mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-02-02 01:05:20 +03:00
return to Python 3.8
This commit is contained in:
YS
parent
6ad981358e
commit
86af2a5615
@ -1,7 +1,6 @@
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import json
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import logging
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import multiprocessing as mp
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import shared_memory
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import os
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import signal
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import sys
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@ -42,7 +41,7 @@ class FrigateApp:
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self.detection_queue = mp.Queue()
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self.detectors: Dict[str, EdgeTPUProcess] = {}
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self.detection_out_events: Dict[str, mp.Event] = {}
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self.detection_shms: List[shared_memory.SharedMemory] = []
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self.detection_shms: List[mp.shared_memory.SharedMemory] = []
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self.log_queue = mp.Queue()
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self.camera_metrics = {}
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@ -164,20 +163,20 @@ class FrigateApp:
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self.detection_out_events[name] = mp.Event()
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try:
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shm_in = shared_memory.SharedMemory(
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shm_in = mp.shared_memory.SharedMemory(
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name=name,
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create=True,
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size=self.config.model.height * self.config.model.width * 3,
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)
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except FileExistsError:
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shm_in = shared_memory.SharedMemory(name=name)
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shm_in = mp.shared_memory.SharedMemory(name=name)
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try:
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shm_out = shared_memory.SharedMemory(
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shm_out = mp.shared_memory.SharedMemory(
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name=f"out-{name}", create=True, size=20 * 6 * 4
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)
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except FileExistsError:
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shm_out = shared_memory.SharedMemory(name=f"out-{name}")
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shm_out = mp.shared_memory.SharedMemory(name=f"out-{name}")
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self.detection_shms.append(shm_in)
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self.detection_shms.append(shm_out)
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@ -1,3 +1,5 @@
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from __future__ import annotations
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import json
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import logging
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import os
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@ -20,8 +22,7 @@ DEFAULT_TIME_FORMAT = "%m/%d/%Y %H:%M:%S"
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# German Style:
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# DEFAULT_TIME_FORMAT = "%d.%m.%Y %H:%M:%S"
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FRIGATE_ENV_VARS = {k: v for k,
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v in os.environ.items() if k.startswith("FRIGATE_")}
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FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
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DEFAULT_TRACKED_OBJECTS = ["person"]
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DEFAULT_DETECTORS = {"cpu": {"type": "cpu"}}
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@ -38,8 +39,7 @@ class DetectorTypeEnum(str, Enum):
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class DetectorConfig(FrigateBaseModel):
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type: DetectorTypeEnum = Field(
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default=DetectorTypeEnum.cpu, title="Detector Type")
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type: DetectorTypeEnum = Field(default=DetectorTypeEnum.cpu, title="Detector Type")
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device: str = Field(default="usb", title="Device Type")
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num_threads: int = Field(default=3, title="Number of detection threads")
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@ -82,10 +82,8 @@ class RetainConfig(FrigateBaseModel):
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class EventsConfig(FrigateBaseModel):
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max_seconds: int = Field(default=300, title="Maximum event duration.")
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pre_capture: int = Field(
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default=5, title="Seconds to retain before event starts.")
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post_capture: int = Field(
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default=5, title="Seconds to retain after event ends.")
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pre_capture: int = Field(default=5, title="Seconds to retain before event starts.")
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post_capture: int = Field(default=5, title="Seconds to retain after event ends.")
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required_zones: List[str] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to save the event.",
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@ -163,10 +161,8 @@ class RuntimeMotionConfig(MotionConfig):
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class DetectConfig(FrigateBaseModel):
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height: int = Field(
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default=720, title="Height of the stream for the detect role.")
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width: int = Field(
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default=1280, title="Width of the stream for the detect role.")
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height: int = Field(default=720, title="Height of the stream for the detect role.")
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width: int = Field(default=1280, title="Width of the stream for the detect role.")
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fps: int = Field(
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default=5, title="Number of frames per second to process through detection."
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)
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@ -208,8 +204,7 @@ class RuntimeFilterConfig(FilterConfig):
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config["raw_mask"] = mask
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if mask is not None:
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config["mask"] = create_mask(
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config.get("frame_shape", (1, 1)), mask)
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config["mask"] = create_mask(config.get("frame_shape", (1, 1)), mask)
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super().__init__(**config)
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@ -256,22 +251,19 @@ class ZoneConfig(BaseModel):
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if isinstance(coordinates, list):
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self._contour = np.array(
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[[int(p.split(",")[0]), int(p.split(",")[1])]
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for p in coordinates]
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[[int(p.split(",")[0]), int(p.split(",")[1])] for p in coordinates]
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)
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elif isinstance(coordinates, str):
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points = coordinates.split(",")
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self._contour = np.array(
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[[int(points[i]), int(points[i + 1])]
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for i in range(0, len(points), 2)]
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[[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)]
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)
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else:
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self._contour = np.array([])
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class ObjectConfig(FrigateBaseModel):
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track: List[str] = Field(
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default=DEFAULT_TRACKED_OBJECTS, title="Objects to track.")
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track: List[str] = Field(default=DEFAULT_TRACKED_OBJECTS, title="Objects to track.")
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filters: Optional[Dict[str, FilterConfig]] = Field(title="Object filters.")
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mask: Union[str, List[str]] = Field(default="", title="Object mask.")
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@ -362,15 +354,25 @@ class FfmpegConfig(FrigateBaseModel):
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class GstreamerConfig(FrigateBaseModel):
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manual_pipeline: List[str] = Field(
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default=[], title="GStreamer manual pipeline. Use `manual_pipeline` to fine tune gstreamer. Each item will be splited by the `!`.")
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default=[],
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title="GStreamer manual pipeline. Use `manual_pipeline` to fine tune gstreamer. Each item will be splited by the `!`.",
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)
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input_pipeline: List[str] = Field(
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default=[], title="Override the `rtspsrc location={{gstreamer_input.path}} latency=0` default pipeline item.")
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default=[],
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title="Override the `rtspsrc location={{gstreamer_input.path}} latency=0` default pipeline item.",
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)
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decoder_pipeline: List[str] = Field(
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default=[], title="Set the hardware specific decoder. Example: ['rtph265depay', 'h265parse', 'omxh265dec']")
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default=[],
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title="Set the hardware specific decoder. Example: ['rtph265depay', 'h265parse', 'omxh265dec']",
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)
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source_format_pipeline: List[str] = Field(
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default=[], title="Set the camera source format. Default is: ['video/x-raw,format=(string)NV12', 'videoconvert', 'videoscale']")
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default=[],
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title="Set the camera source format. Default is: ['video/x-raw,format=(string)NV12', 'videoconvert', 'videoscale']",
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)
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destination_format_pipeline: List[str] = Field(
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default=[], title="Set the Frigate format. Please keep `format=I420` if override. Default is: ['video/x-raw,width=(int){self.detect.width},height=(int){self.detect.height},format=(string)I420', 'videoconvert']")
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default=[],
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title="Set the Frigate format. Please keep `format=I420` if override. Default is: ['video/x-raw,width=(int){self.detect.width},height=(int){self.detect.height},format=(string)I420', 'videoconvert']",
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)
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class CameraRoleEnum(str, Enum):
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@ -398,7 +400,8 @@ class CameraFFmpegInput(CameraInput):
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class CameraGStreamerInput(CameraInput):
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pipeline: List[str] = Field(
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default=[], title="GStreamer pipeline. Each pipeline will be splited by ! sign")
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default=[], title="GStreamer pipeline. Each pipeline will be splited by ! sign"
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)
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class CameraInputValidator:
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@ -421,8 +424,7 @@ class CameraFfmpegConfig(FfmpegConfig, CameraInputValidator):
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class CameraGStreamerConfig(GstreamerConfig, CameraInputValidator):
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inputs: List[CameraGStreamerInput] = Field(
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title="Camera GStreamer inputs.")
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inputs: List[CameraGStreamerInput] = Field(title="Camera GStreamer inputs.")
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class SnapshotsConfig(FrigateBaseModel):
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@ -436,8 +438,7 @@ class SnapshotsConfig(FrigateBaseModel):
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bounding_box: bool = Field(
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default=True, title="Add a bounding box overlay on the snapshot."
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)
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crop: bool = Field(
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default=False, title="Crop the snapshot to the detected object.")
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crop: bool = Field(default=False, title="Crop the snapshot to the detected object.")
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required_zones: List[str] = Field(
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default_factory=list,
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title="List of required zones to be entered in order to save a snapshot.",
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@ -477,8 +478,7 @@ class TimestampStyleConfig(FrigateBaseModel):
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default=TimestampPositionEnum.tl, title="Timestamp position."
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)
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format: str = Field(default=DEFAULT_TIME_FORMAT, title="Timestamp format.")
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color: ColorConfig = Field(
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default_factory=ColorConfig, title="Timestamp color.")
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color: ColorConfig = Field(default_factory=ColorConfig, title="Timestamp color.")
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thickness: int = Field(default=2, title="Timestamp thickness.")
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effect: Optional[TimestampEffectEnum] = Field(title="Timestamp effect.")
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@ -486,10 +486,8 @@ class TimestampStyleConfig(FrigateBaseModel):
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class CameraMqttConfig(FrigateBaseModel):
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enabled: bool = Field(default=True, title="Send image over MQTT.")
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timestamp: bool = Field(default=True, title="Add timestamp to MQTT image.")
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bounding_box: bool = Field(
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default=True, title="Add bounding box to MQTT image.")
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crop: bool = Field(
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default=True, title="Crop MQTT image to detected object.")
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bounding_box: bool = Field(default=True, title="Add bounding box to MQTT image.")
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crop: bool = Field(default=True, title="Crop MQTT image to detected object.")
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height: int = Field(default=270, title="MQTT image height.")
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required_zones: List[str] = Field(
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default_factory=list,
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@ -509,16 +507,17 @@ class RtmpConfig(FrigateBaseModel):
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class CameraLiveConfig(FrigateBaseModel):
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height: int = Field(default=720, title="Live camera view height")
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quality: int = Field(default=8, ge=1, le=31,
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title="Live camera view quality")
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quality: int = Field(default=8, ge=1, le=31, title="Live camera view quality")
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class CameraConfig(FrigateBaseModel):
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name: Optional[str] = Field(title="Camera name.")
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ffmpeg: Optional[CameraFfmpegConfig] = Field(
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title="FFmpeg configuration for the camera.")
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title="FFmpeg configuration for the camera."
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)
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gstreamer: Optional[CameraGStreamerConfig] = Field(
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title="GStreamer configuration for the camera.")
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title="GStreamer configuration for the camera."
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)
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best_image_timeout: int = Field(
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default=60,
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title="How long to wait for the image with the highest confidence score.",
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@ -544,8 +543,7 @@ class CameraConfig(FrigateBaseModel):
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objects: ObjectConfig = Field(
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default_factory=ObjectConfig, title="Object configuration."
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)
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motion: Optional[MotionConfig] = Field(
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title="Motion detection configuration.")
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motion: Optional[MotionConfig] = Field(title="Motion detection configuration.")
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detect: DetectConfig = Field(
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default_factory=DetectConfig, title="Object detection configuration."
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)
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@ -559,16 +557,14 @@ class CameraConfig(FrigateBaseModel):
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if "zones" in config:
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colors = plt.cm.get_cmap("tab10", len(config["zones"]))
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config["zones"] = {
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name: {**z, "color": tuple(round(255 * c)
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for c in colors(idx)[:3])}
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name: {**z, "color": tuple(round(255 * c) for c in colors(idx)[:3])}
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for idx, (name, z) in enumerate(config["zones"].items())
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}
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# add roles to the input if there is only one
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if "ffmpeg" in config:
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if len(config["ffmpeg"]["inputs"]) == 1:
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config["ffmpeg"]["inputs"][0]["roles"] = [
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"record", "rtmp", "detect"]
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config["ffmpeg"]["inputs"][0]["roles"] = ["record", "rtmp", "detect"]
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super().__init__(**config)
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@ -593,7 +589,8 @@ class CameraConfig(FrigateBaseModel):
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continue
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decoder_cmds.append(
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{"roles": gstreamer_input.roles, "cmd": decoder_cmd})
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{"roles": gstreamer_input.roles, "cmd": decoder_cmd}
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)
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return decoder_cmds
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@ -611,63 +608,75 @@ class CameraConfig(FrigateBaseModel):
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def _get_gstreamer_cmd(self, gstreamer_input: CameraGStreamerInput):
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assert list(
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["detect"]) == gstreamer_input.roles, "only detect role is supported"
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assert (
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list(["detect"]) == gstreamer_input.roles
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), "only detect role is supported"
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manual_pipeline = [
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part for part in self.gstreamer.manual_pipeline if part != ""]
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input_pipeline = [
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part for part in self.gstreamer.input_pipeline if part != ""]
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part for part in self.gstreamer.manual_pipeline if part != ""
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]
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input_pipeline = [part for part in self.gstreamer.input_pipeline if part != ""]
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decoder_pipeline = [
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part for part in self.gstreamer.decoder_pipeline if part != ""]
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part for part in self.gstreamer.decoder_pipeline if part != ""
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]
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source_format_pipeline = [
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part for part in self.gstreamer.source_format_pipeline if part != ""]
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part for part in self.gstreamer.source_format_pipeline if part != ""
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]
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destination_format_pipeline = [
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part for part in self.gstreamer.destination_format_pipeline if part != ""]
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part for part in self.gstreamer.destination_format_pipeline if part != ""
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]
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video_format = f"video/x-raw,width=(int){self.detect.width},height=(int){self.detect.height},format=(string)I420"
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if not manual_pipeline and not input_pipeline and not decoder_pipeline and not source_format_pipeline and not destination_format_pipeline:
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if (
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not manual_pipeline
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and not input_pipeline
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and not decoder_pipeline
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and not source_format_pipeline
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and not destination_format_pipeline
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):
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logger.warn(
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"gsreamer pipeline not configured. Using videotestsrc pattern=0")
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"gsreamer pipeline not configured. Using videotestsrc pattern=0"
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)
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pipeline = [
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"videotestsrc pattern=0",
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video_format,
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]
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elif len(manual_pipeline) > 0:
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logger.warn(
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"gsreamer manual pipeline is set. Please make sure your detect width and height does math the gstreamer parameters")
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"gsreamer manual pipeline is set. Please make sure your detect width and height does math the gstreamer parameters"
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)
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pipeline = manual_pipeline
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else:
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input_pipeline = input_pipeline if input_pipeline else [
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f"rtspsrc location=\"{gstreamer_input.path}\" latency=0"
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]
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input_pipeline = (
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input_pipeline
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if input_pipeline
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else [f'rtspsrc location="{gstreamer_input.path}" latency=0']
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)
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decoder_pipeline = decoder_pipeline if decoder_pipeline else [
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"rtph265depay", "h265parse", "omxh265dec"
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]
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source_format_pipeline = source_format_pipeline if source_format_pipeline else [
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'video/x-raw,format=(string)NV12', 'videoconvert', 'videoscale'
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]
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destination_format_pipeline = destination_format_pipeline if destination_format_pipeline else [
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video_format, "videoconvert"
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]
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decoder_pipeline = (
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decoder_pipeline
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if decoder_pipeline
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else ["rtph265depay", "h265parse", "omxh265dec"]
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)
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source_format_pipeline = (
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source_format_pipeline
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if source_format_pipeline
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else ["video/x-raw,format=(string)NV12", "videoconvert", "videoscale"]
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)
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destination_format_pipeline = (
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destination_format_pipeline
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if destination_format_pipeline
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else [video_format, "videoconvert"]
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)
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pipeline = [
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*input_pipeline,
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*decoder_pipeline,
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*source_format_pipeline,
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*destination_format_pipeline
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*destination_format_pipeline,
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]
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pipeline_args = (
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[f"{item} !".split(" ") for item in pipeline]
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)
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pipeline_args = [f"{item} !".split(" ") for item in pipeline]
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pipeline_args = [item for sublist in pipeline_args for item in sublist]
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pipeline_args = [
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"gst-launch-1.0",
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"-q",
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*pipeline_args,
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"fdsink"
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]
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logger.debug(
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f"using gstreamer pipeline: {' '.join(pipeline_args)}")
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pipeline_args = ["gst-launch-1.0", "-q", *pipeline_args, "fdsink"]
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logger.debug(f"using gstreamer pipeline: {' '.join(pipeline_args)}")
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return pipeline_args
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@ -697,8 +706,7 @@ class CameraConfig(FrigateBaseModel):
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else self.ffmpeg.output_args.rtmp.split(" ")
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)
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ffmpeg_output_args = (
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rtmp_args +
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[f"rtmp://127.0.0.1/live/{self.name}"] + ffmpeg_output_args
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rtmp_args + [f"rtmp://127.0.0.1/live/{self.name}"] + ffmpeg_output_args
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)
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if "record" in ffmpeg_input.roles and self.record.enabled:
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record_args = (
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@ -722,16 +730,13 @@ class CameraConfig(FrigateBaseModel):
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input_args = ffmpeg_input.input_args or self.ffmpeg.input_args
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global_args = (
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global_args if isinstance(
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global_args, list) else global_args.split(" ")
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global_args if isinstance(global_args, list) else global_args.split(" ")
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)
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hwaccel_args = (
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hwaccel_args if isinstance(
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hwaccel_args, list) else hwaccel_args.split(" ")
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hwaccel_args if isinstance(hwaccel_args, list) else hwaccel_args.split(" ")
|
||||
)
|
||||
input_args = (
|
||||
input_args if isinstance(
|
||||
input_args, list) else input_args.split(" ")
|
||||
input_args if isinstance(input_args, list) else input_args.split(" ")
|
||||
)
|
||||
|
||||
cmd = (
|
||||
@ -748,7 +753,7 @@ class CameraConfig(FrigateBaseModel):
|
||||
@root_validator
|
||||
def either_ffmpeg_or_gstreamer(cls, v):
|
||||
if ("ffmpeg" not in v) and ("gstreamer" not in v):
|
||||
raise ValueError('either ffmpeg or gstreamer should be set')
|
||||
raise ValueError("either ffmpeg or gstreamer should be set")
|
||||
return v
|
||||
|
||||
|
||||
@ -760,12 +765,9 @@ class DatabaseConfig(FrigateBaseModel):
|
||||
|
||||
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_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."
|
||||
)
|
||||
@ -792,8 +794,7 @@ class ModelConfig(FrigateBaseModel):
|
||||
|
||||
self._colormap = {}
|
||||
for key, val in self._merged_labelmap.items():
|
||||
self._colormap[val] = tuple(int(round(255 * c))
|
||||
for c in cmap(key)[:3])
|
||||
self._colormap[val] = tuple(int(round(255 * c)) for c in cmap(key)[:3])
|
||||
|
||||
|
||||
class LogLevelEnum(str, Enum):
|
||||
@ -825,8 +826,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
default_factory=ModelConfig, title="Detection model configuration."
|
||||
)
|
||||
detectors: Dict[str, DetectorConfig] = Field(
|
||||
default={name: DetectorConfig(**d)
|
||||
for name, d in DEFAULT_DETECTORS.items()},
|
||||
default={name: DetectorConfig(**d) for name, d in DEFAULT_DETECTORS.items()},
|
||||
title="Detector hardware configuration.",
|
||||
)
|
||||
logger: LoggerConfig = Field(
|
||||
@ -872,8 +872,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
|
||||
# MQTT password substitution
|
||||
if config.mqtt.password:
|
||||
config.mqtt.password = config.mqtt.password.format(
|
||||
**FRIGATE_ENV_VARS)
|
||||
config.mqtt.password = config.mqtt.password.format(**FRIGATE_ENV_VARS)
|
||||
|
||||
# Global config to propegate down to camera level
|
||||
global_config = config.dict(
|
||||
@ -892,8 +891,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
)
|
||||
|
||||
for name, camera in config.cameras.items():
|
||||
merged_config = deep_merge(camera.dict(
|
||||
exclude_unset=True), global_config)
|
||||
merged_config = deep_merge(camera.dict(exclude_unset=True), global_config)
|
||||
camera_config: CameraConfig = CameraConfig.parse_obj(
|
||||
{"name": name, **merged_config}
|
||||
)
|
||||
@ -957,7 +955,11 @@ class FrigateConfig(FrigateBaseModel):
|
||||
)
|
||||
|
||||
# check runtime config
|
||||
decoder_config = camera_config.ffmpeg if "ffmpeg" in camera_config else camera_config.gstreamer
|
||||
decoder_config = (
|
||||
camera_config.ffmpeg
|
||||
if "ffmpeg" in camera_config
|
||||
else camera_config.gstreamer
|
||||
)
|
||||
assigned_roles = list(
|
||||
set([r for i in decoder_config.inputs for r in i.roles])
|
||||
)
|
||||
|
||||
@ -7,10 +7,8 @@ import signal
|
||||
import threading
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Dict
|
||||
import shared_memory
|
||||
|
||||
import numpy as np
|
||||
# TensorRT https://github.com/NobuoTsukamoto/tensorrt-examples/blob/main/python/detection/README.md
|
||||
import tflite_runtime.interpreter as tflite
|
||||
from setproctitle import setproctitle
|
||||
from tflite_runtime.interpreter import load_delegate
|
||||
@ -141,7 +139,7 @@ def run_detector(
|
||||
|
||||
outputs = {}
|
||||
for name in out_events.keys():
|
||||
out_shm = shared_memory.SharedMemory(name=f"out-{name}", create=False)
|
||||
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}
|
||||
|
||||
@ -230,11 +228,11 @@ class RemoteObjectDetector:
|
||||
self.fps = EventsPerSecond()
|
||||
self.detection_queue = detection_queue
|
||||
self.event = event
|
||||
self.shm = shared_memory.SharedMemory(name=self.name, create=False)
|
||||
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 = shared_memory.SharedMemory(
|
||||
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)
|
||||
|
||||
@ -610,8 +610,7 @@ def recording_clip(camera, start_ts, end_ts):
|
||||
ffmpeg_cmd,
|
||||
input="\n".join(playlist_lines),
|
||||
encoding="ascii",
|
||||
stdout=sp.PIPE,
|
||||
stderr=sp.PIPE,
|
||||
capture_output=True,
|
||||
)
|
||||
if p.returncode != 0:
|
||||
logger.error(p.stderr)
|
||||
|
||||
@ -7,6 +7,7 @@ import queue
|
||||
import signal
|
||||
import subprocess as sp
|
||||
import threading
|
||||
from multiprocessing import shared_memory
|
||||
from wsgiref.simple_server import make_server
|
||||
from frigate.log import LogPipe
|
||||
|
||||
@ -32,27 +33,20 @@ class FFMpegConverter:
|
||||
ffmpeg_cmd = f"ffmpeg -f rawvideo -pix_fmt yuv420p -video_size {in_width}x{in_height} -i pipe: -f mpegts -s {out_width}x{out_height} -codec:v mpeg1video -q {quality} -bf 0 pipe:".split(
|
||||
" "
|
||||
)
|
||||
# ffmpeg_cmd = f"gst-launch-1.0 rtspsrc location=\"rtsp://admin:123456@192.168.5.95:554/stream0\" ! rtph265depay ! h265parse ! omxh265dec ! 'video/x-raw,format=(string)NV12' ! videoconvert ! 'video/x-raw, width={in_width}, height={in_height}, format=I420, framerate=(fraction)10/1' ! omxh264enc bitrate=500000 temporal-tradeoff=2 iframeinterval=10 ! h264parse ! mpegtsmux ! fdsink"
|
||||
# # .split(
|
||||
# # " "
|
||||
# # )
|
||||
|
||||
self.logpipe = LogPipe(
|
||||
"ffmpeg.converter", logging.ERROR)
|
||||
"ffmpeg.converter", logging.ERROR)
|
||||
self.process = sp.Popen(
|
||||
ffmpeg_cmd,
|
||||
stdout=sp.PIPE,
|
||||
stderr=self.logpipe,
|
||||
stdin=sp.PIPE,
|
||||
start_new_session=True,
|
||||
# shell=True
|
||||
)
|
||||
|
||||
def write(self, b):
|
||||
try:
|
||||
self.process.stdin.write(b)
|
||||
except Exception:
|
||||
logger.error("Failure while writing to the stream:")
|
||||
self.logpipe.dump()
|
||||
return False
|
||||
|
||||
@ -60,7 +54,6 @@ class FFMpegConverter:
|
||||
try:
|
||||
return self.process.stdout.read1(length)
|
||||
except ValueError:
|
||||
logger.error("Failure while readig from the stream:")
|
||||
self.logpipe.dump()
|
||||
return False
|
||||
|
||||
@ -423,13 +416,8 @@ def output_frames(config: FrigateConfig, video_output_queue):
|
||||
if any(
|
||||
ws.environ["PATH_INFO"].endswith(camera) for ws in websocket_server.manager
|
||||
):
|
||||
try:
|
||||
# write to the converter for the camera if clients are listening to the specific camera
|
||||
converters[camera].write(frame.tobytes())
|
||||
except Exception:
|
||||
# in case of videoconverter failure continure processing video_output_queue
|
||||
# FFMpegConverter should dump an error response
|
||||
pass
|
||||
# write to the converter for the camera if clients are listening to the specific camera
|
||||
converters[camera].write(frame.tobytes())
|
||||
|
||||
# update birdseye if websockets are connected
|
||||
if config.birdseye.enabled and any(
|
||||
|
||||
@ -502,9 +502,8 @@ class RecordingCleanup(threading.Thread):
|
||||
logger.debug(f"Oldest recording in the db: {oldest_timestamp}")
|
||||
process = sp.run(
|
||||
["find", RECORD_DIR, "-type", "f", "!", "-newermt", f"@{oldest_timestamp}"],
|
||||
stdout=sp.PIPE,
|
||||
stderr=sp.PIPE,
|
||||
universal_newlines=True,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
)
|
||||
files_to_check = process.stdout.splitlines()
|
||||
|
||||
|
||||
@ -11,8 +11,7 @@ import threading
|
||||
import time
|
||||
import traceback
|
||||
from abc import ABC, abstractmethod
|
||||
#from multiprocessing import shared_memory
|
||||
import shared_memory
|
||||
from multiprocessing import shared_memory
|
||||
from typing import AnyStr
|
||||
|
||||
import cv2
|
||||
|
||||
@ -187,8 +187,7 @@ class CameraWatchdog(threading.Thread):
|
||||
self.config = config
|
||||
self.capture_thread = None
|
||||
self.ffmpeg_detect_process = None
|
||||
self.logpipe = LogPipe(
|
||||
f"ffmpeg.{self.camera_name}.detect", logging.ERROR)
|
||||
self.logpipe = LogPipe(f"ffmpeg.{self.camera_name}.detect", logging.ERROR)
|
||||
self.ffmpeg_other_processes = []
|
||||
self.camera_fps = camera_fps
|
||||
self.ffmpeg_pid = ffmpeg_pid
|
||||
@ -226,8 +225,7 @@ class CameraWatchdog(threading.Thread):
|
||||
self.logger.error(
|
||||
"The following ffmpeg logs include the last 100 lines prior to exit."
|
||||
)
|
||||
self.logger.error(
|
||||
"You may have invalid args defined for this camera.")
|
||||
self.logger.error("You may have invalid args defined for this camera.")
|
||||
self.logpipe.dump()
|
||||
self.start_ffmpeg_detect()
|
||||
elif now - self.capture_thread.current_frame.value > 20:
|
||||
@ -236,8 +234,7 @@ class CameraWatchdog(threading.Thread):
|
||||
)
|
||||
self.ffmpeg_detect_process.terminate()
|
||||
try:
|
||||
self.logger.info(
|
||||
"Waiting for ffmpeg to exit gracefully...")
|
||||
self.logger.info("Waiting for ffmpeg to exit gracefully...")
|
||||
self.ffmpeg_detect_process.communicate(timeout=30)
|
||||
except sp.TimeoutExpired:
|
||||
self.logger.info("FFmpeg didnt exit. Force killing...")
|
||||
@ -485,13 +482,11 @@ def process_frames(
|
||||
current_frame_time.value = frame_time
|
||||
|
||||
frame = frame_manager.get(
|
||||
f"{camera_name}{frame_time}", (
|
||||
frame_shape[0] * 3 // 2, frame_shape[1])
|
||||
f"{camera_name}{frame_time}", (frame_shape[0] * 3 // 2, frame_shape[1])
|
||||
)
|
||||
|
||||
if frame is None:
|
||||
logger.info(
|
||||
f"{camera_name}: frame {frame_time} is not in memory store.")
|
||||
logger.info(f"{camera_name}: frame {frame_time} is not in memory store.")
|
||||
continue
|
||||
|
||||
if not detection_enabled.value:
|
||||
|
||||
@ -27,7 +27,7 @@ class FrigateWatchdog(threading.Thread):
|
||||
# check the detection processes
|
||||
for detector in self.detectors.values():
|
||||
detection_start = detector.detection_start.value
|
||||
if detection_start > 0.0 and now - detection_start > 10:
|
||||
if detection_start > 0.0 and now - detection_start > 30:
|
||||
logger.info(
|
||||
"Detection appears to be stuck. Restarting detection process..."
|
||||
)
|
||||
|
||||
@ -44,7 +44,7 @@ def get_frame_shape(source):
|
||||
"json",
|
||||
source,
|
||||
]
|
||||
p = sp.run(ffprobe_cmd, stdout=sp.PIPE, stderr=sp.PIPE)
|
||||
p = sp.run(ffprobe_cmd, capture_output=True)
|
||||
info = json.loads(p.stdout)
|
||||
|
||||
video_info = [s for s in info["streams"] if s["codec_type"] == "video"][0]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user