mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-09-27 03:38:59 +03:00
Nicolas Mowen
6ae8050974
* Refactor hardware stats to have consolidated ffmpeg, detector, and enrichments running. * Cleanup hardware access that is not passed into the container * Remove network stats from hardware refactor
313 lines
12 KiB
Python
313 lines
12 KiB
Python
"""Utilities for stats."""
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import logging
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import shutil
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import time
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from json import JSONDecodeError
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from multiprocessing.managers import DictProxy
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from typing import Any
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import requests
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from requests.exceptions import RequestException
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from frigate.config import FrigateConfig
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from frigate.const import CACHE_DIR, CLIPS_DIR, RECORD_DIR
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from frigate.data_processing.types import DataProcessorMetrics
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from frigate.object_detection.base import ObjectDetectProcess
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from frigate.stats.hardware import HardwareStats, get_hardware_temperatures
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from frigate.types import StatsTrackingTypes
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from frigate.util.services import (
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calculate_shm_requirements,
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get_bandwidth_stats,
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get_fs_type,
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)
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from frigate.version import VERSION
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logger = logging.getLogger(__name__)
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def get_latest_version(config: FrigateConfig) -> str:
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if not config.telemetry.version_check:
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return "disabled"
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try:
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request = requests.get(
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"https://api.github.com/repos/blakeblackshear/frigate/releases/latest",
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timeout=10,
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)
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response = request.json()
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except (RequestException, JSONDecodeError):
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return "unknown"
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if request.ok and response and "tag_name" in response:
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return str(response.get("tag_name").replace("v", ""))
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else:
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return "unknown"
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def stats_init(
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config: FrigateConfig,
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camera_metrics: DictProxy,
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embeddings_metrics: DataProcessorMetrics,
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detectors: dict[str, ObjectDetectProcess],
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processes: dict[str, int],
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) -> StatsTrackingTypes:
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stats_tracking: StatsTrackingTypes = {
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"camera_metrics": camera_metrics,
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"embeddings_metrics": embeddings_metrics,
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"detectors": detectors,
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"started": int(time.time()),
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"latest_frigate_version": get_latest_version(config),
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"last_updated": int(time.time()),
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"processes": processes,
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}
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return stats_tracking
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def get_detector_stats(
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stats_tracking: StatsTrackingTypes,
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) -> dict[str, dict[str, Any]]:
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"""Get stats for all detectors, including temperatures based on detector type."""
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detector_stats: dict[str, dict[str, Any]] = {}
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detector_type_indices: dict[str, int] = {}
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for name, detector in stats_tracking["detectors"].items():
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pid = detector.detect_process.pid if detector.detect_process else None
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detector_type = detector.detector_config.type
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# Keep track of the index for each detector type to match temperatures correctly
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current_index = detector_type_indices.get(detector_type, 0)
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detector_type_indices[detector_type] = current_index + 1
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detector_stat = {
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"inference_speed": round(detector.avg_inference_speed.value * 1000, 2), # type: ignore[attr-defined]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"detection_start": detector.detection_start.value, # type: ignore[attr-defined]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"pid": pid,
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}
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temps = get_hardware_temperatures(detector_type)
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if current_index < len(temps) and temps[current_index] is not None:
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detector_stat["temperature"] = round(temps[current_index], 1)
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detector_stats[name] = detector_stat
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return detector_stats
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def stats_snapshot(
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config: FrigateConfig,
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stats_tracking: StatsTrackingTypes,
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hardware_stats: HardwareStats,
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) -> dict[str, Any]:
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"""Get a snapshot of the current stats that are being tracked."""
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camera_metrics = stats_tracking["camera_metrics"]
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stats: dict[str, Any] = {}
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total_camera_fps = total_process_fps = total_skipped_fps = total_detection_fps = 0
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stats["cameras"] = {}
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for name, camera_stats in camera_metrics.items():
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if name not in config.cameras:
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continue
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total_camera_fps += camera_stats.camera_fps.value
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total_process_fps += camera_stats.process_fps.value
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total_skipped_fps += camera_stats.skipped_fps.value
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total_detection_fps += camera_stats.detection_fps.value
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pid = camera_stats.process_pid.value if camera_stats.process_pid.value else None
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ffmpeg_pid = camera_stats.ffmpeg_pid.value if camera_stats.ffmpeg_pid else None
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capture_pid = (
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camera_stats.capture_process_pid.value
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if camera_stats.capture_process_pid.value
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else None
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)
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# Calculate connection quality based on current state
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# This is computed at stats-collection time so offline cameras
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# correctly show as unusable rather than excellent
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expected_fps = config.cameras[name].detect.fps
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current_fps = camera_stats.camera_fps.value
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reconnects = camera_stats.reconnects_last_hour.value
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stalls = camera_stats.stalls_last_hour.value
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if current_fps < 0.1:
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quality_str = "unusable"
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elif reconnects == 0 and current_fps >= 0.9 * expected_fps and stalls < 5:
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quality_str = "excellent"
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elif reconnects <= 2 and current_fps >= 0.6 * expected_fps:
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quality_str = "fair"
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elif reconnects > 10 or current_fps < 1.0 or stalls > 100:
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quality_str = "unusable"
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else:
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quality_str = "poor"
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connection_quality = {
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"connection_quality": quality_str,
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"expected_fps": expected_fps,
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"reconnects_last_hour": reconnects,
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"stalls_last_hour": stalls,
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}
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stats["cameras"][name] = {
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"camera_fps": round(camera_stats.camera_fps.value, 2),
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"process_fps": round(camera_stats.process_fps.value, 2),
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"skipped_fps": round(camera_stats.skipped_fps.value, 2),
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"detection_fps": round(camera_stats.detection_fps.value, 2),
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"detection_enabled": config.cameras[name].detect.enabled,
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"pid": pid,
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"capture_pid": capture_pid,
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"ffmpeg_pid": ffmpeg_pid,
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"audio_rms": round(camera_stats.audio_rms.value, 4),
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"audio_dBFS": round(camera_stats.audio_dBFS.value, 4),
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**connection_quality,
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}
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stats["detectors"] = get_detector_stats(stats_tracking)
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stats["camera_fps"] = round(total_camera_fps, 2)
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stats["process_fps"] = round(total_process_fps, 2)
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stats["skipped_fps"] = round(total_skipped_fps, 2)
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stats["detection_fps"] = round(total_detection_fps, 2)
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stats["embeddings"] = {}
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# Get metrics if available
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embeddings_metrics = stats_tracking.get("embeddings_metrics")
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if embeddings_metrics:
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# Add metrics based on what's enabled
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if config.semantic_search.enabled:
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stats["embeddings"].update(
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{
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"image_embedding_speed": round(
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embeddings_metrics.image_embeddings_speed.value * 1000, 2
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),
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"image_embedding": round(
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embeddings_metrics.image_embeddings_eps.value, 2
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),
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"text_embedding_speed": round(
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embeddings_metrics.text_embeddings_speed.value * 1000, 2
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),
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"text_embedding": round(
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embeddings_metrics.text_embeddings_eps.value, 2
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),
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}
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)
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if config.face_recognition.enabled:
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stats["embeddings"]["face_recognition_speed"] = round(
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embeddings_metrics.face_rec_speed.value * 1000, 2
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)
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stats["embeddings"]["face_recognition"] = round(
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embeddings_metrics.face_rec_fps.value, 2
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)
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if config.lpr.enabled:
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stats["embeddings"]["plate_recognition_speed"] = round(
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embeddings_metrics.alpr_speed.value * 1000, 2
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)
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stats["embeddings"]["plate_recognition"] = round(
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embeddings_metrics.alpr_pps.value, 2
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)
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if embeddings_metrics.yolov9_lpr_pps.value > 0.0:
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stats["embeddings"]["yolov9_plate_detection_speed"] = round(
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embeddings_metrics.yolov9_lpr_speed.value * 1000, 2
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)
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stats["embeddings"]["yolov9_plate_detection"] = round(
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embeddings_metrics.yolov9_lpr_pps.value, 2
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)
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if embeddings_metrics.review_desc_speed.value > 0.0:
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stats["embeddings"]["review_description_speed"] = round(
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embeddings_metrics.review_desc_speed.value * 1000, 2
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)
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stats["embeddings"]["review_description_events_per_second"] = round(
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embeddings_metrics.review_desc_dps.value, 2
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)
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if embeddings_metrics.object_desc_speed.value > 0.0:
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stats["embeddings"]["object_description_speed"] = round(
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embeddings_metrics.object_desc_speed.value * 1000, 2
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)
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stats["embeddings"]["object_description_events_per_second"] = round(
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embeddings_metrics.object_desc_dps.value, 2
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)
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for key in embeddings_metrics.classification_speeds.keys():
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stats["embeddings"][f"{key}_classification_speed"] = round(
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embeddings_metrics.classification_speeds[key].value * 1000, 2
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)
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stats["embeddings"][f"{key}_classification_events_per_second"] = round(
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embeddings_metrics.classification_cps[key].value, 2
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)
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hardware_stats.update_stats(stats)
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if config.telemetry.stats.network_bandwidth:
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bandwidth_stats = get_bandwidth_stats(config)
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if bandwidth_stats:
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stats["bandwidth_usages"] = bandwidth_stats
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stats["service"] = {
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"uptime": (int(time.time()) - stats_tracking["started"]),
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"version": VERSION,
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"latest_version": stats_tracking["latest_frigate_version"],
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"storage": {},
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"last_updated": int(time.time()),
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}
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for path in [RECORD_DIR, CLIPS_DIR, CACHE_DIR]:
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try:
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storage_stats = shutil.disk_usage(path)
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except (FileNotFoundError, OSError):
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stats["service"]["storage"][path] = {}
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continue
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stats["service"]["storage"][path] = {
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"total": round(storage_stats.total / pow(2, 20), 1),
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"used": round(storage_stats.used / pow(2, 20), 1),
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"free": round(storage_stats.free / pow(2, 20), 1),
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"mount_type": get_fs_type(path),
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}
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stats["service"]["storage"]["/dev/shm"] = calculate_shm_requirements(config)
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stats["processes"] = {}
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for name, pid in stats_tracking["processes"].items():
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stats["processes"][name] = {
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"pid": pid,
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}
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# Embed cpu/mem stats into detectors, cameras, and processes
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# so history consumers don't need the full cpu_usages dict
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cpu_usages = stats.get("cpu_usages", {})
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for det_stats in stats["detectors"].values():
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pid_str = str(det_stats.get("pid", ""))
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usage = cpu_usages.get(pid_str, {})
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det_stats["cpu"] = usage.get("cpu")
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det_stats["mem"] = usage.get("mem")
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for cam_stats in stats["cameras"].values():
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for pid_key, field in [
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("ffmpeg_pid", "ffmpeg_cpu"),
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("capture_pid", "capture_cpu"),
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("pid", "detect_cpu"),
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]:
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pid_str = str(cam_stats.get(pid_key, ""))
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usage = cpu_usages.get(pid_str, {})
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cam_stats[field] = usage.get("cpu")
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for proc_stats in stats["processes"].values():
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pid_str = str(proc_stats.get("pid", ""))
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usage = cpu_usages.get(pid_str, {})
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proc_stats["cpu"] = usage.get("cpu")
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proc_stats["mem"] = usage.get("mem")
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return stats
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