Merge 11bb9fed4c into a182385618

docker/rocm/Dockerfile

@@ -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 -t trixie libstdc++-14-dev && \
-    apt-get install -qq -y libstdc++-12-dev && \
+    rm -f /etc/apt/sources.list.d/trixie.list && \
     rm -rf /var/lib/apt/lists/*
 
 WORKDIR /opt/frigate

docs/docs/configuration/face_recognition.md

@@ -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.
 

frigate/api/export.py

@@ -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 fastapi.responses import JSONResponse, StreamingResponse
-from pathvalidate import sanitize_filepath
+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,

frigate/genai/llama_cpp.py

@@ -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]
                 }
             )

frigate/video/ffmpeg.py

@@ -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"],

web/src/pages/Exports.tsx

@@ -57,6 +57,7 @@ import { useTranslation } from "react-i18next";
 
 import { IoMdArrowRoundBack } from "react-icons/io";
 import {
+  LuDownload,
   LuFolderPlus,
   LuFolderX,
   LuPencil,
@@ -777,8 +778,29 @@ function Exports() {
                   filters={["cameras"]}
                   onUpdateFilter={setExportFilter}
                 />
-                {isAdmin && (
                 <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("button.download", { ns: "common" })}
+                    >
+                      <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>
+                  )}
+                  {isAdmin && (
+                    <>
                       <Button
                         className="flex items-center gap-2 p-2"
                         size="sm"
@@ -823,9 +845,10 @@ function Exports() {
                           </div>
                         )}
                       </Button>
-                  </div>
+                    </>
                   )}
                 </div>
+              </div>
             )}
           </>
         )}