
|
||||
# Mock validate_and_move_segment to avoid further logic
|
||||
maintainer.validate_and_move_segment = MagicMock()
|
||||
|
||||
try:
|
||||
await maintainer.move_files()
|
||||
except ValueError as e:
|
||||
if "not enough values to unpack" in str(e):
|
||||
self.fail("move_files() crashed on bad filename!")
|
||||
raise e
|
||||
except Exception:
|
||||
# Ignore other errors (like DB connection) as we only care about the unpack crash
|
||||
pass
|
||||
|
||||
# The bad filename is encountered in multiple loops, but should only warn once.
|
||||
matching = [
|
||||
c
|
||||
for c in warn.call_args_list
|
||||
if c.args
|
||||
and isinstance(c.args[0], str)
|
||||
and "Skipping unexpected files in cache" in c.args[0]
|
||||
]
|
||||
self.assertEqual(
|
||||
1,
|
||||
len(matching),
|
||||
f"Expected a single warning for unexpected files, got {len(matching)}",
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@ -540,16 +540,9 @@ def get_jetson_stats() -> Optional[dict[int, dict]]:
|
||||
try:
|
||||
results["mem"] = "-" # no discrete gpu memory
|
||||
|
||||
if os.path.exists("/sys/devices/gpu.0/load"):
|
||||
with open("/sys/devices/gpu.0/load", "r") as f:
|
||||
gpuload = float(f.readline()) / 10
|
||||
results["gpu"] = f"{gpuload}%"
|
||||
elif os.path.exists("/sys/devices/platform/gpu.0/load"):
|
||||
with open("/sys/devices/platform/gpu.0/load", "r") as f:
|
||||
gpuload = float(f.readline()) / 10
|
||||
results["gpu"] = f"{gpuload}%"
|
||||
else:
|
||||
results["gpu"] = "-"
|
||||
with open("/sys/devices/gpu.0/load", "r") as f:
|
||||
gpuload = float(f.readline()) / 10
|
||||
results["gpu"] = f"{gpuload}%"
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
|
||||
@ -64,12 +64,10 @@ def stop_ffmpeg(ffmpeg_process: sp.Popen[Any], logger: logging.Logger):
|
||||
try:
|
||||
logger.info("Waiting for ffmpeg to exit gracefully...")
|
||||
ffmpeg_process.communicate(timeout=30)
|
||||
logger.info("FFmpeg has exited")
|
||||
except sp.TimeoutExpired:
|
||||
logger.info("FFmpeg didn't exit. Force killing...")
|
||||
ffmpeg_process.kill()
|
||||
ffmpeg_process.communicate()
|
||||
logger.info("FFmpeg has been killed")
|
||||
ffmpeg_process = None
|
||||
|
||||
|
||||
|
||||
35
web/package-lock.json
generated
35
web/package-lock.json
generated
@ -48,7 +48,7 @@
|
||||
"idb-keyval": "^6.2.1",
|
||||
"immer": "^10.1.1",
|
||||
"konva": "^9.3.18",
|
||||
"lodash": "^4.17.23",
|
||||
"lodash": "^4.17.21",
|
||||
"lucide-react": "^0.477.0",
|
||||
"monaco-yaml": "^5.3.1",
|
||||
"next-themes": "^0.3.0",
|
||||
@ -64,7 +64,7 @@
|
||||
"react-i18next": "^15.2.0",
|
||||
"react-icons": "^5.5.0",
|
||||
"react-konva": "^18.2.10",
|
||||
"react-router-dom": "^6.30.3",
|
||||
"react-router-dom": "^6.26.0",
|
||||
"react-swipeable": "^7.0.2",
|
||||
"react-tracked": "^2.0.1",
|
||||
"react-transition-group": "^4.4.5",
|
||||
@ -3293,9 +3293,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@remix-run/router": {
|
||||
"version": "1.23.2",
|
||||
"resolved": "https://registry.npmjs.org/@remix-run/router/-/router-1.23.2.tgz",
|
||||
"integrity": "sha512-Ic6m2U/rMjTkhERIa/0ZtXJP17QUi2CbWE7cqx4J58M8aA3QTfW+2UlQ4psvTX9IO1RfNVhK3pcpdjej7L+t2w==",
|
||||
"version": "1.19.0",
|
||||
"resolved": "https://registry.npmjs.org/@remix-run/router/-/router-1.19.0.tgz",
|
||||
"integrity": "sha512-zDICCLKEwbVYTS6TjYaWtHXxkdoUvD/QXvyVZjGCsWz5vyH7aFeONlPffPdW+Y/t6KT0MgXb2Mfjun9YpWN1dA==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=14.0.0"
|
||||
@ -7210,10 +7210,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/lodash": {
|
||||
"version": "4.17.23",
|
||||
"resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.23.tgz",
|
||||
"integrity": "sha512-LgVTMpQtIopCi79SJeDiP0TfWi5CNEc/L/aRdTh3yIvmZXTnheWpKjSZhnvMl8iXbC1tFg9gdHHDMLoV7CnG+w==",
|
||||
"license": "MIT"
|
||||
"version": "4.17.21",
|
||||
"resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.21.tgz",
|
||||
"integrity": "sha512-v2kDEe57lecTulaDIuNTPy3Ry4gLGJ6Z1O3vE1krgXZNrsQ+LFTGHVxVjcXPs17LhbZVGedAJv8XZ1tvj5FvSg=="
|
||||
},
|
||||
"node_modules/lodash.merge": {
|
||||
"version": "4.6.2",
|
||||
@ -8618,12 +8617,12 @@
|
||||
}
|
||||
},
|
||||
"node_modules/react-router": {
|
||||
"version": "6.30.3",
|
||||
"resolved": "https://registry.npmjs.org/react-router/-/react-router-6.30.3.tgz",
|
||||
"integrity": "sha512-XRnlbKMTmktBkjCLE8/XcZFlnHvr2Ltdr1eJX4idL55/9BbORzyZEaIkBFDhFGCEWBBItsVrDxwx3gnisMitdw==",
|
||||
"version": "6.26.0",
|
||||
"resolved": "https://registry.npmjs.org/react-router/-/react-router-6.26.0.tgz",
|
||||
"integrity": "sha512-wVQq0/iFYd3iZ9H2l3N3k4PL8EEHcb0XlU2Na8nEwmiXgIUElEH6gaJDtUQxJ+JFzmIXaQjfdpcGWaM6IoQGxg==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@remix-run/router": "1.23.2"
|
||||
"@remix-run/router": "1.19.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=14.0.0"
|
||||
@ -8633,13 +8632,13 @@
|
||||
}
|
||||
},
|
||||
"node_modules/react-router-dom": {
|
||||
"version": "6.30.3",
|
||||
"resolved": "https://registry.npmjs.org/react-router-dom/-/react-router-dom-6.30.3.tgz",
|
||||
"integrity": "sha512-pxPcv1AczD4vso7G4Z3TKcvlxK7g7TNt3/FNGMhfqyntocvYKj+GCatfigGDjbLozC4baguJ0ReCigoDJXb0ag==",
|
||||
"version": "6.26.0",
|
||||
"resolved": "https://registry.npmjs.org/react-router-dom/-/react-router-dom-6.26.0.tgz",
|
||||
"integrity": "sha512-RRGUIiDtLrkX3uYcFiCIxKFWMcWQGMojpYZfcstc63A1+sSnVgILGIm9gNUA6na3Fm1QuPGSBQH2EMbAZOnMsQ==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@remix-run/router": "1.23.2",
|
||||
"react-router": "6.30.3"
|
||||
"@remix-run/router": "1.19.0",
|
||||
"react-router": "6.26.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=14.0.0"
|
||||
|
||||
@ -54,7 +54,7 @@
|
||||
"idb-keyval": "^6.2.1",
|
||||
"immer": "^10.1.1",
|
||||
"konva": "^9.3.18",
|
||||
"lodash": "^4.17.23",
|
||||
"lodash": "^4.17.21",
|
||||
"lucide-react": "^0.477.0",
|
||||
"monaco-yaml": "^5.3.1",
|
||||
"next-themes": "^0.3.0",
|
||||
@ -70,7 +70,7 @@
|
||||
"react-i18next": "^15.2.0",
|
||||
"react-icons": "^5.5.0",
|
||||
"react-konva": "^18.2.10",
|
||||
"react-router-dom": "^6.30.3",
|
||||
"react-router-dom": "^6.26.0",
|
||||
"react-swipeable": "^7.0.2",
|
||||
"react-tracked": "^2.0.1",
|
||||
"react-transition-group": "^4.4.5",
|
||||
|
||||
@ -3,7 +3,6 @@
|
||||
"untilForTime": "Until {{time}}",
|
||||
"untilForRestart": "Until Frigate restarts.",
|
||||
"untilRestart": "Until restart",
|
||||
"never": "Never",
|
||||
"ago": "{{timeAgo}} ago",
|
||||
"justNow": "Just now",
|
||||
"today": "Today",
|
||||
|
||||
@ -181,16 +181,6 @@
|
||||
"restricted": {
|
||||
"title": "No Cameras Available",
|
||||
"description": "You don't have permission to view any cameras in this group."
|
||||
},
|
||||
"default": {
|
||||
"title": "No Cameras Configured",
|
||||
"description": "Get started by connecting a camera to Frigate.",
|
||||
"buttonText": "Add Camera"
|
||||
},
|
||||
"group": {
|
||||
"title": "No Cameras in Group",
|
||||
"description": "This camera group has no assigned or enabled cameras.",
|
||||
"buttonText": "Manage Groups"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -386,11 +386,11 @@
|
||||
"title": "Camera Review Settings",
|
||||
"object_descriptions": {
|
||||
"title": "Generative AI Object Descriptions",
|
||||
"desc": "Temporarily enable/disable Generative AI object descriptions for this camera until Frigate restarts. When disabled, AI generated descriptions will not be requested for tracked objects on this camera."
|
||||
"desc": "Temporarily enable/disable Generative AI object descriptions for this camera. When disabled, AI generated descriptions will not be requested for tracked objects on this camera."
|
||||
},
|
||||
"review_descriptions": {
|
||||
"title": "Generative AI Review Descriptions",
|
||||
"desc": "Temporarily enable/disable Generative AI review descriptions for this camera until Frigate restarts. When disabled, AI generated descriptions will not be requested for review items on this camera."
|
||||
"desc": "Temporarily enable/disable Generative AI review descriptions for this camera. When disabled, AI generated descriptions will not be requested for review items on this camera."
|
||||
},
|
||||
"review": {
|
||||
"title": "Review",
|
||||
|
||||
@ -35,9 +35,7 @@ export function EmptyCard({
|
||||
{icon}
|
||||
{TitleComponent}
|
||||
{description && (
|
||||
<div className="mb-3 text-center text-secondary-foreground">
|
||||
{description}
|
||||
</div>
|
||||
<div className="mb-3 text-secondary-foreground">{description}</div>
|
||||
)}
|
||||
{buttonText?.length && (
|
||||
<Button size="sm" variant="select">
|
||||
|
||||
@ -268,7 +268,7 @@ export default function CreateTriggerDialog({
|
||||
<FormItem className="flex flex-row items-center justify-between">
|
||||
<div className="space-y-0.5">
|
||||
<FormLabel className="text-base">
|
||||
{t("button.enabled", { ns: "common" })}
|
||||
{t("enabled", { ns: "common" })}
|
||||
</FormLabel>
|
||||
<div className="text-sm text-muted-foreground">
|
||||
{t("triggers.dialog.form.enabled.description")}
|
||||
@ -394,10 +394,7 @@ export default function CreateTriggerDialog({
|
||||
</FormLabel>
|
||||
<div className="space-y-2">
|
||||
{availableActions.map((action) => (
|
||||
<label
|
||||
key={action}
|
||||
className="flex cursor-pointer items-center space-x-2"
|
||||
>
|
||||
<div key={action} className="flex items-center space-x-2">
|
||||
<FormControl>
|
||||
<Checkbox
|
||||
checked={form
|
||||
@ -419,10 +416,10 @@ export default function CreateTriggerDialog({
|
||||
}}
|
||||
/>
|
||||
</FormControl>
|
||||
<span className="text-sm font-normal">
|
||||
<FormLabel className="text-sm font-normal">
|
||||
{t(`triggers.actions.${action}`)}
|
||||
</span>
|
||||
</label>
|
||||
</FormLabel>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
<FormDescription>
|
||||
|
||||
@ -13,7 +13,7 @@ import HlsVideoPlayer from "@/components/player/HlsVideoPlayer";
|
||||
import { baseUrl } from "@/api/baseUrl";
|
||||
import { REVIEW_PADDING } from "@/types/review";
|
||||
import {
|
||||
ASPECT_PORTRAIT_LAYOUT,
|
||||
ASPECT_VERTICAL_LAYOUT,
|
||||
ASPECT_WIDE_LAYOUT,
|
||||
Recording,
|
||||
} from "@/types/record";
|
||||
@ -39,7 +39,6 @@ import { useApiHost } from "@/api";
|
||||
import ImageLoadingIndicator from "@/components/indicators/ImageLoadingIndicator";
|
||||
import ObjectTrackOverlay from "../ObjectTrackOverlay";
|
||||
import { useIsAdmin } from "@/hooks/use-is-admin";
|
||||
import { VideoResolutionType } from "@/types/live";
|
||||
|
||||
type TrackingDetailsProps = {
|
||||
className?: string;
|
||||
@ -254,25 +253,16 @@ export function TrackingDetails({
|
||||
|
||||
const [timelineSize] = useResizeObserver(timelineContainerRef);
|
||||
|
||||
const [fullResolution, setFullResolution] = useState<VideoResolutionType>({
|
||||
width: 0,
|
||||
height: 0,
|
||||
});
|
||||
|
||||
const aspectRatio = useMemo(() => {
|
||||
if (!config) {
|
||||
return 16 / 9;
|
||||
}
|
||||
|
||||
if (fullResolution.width && fullResolution.height) {
|
||||
return fullResolution.width / fullResolution.height;
|
||||
}
|
||||
|
||||
return (
|
||||
config.cameras[event.camera].detect.width /
|
||||
config.cameras[event.camera].detect.height
|
||||
);
|
||||
}, [config, event, fullResolution]);
|
||||
}, [config, event]);
|
||||
|
||||
const label = event.sub_label
|
||||
? event.sub_label
|
||||
@ -470,7 +460,7 @@ export function TrackingDetails({
|
||||
return "normal";
|
||||
} else if (aspectRatio > ASPECT_WIDE_LAYOUT) {
|
||||
return "wide";
|
||||
} else if (aspectRatio < ASPECT_PORTRAIT_LAYOUT) {
|
||||
} else if (aspectRatio < ASPECT_VERTICAL_LAYOUT) {
|
||||
return "tall";
|
||||
} else {
|
||||
return "normal";
|
||||
@ -566,7 +556,6 @@ export function TrackingDetails({
|
||||
onSeekToTime={handleSeekToTime}
|
||||
onUploadFrame={onUploadFrameToPlus}
|
||||
onPlaying={() => setIsVideoLoading(false)}
|
||||
setFullResolution={setFullResolution}
|
||||
isDetailMode={true}
|
||||
camera={event.camera}
|
||||
currentTimeOverride={currentTime}
|
||||
@ -634,7 +623,7 @@ export function TrackingDetails({
|
||||
<div
|
||||
className={cn(
|
||||
isDesktop && "justify-start overflow-hidden",
|
||||
aspectRatio > 1 && aspectRatio < ASPECT_PORTRAIT_LAYOUT
|
||||
aspectRatio > 1 && aspectRatio < 1.5
|
||||
? "lg:basis-3/5"
|
||||
: "lg:basis-2/5",
|
||||
)}
|
||||
|
||||
@ -16,7 +16,7 @@ import { zodResolver } from "@hookform/resolvers/zod";
|
||||
import { useForm, useFieldArray } from "react-hook-form";
|
||||
import { z } from "zod";
|
||||
import axios from "axios";
|
||||
import { toast } from "sonner";
|
||||
import { toast, Toaster } from "sonner";
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { useState, useMemo, useEffect } from "react";
|
||||
import { LuTrash2, LuPlus } from "react-icons/lu";
|
||||
@ -26,7 +26,6 @@ import useSWR from "swr";
|
||||
import { processCameraName } from "@/utils/cameraUtil";
|
||||
import { Label } from "@/components/ui/label";
|
||||
import { ConfigSetBody } from "@/types/cameraWizard";
|
||||
import { Toaster } from "../ui/sonner";
|
||||
|
||||
const RoleEnum = z.enum(["audio", "detect", "record"]);
|
||||
type Role = z.infer<typeof RoleEnum>;
|
||||
|
||||
@ -887,10 +887,7 @@ function LifecycleItem({
|
||||
</span>
|
||||
<span className="font-medium text-foreground">
|
||||
{attributeAreaPx}{" "}
|
||||
{t("information.pixels", {
|
||||
ns: "common",
|
||||
area: attributeAreaPx,
|
||||
})}{" "}
|
||||
{t("information.pixels", { ns: "common" })}{" "}
|
||||
<span className="text-secondary-foreground">·</span>{" "}
|
||||
{attributeAreaPct}%
|
||||
</span>
|
||||
|
||||
@ -142,10 +142,7 @@ export default function Step3ThresholdAndActions({
|
||||
<FormLabel>{t("triggers.dialog.form.actions.title")}</FormLabel>
|
||||
<div className="space-y-2">
|
||||
{availableActions.map((action) => (
|
||||
<label
|
||||
key={action}
|
||||
className="flex cursor-pointer items-center space-x-2"
|
||||
>
|
||||
<div key={action} className="flex items-center space-x-2">
|
||||
<FormControl>
|
||||
<Checkbox
|
||||
checked={form
|
||||
@ -167,10 +164,10 @@ export default function Step3ThresholdAndActions({
|
||||
}}
|
||||
/>
|
||||
</FormControl>
|
||||
<span className="text-sm font-normal">
|
||||
<FormLabel className="text-sm font-normal">
|
||||
{t(`triggers.actions.${action}`)}
|
||||
</span>
|
||||
</label>
|
||||
</FormLabel>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
<FormDescription>
|
||||
@ -200,7 +197,9 @@ export default function Step3ThresholdAndActions({
|
||||
{isLoading && <ActivityIndicator className="mr-2 size-5" />}
|
||||
{isLoading
|
||||
? t("button.saving", { ns: "common" })
|
||||
: t("button.save", { ns: "common" })}
|
||||
: t("triggers.dialog.form.save", {
|
||||
defaultValue: "Save Trigger",
|
||||
})}
|
||||
</Button>
|
||||
</div>
|
||||
</form>
|
||||
|
||||
@ -206,7 +206,7 @@ function Exports() {
|
||||
>
|
||||
{Object.values(exports).map((item) => (
|
||||
<ExportCard
|
||||
key={item.id}
|
||||
key={item.name}
|
||||
className={
|
||||
search == "" || filteredExports.includes(item) ? "" : "hidden"
|
||||
}
|
||||
|
||||
@ -44,5 +44,4 @@ export type RecordingStartingPoint = {
|
||||
export type RecordingPlayerError = "stalled" | "startup";
|
||||
|
||||
export const ASPECT_VERTICAL_LAYOUT = 1.5;
|
||||
export const ASPECT_PORTRAIT_LAYOUT = 1.333;
|
||||
export const ASPECT_WIDE_LAYOUT = 2;
|
||||
|
||||
@ -81,8 +81,7 @@ export async function detectReolinkCamera(
|
||||
export function maskUri(uri: string): string {
|
||||
try {
|
||||
// Handle RTSP URLs with user:pass@host format
|
||||
// Use greedy match for password to handle passwords with @
|
||||
const rtspMatch = uri.match(/rtsp:\/\/([^:]+):(.+)@(.+)/);
|
||||
const rtspMatch = uri.match(/rtsp:\/\/([^:]+):([^@]+)@(.+)/);
|
||||
if (rtspMatch) {
|
||||
return `rtsp://${rtspMatch[1]}:${"*".repeat(4)}@${rtspMatch[3]}`;
|
||||
}
|
||||
|
||||
@ -266,10 +266,7 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
const keys = Object.keys(dataset.categories).filter(
|
||||
(key) => key != "none" && key.toLowerCase() != "unknown",
|
||||
);
|
||||
|
||||
const keys = Object.keys(dataset.categories).filter((key) => key != "none");
|
||||
if (keys.length === 0) {
|
||||
return undefined;
|
||||
}
|
||||
|
||||
@ -75,7 +75,6 @@ import SearchDetailDialog, {
|
||||
} from "@/components/overlay/detail/SearchDetailDialog";
|
||||
import { SearchResult } from "@/types/search";
|
||||
import { HiSparkles } from "react-icons/hi";
|
||||
import { capitalizeFirstLetter } from "@/utils/stringUtil";
|
||||
|
||||
type ModelTrainingViewProps = {
|
||||
model: CustomClassificationModelConfig;
|
||||
@ -89,7 +88,7 @@ export default function ModelTrainingView({ model }: ModelTrainingViewProps) {
|
||||
// title
|
||||
|
||||
useEffect(() => {
|
||||
document.title = `${capitalizeFirstLetter(model.name)} - ${t("documentTitle")}`;
|
||||
document.title = `${model.name.toUpperCase()} - ${t("documentTitle")}`;
|
||||
}, [model.name, t]);
|
||||
|
||||
// model state
|
||||
|
||||
@ -447,7 +447,7 @@ export default function LiveDashboardView({
|
||||
)}
|
||||
|
||||
{cameras.length == 0 && !includeBirdseye ? (
|
||||
<NoCameraView cameraGroup={cameraGroup} />
|
||||
<NoCameraView />
|
||||
) : (
|
||||
<>
|
||||
{!fullscreen && events && events.length > 0 && (
|
||||
@ -666,39 +666,28 @@ export default function LiveDashboardView({
|
||||
);
|
||||
}
|
||||
|
||||
function NoCameraView({ cameraGroup }: { cameraGroup?: string }) {
|
||||
function NoCameraView() {
|
||||
const { t } = useTranslation(["views/live"]);
|
||||
const { auth } = useContext(AuthContext);
|
||||
const isAdmin = useIsAdmin();
|
||||
|
||||
const isDefault = cameraGroup === "default";
|
||||
// Check if this is a restricted user with no cameras in this group
|
||||
const isRestricted = !isAdmin && auth.isAuthenticated;
|
||||
|
||||
let type: "default" | "group" | "restricted";
|
||||
if (isRestricted) {
|
||||
type = "restricted";
|
||||
} else if (isDefault) {
|
||||
type = "default";
|
||||
} else {
|
||||
type = "group";
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="flex size-full items-center justify-center">
|
||||
<EmptyCard
|
||||
icon={<BsFillCameraVideoOffFill className="size-8" />}
|
||||
title={t(`noCameras.${type}.title`)}
|
||||
description={t(`noCameras.${type}.description`)}
|
||||
buttonText={
|
||||
type !== "restricted" && isDefault
|
||||
? t(`noCameras.${type}.buttonText`)
|
||||
: undefined
|
||||
title={
|
||||
isRestricted ? t("noCameras.restricted.title") : t("noCameras.title")
|
||||
}
|
||||
link={
|
||||
type !== "restricted" && isDefault
|
||||
? "/settings?page=cameraManagement"
|
||||
: undefined
|
||||
description={
|
||||
isRestricted
|
||||
? t("noCameras.restricted.description")
|
||||
: t("noCameras.description")
|
||||
}
|
||||
buttonText={!isRestricted ? t("noCameras.buttonText") : undefined}
|
||||
link={!isRestricted ? "/settings?page=cameraManagement" : undefined}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
import Heading from "@/components/ui/heading";
|
||||
import { useCallback, useEffect, useMemo, useState } from "react";
|
||||
import { Toaster } from "@/components/ui/sonner";
|
||||
import { Toaster } from "sonner";
|
||||
import { Button } from "@/components/ui/button";
|
||||
import useSWR from "swr";
|
||||
import { FrigateConfig } from "@/types/frigateConfig";
|
||||
|
||||
@ -1,7 +1,6 @@
|
||||
import Heading from "@/components/ui/heading";
|
||||
import { useCallback, useContext, useEffect, useMemo, useState } from "react";
|
||||
import { toast } from "sonner";
|
||||
import { Toaster } from "@/components/ui/sonner";
|
||||
import { Toaster, toast } from "sonner";
|
||||
import {
|
||||
Form,
|
||||
FormControl,
|
||||
@ -159,12 +158,11 @@ export default function CameraReviewSettingsView({
|
||||
});
|
||||
}
|
||||
setChangedValue(true);
|
||||
setUnsavedChanges(true);
|
||||
setSelectDetections(isChecked as boolean);
|
||||
},
|
||||
// we know that these deps are correct
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
[watchedAlertsZones, setUnsavedChanges],
|
||||
[watchedAlertsZones],
|
||||
);
|
||||
|
||||
const saveToConfig = useCallback(
|
||||
@ -199,8 +197,6 @@ export default function CameraReviewSettingsView({
|
||||
position: "top-center",
|
||||
},
|
||||
);
|
||||
setChangedValue(false);
|
||||
setUnsavedChanges(false);
|
||||
updateConfig();
|
||||
} else {
|
||||
toast.error(
|
||||
@ -233,14 +229,7 @@ export default function CameraReviewSettingsView({
|
||||
setIsLoading(false);
|
||||
});
|
||||
},
|
||||
[
|
||||
updateConfig,
|
||||
setIsLoading,
|
||||
selectedCamera,
|
||||
cameraConfig,
|
||||
t,
|
||||
setUnsavedChanges,
|
||||
],
|
||||
[updateConfig, setIsLoading, selectedCamera, cameraConfig, t],
|
||||
);
|
||||
|
||||
const onCancel = useCallback(() => {
|
||||
@ -506,7 +495,6 @@ export default function CameraReviewSettingsView({
|
||||
)}
|
||||
onCheckedChange={(checked) => {
|
||||
setChangedValue(true);
|
||||
setUnsavedChanges(true);
|
||||
return checked
|
||||
? field.onChange([
|
||||
...field.value,
|
||||
@ -612,8 +600,6 @@ export default function CameraReviewSettingsView({
|
||||
zone.name,
|
||||
)}
|
||||
onCheckedChange={(checked) => {
|
||||
setChangedValue(true);
|
||||
setUnsavedChanges(true);
|
||||
return checked
|
||||
? field.onChange([
|
||||
...field.value,
|
||||
@ -713,6 +699,7 @@ export default function CameraReviewSettingsView({
|
||||
)}
|
||||
/>
|
||||
</div>
|
||||
<Separator className="my-2 flex bg-secondary" />
|
||||
|
||||
<div className="flex w-full flex-row items-center gap-2 pt-2 md:w-[25%]">
|
||||
<Button
|
||||
@ -725,7 +712,7 @@ export default function CameraReviewSettingsView({
|
||||
</Button>
|
||||
<Button
|
||||
variant="select"
|
||||
disabled={!changedValue || isLoading}
|
||||
disabled={isLoading}
|
||||
className="flex flex-1"
|
||||
aria-label={t("button.save", { ns: "common" })}
|
||||
type="submit"
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
import Heading from "@/components/ui/heading";
|
||||
import { Label } from "@/components/ui/label";
|
||||
import { useCallback, useContext, useEffect, useState } from "react";
|
||||
import { Toaster } from "@/components/ui/sonner";
|
||||
import { Toaster } from "sonner";
|
||||
import { Separator } from "../../components/ui/separator";
|
||||
import ActivityIndicator from "@/components/indicators/activity-indicator";
|
||||
import { toast } from "sonner";
|
||||
|
||||
@ -1,7 +1,6 @@
|
||||
import { useCallback, useEffect, useMemo, useState } from "react";
|
||||
import { Trans, useTranslation } from "react-i18next";
|
||||
import { toast } from "sonner";
|
||||
import { Toaster } from "@/components/ui/sonner";
|
||||
import { Toaster, toast } from "sonner";
|
||||
import useSWR from "swr";
|
||||
import axios from "axios";
|
||||
import { Button } from "@/components/ui/button";
|
||||
@ -599,7 +598,7 @@ export default function TriggerView({
|
||||
date_style: "medium",
|
||||
},
|
||||
)
|
||||
: t("never", { ns: "common" })}
|
||||
: "Never"}
|
||||
</span>
|
||||
{trigger_status?.triggers[trigger.name]
|
||||
?.triggering_event_id && (
|
||||
@ -664,7 +663,7 @@ export default function TriggerView({
|
||||
<TableHeader className="sticky top-0 bg-muted/50">
|
||||
<TableRow>
|
||||
<TableHead className="w-4"></TableHead>
|
||||
<TableHead>{t("triggers.table.name")}</TableHead>
|
||||
<TableHead>{t("name", { ns: "common" })}</TableHead>
|
||||
<TableHead>{t("triggers.table.type")}</TableHead>
|
||||
<TableHead>
|
||||
{t("triggers.table.lastTriggered")}
|
||||
@ -760,7 +759,7 @@ export default function TriggerView({
|
||||
date_style: "medium",
|
||||
},
|
||||
)
|
||||
: t("time.never", { ns: "common" })}
|
||||
: "Never"}
|
||||
</span>
|
||||
{trigger_status?.triggers[trigger.name]
|
||||
?.triggering_event_id && (
|
||||
|
||||
@ -2,7 +2,7 @@ import Heading from "@/components/ui/heading";
|
||||
import { Label } from "@/components/ui/label";
|
||||
import { Switch } from "@/components/ui/switch";
|
||||
import { useCallback, useContext, useEffect } from "react";
|
||||
import { Toaster } from "@/components/ui/sonner";
|
||||
import { Toaster } from "sonner";
|
||||
import { toast } from "sonner";
|
||||
import { Separator } from "../../components/ui/separator";
|
||||
import { Button } from "../../components/ui/button";
|
||||
|
||||
Loading…
Reference in New Issue
Block a user