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Author SHA1 Message Date
Josh Hawkins
ee7970e83a
Merge 11bb9fed4c into a182385618 2026-04-29 14:43:38 +00:00
Nicolas Mowen
11bb9fed4c Fix llama.cpp media marker 2026-04-29 08:43:32 -06:00
Nicolas Mowen
a182385618
Fix ROCm build (#23040)
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2026-04-29 09:30:16 -05:00
Josh Hawkins
3201985359 docs tweak 2026-04-29 09:26:51 -05:00
Josh Hawkins
914941090b ensure recording staleness threshold scales with segment_time 2026-04-29 08:42:57 -05:00
Nicolas Mowen
088e1ad7ef
Add ability to download case as zip (#23034)
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2026-04-28 19:11:41 -05:00
6 changed files with 249 additions and 57 deletions

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@ -32,11 +32,14 @@ RUN echo /opt/rocm/lib|tee /opt/rocm-dist/etc/ld.so.conf.d/rocm.conf
FROM deps AS deps-prelim
COPY docker/rocm/debian-backports.sources /etc/apt/sources.list.d/debian-backports.sources
RUN apt-get update && \
# install_deps.sh upgraded libstdc++6 from trixie for Battlemage; the matching
# -dev package must also come from trixie or apt refuses to satisfy it.
RUN echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list && \
apt-get update && \
apt-get install -y libnuma1 && \
apt-get install -qq -y -t bookworm-backports mesa-va-drivers mesa-vulkan-drivers && \
# Install C++ standard library headers for HIPRTC kernel compilation fallback
apt-get install -qq -y libstdc++-12-dev && \
apt-get install -qq -y -t trixie libstdc++-14-dev && \
rm -f /etc/apt/sources.list.d/trixie.list && \
rm -rf /var/lib/apt/lists/*
WORKDIR /opt/frigate

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@ -171,7 +171,7 @@ When choosing images to include in the face training set it is recommended to al
- If it is difficult to make out details in a persons face it will not be helpful in training.
- Avoid images with extreme under/over-exposure.
- Avoid blurry / pixelated images.
- Avoid training on infrared (gray-scale). The models are trained on color images and will be able to extract features from gray-scale images.
- Avoid training on infrared (gray-scale). The models are trained on color images and will not be able to extract features from gray-scale images.
- Using images of people wearing hats / sunglasses may confuse the model.
- Do not upload too many similar images at the same time, it is recommended to train no more than 4-6 similar images for each person to avoid over-fitting.

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@ -5,13 +5,15 @@ import logging
import random
import string
import time
import zipfile
from collections import deque
from pathlib import Path
from typing import List, Optional
from typing import Iterator, List, Optional
import psutil
from fastapi import APIRouter, Depends, Query, Request
from fastapi.responses import JSONResponse
from pathvalidate import sanitize_filepath
from fastapi.responses import JSONResponse, StreamingResponse
from pathvalidate import sanitize_filename, sanitize_filepath
from peewee import DoesNotExist
from playhouse.shortcuts import model_to_dict
@ -361,6 +363,136 @@ def get_export_case(case_id: str):
)
_ZIP_STREAM_CHUNK_SIZE = 1024 * 1024 # 1 MiB
class _StreamingZipBuffer:
"""File-like sink for ZipFile that exposes written bytes via drain().
ZipFile writes synchronously into this buffer; the generator drains the
queue between writes so StreamingResponse can yield bytes without
materializing the whole archive in memory.
"""
def __init__(self) -> None:
self._queue: deque[bytes] = deque()
self._offset = 0
def write(self, data: bytes) -> int:
if data:
self._queue.append(bytes(data))
self._offset += len(data)
return len(data)
def tell(self) -> int:
return self._offset
def flush(self) -> None:
pass
def drain(self) -> Iterator[bytes]:
while self._queue:
yield self._queue.popleft()
def _unique_archive_name(export: Export, used: set[str]) -> str:
base = sanitize_filename(export.name) if export.name else None
if not base:
base = f"{export.camera}_{int(datetime.datetime.timestamp(export.date))}"
candidate = f"{base}.mp4"
counter = 1
while candidate in used:
candidate = f"{base}_{counter}.mp4"
counter += 1
used.add(candidate)
return candidate
def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
"""Yield bytes of a zip archive built from the given exports' mp4 files."""
buffer = _StreamingZipBuffer()
used_names: set[str] = set()
# ZIP_STORED: mp4 is already compressed, recompressing wastes CPU for ~0% size win.
with zipfile.ZipFile(
buffer,
mode="w",
compression=zipfile.ZIP_STORED,
allowZip64=True,
) as archive:
for export in exports:
source = Path(export.video_path)
if not source.exists():
continue
arcname = _unique_archive_name(export, used_names)
with (
archive.open(arcname, mode="w", force_zip64=True) as entry,
source.open("rb") as src,
):
while True:
chunk = src.read(_ZIP_STREAM_CHUNK_SIZE)
if not chunk:
break
entry.write(chunk)
yield from buffer.drain()
yield from buffer.drain()
yield from buffer.drain()
@router.get(
"/cases/{case_id}/download",
dependencies=[Depends(allow_any_authenticated())],
summary="Download export case as zip",
description="Streams a zip archive containing every completed export's mp4 for the given case.",
)
def download_export_case(
case_id: str,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
):
try:
case = ExportCase.get(ExportCase.id == case_id)
except DoesNotExist:
return JSONResponse(
content={"success": False, "message": "Export case not found"},
status_code=404,
)
exports = list(
Export.select()
.where(
Export.export_case == case_id,
~Export.in_progress,
Export.camera << allowed_cameras,
)
.order_by(Export.date.asc())
)
if not exports:
return JSONResponse(
content={"success": False, "message": "No exports available to download."},
status_code=404,
)
archive_base = sanitize_filename(case.name) if case.name else ""
if not archive_base:
archive_base = case_id
return StreamingResponse(
_stream_case_archive(exports),
media_type="application/zip",
headers={
"Content-Disposition": f'attachment; filename="{archive_base}.zip"',
},
)
@router.patch(
"/cases/{case_id}",
response_model=GenericResponse,

View File

@ -44,6 +44,7 @@ class LlamaCppClient(GenAIClient):
_supports_tools: bool
_image_token_cache: dict[tuple[int, int], int]
_text_baseline_tokens: int | None
_media_marker: str
def _init_provider(self) -> str | None:
"""Initialize the client and query model metadata from the server."""
@ -56,6 +57,7 @@ class LlamaCppClient(GenAIClient):
self._supports_tools = False
self._image_token_cache = {}
self._text_baseline_tokens = None
self._media_marker = "<__media__>"
base_url = (
self.genai_config.base_url.rstrip("/")
@ -141,6 +143,13 @@ class LlamaCppClient(GenAIClient):
chat_caps = props.get("chat_template_caps", {})
self._supports_tools = chat_caps.get("supports_tools", False)
# Media marker for multimodal embeddings; the server randomizes this
# per startup unless LLAMA_MEDIA_MARKER is set, so we must read it
# from /props rather than hardcoding "<__media__>".
media_marker = props.get("media_marker")
if isinstance(media_marker, str) and media_marker:
self._media_marker = media_marker
logger.info(
"llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s",
configured_model,
@ -465,10 +474,11 @@ class LlamaCppClient(GenAIClient):
jpeg_bytes = _to_jpeg(img)
to_encode = jpeg_bytes if jpeg_bytes is not None else img
encoded = base64.b64encode(to_encode).decode("utf-8")
# prompt_string must contain <__media__> placeholder for image tokenization
# prompt_string must contain the server's media marker placeholder.
# The marker is randomized per server startup (read from /props).
content.append(
{
"prompt_string": "<__media__>\n",
"prompt_string": f"{self._media_marker}\n",
"multimodal_data": [encoded], # type: ignore[dict-item]
}
)

View File

@ -24,7 +24,7 @@ from frigate.config.camera.updater import (
)
from frigate.const import PROCESS_PRIORITY_HIGH
from frigate.log import LogPipe
from frigate.util.builtin import EventsPerSecond
from frigate.util.builtin import EventsPerSecond, get_ffmpeg_arg_list
from frigate.util.ffmpeg import start_or_restart_ffmpeg, stop_ffmpeg
from frigate.util.image import (
FrameManager,
@ -34,6 +34,23 @@ from frigate.util.process import FrigateProcess
logger = logging.getLogger(__name__)
# all built-in record presets use this segment_time
DEFAULT_RECORD_SEGMENT_TIME = 10
def _get_record_segment_time(config: CameraConfig) -> int:
"""Extract -segment_time from the camera's record output args."""
record_args = get_ffmpeg_arg_list(config.ffmpeg.output_args.record)
if record_args and record_args[0].startswith("preset"):
return DEFAULT_RECORD_SEGMENT_TIME
try:
idx = record_args.index("-segment_time")
return int(record_args[idx + 1])
except (ValueError, IndexError):
return DEFAULT_RECORD_SEGMENT_TIME
def capture_frames(
ffmpeg_process: sp.Popen[Any],
@ -164,6 +181,12 @@ class CameraWatchdog(threading.Thread):
self.latest_cache_segment_time: float = 0
self.record_enable_time: datetime | None = None
# `valid` segments are published with the segment's start time, so the
# gap between consecutive publishes can reach 2 * segment_time. Pad the
# staleness threshold so it's never tighter than that worst case.
segment_time = _get_record_segment_time(self.config)
self.record_stale_threshold = max(120, 2 * segment_time + 30)
# Stall tracking (based on last processed frame)
self._stall_timestamps: deque[float] = deque()
self._stall_active: bool = False
@ -413,16 +436,17 @@ class CameraWatchdog(threading.Thread):
# ensure segments are still being created and that they have valid video data
# Skip checks during grace period to allow segments to start being created
stale_window = timedelta(seconds=self.record_stale_threshold)
cache_stale = not in_grace_period and now_utc > (
latest_cache_dt + timedelta(seconds=120)
latest_cache_dt + stale_window
)
valid_stale = not in_grace_period and now_utc > (
latest_valid_dt + timedelta(seconds=120)
latest_valid_dt + stale_window
)
invalid_stale_condition = (
self.latest_invalid_segment_time > 0
and not in_grace_period
and now_utc > (latest_invalid_dt + timedelta(seconds=120))
and now_utc > (latest_invalid_dt + stale_window)
and self.latest_valid_segment_time
<= self.latest_invalid_segment_time
)
@ -439,7 +463,7 @@ class CameraWatchdog(threading.Thread):
)
self.logger.error(
f"{reason} for {self.config.name} in the last 120s. Restarting the ffmpeg record process..."
f"{reason} for {self.config.name} in the last {self.record_stale_threshold}s. Restarting the ffmpeg record process..."
)
p["process"] = start_or_restart_ffmpeg(
p["cmd"],

View File

@ -57,6 +57,7 @@ import { useTranslation } from "react-i18next";
import { IoMdArrowRoundBack } from "react-icons/io";
import {
LuDownload,
LuFolderPlus,
LuFolderX,
LuPencil,
@ -777,54 +778,76 @@ function Exports() {
filters={["cameras"]}
onUpdateFilter={setExportFilter}
/>
{isAdmin && (
<div className="flex items-center gap-1 md:gap-2">
<div className="flex items-center gap-1 md:gap-2">
{(exportsByCase[selectedCase.id]?.length ?? 0) > 0 && (
<Button
asChild
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.addExport")}
onClick={() => setCaseForAddExport(selectedCase)}
aria-label={t("button.download", { ns: "common" })}
>
<LuPlus className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.addExport")}
</div>
)}
<a
download
href={`${baseUrl}api/cases/${selectedCase.id}/download`}
>
<LuDownload className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("button.download", { ns: "common" })}
</div>
)}
</a>
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.editCase")}
onClick={() =>
setCaseDialog({
mode: "edit",
exportCase: selectedCase,
})
}
>
<LuPencil className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.editCase")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.deleteCase")}
onClick={() => setCaseToDelete(selectedCase)}
>
<LuTrash2 className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.deleteCase")}
</div>
)}
</Button>
</div>
)}
)}
{isAdmin && (
<>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.addExport")}
onClick={() => setCaseForAddExport(selectedCase)}
>
<LuPlus className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.addExport")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.editCase")}
onClick={() =>
setCaseDialog({
mode: "edit",
exportCase: selectedCase,
})
}
>
<LuPencil className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.editCase")}
</div>
)}
</Button>
<Button
className="flex items-center gap-2 p-2"
size="sm"
aria-label={t("toolbar.deleteCase")}
onClick={() => setCaseToDelete(selectedCase)}
>
<LuTrash2 className="text-secondary-foreground" />
{!isMobile && (
<div className="text-primary">
{t("toolbar.deleteCase")}
</div>
)}
</Button>
</>
)}
</div>
</div>
)}
</>