mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
cedd082b30
* Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model
123 lines
2.9 KiB
Python
123 lines
2.9 KiB
Python
import re
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CONFIG_DIR = "/config"
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DEFAULT_DB_PATH = f"{CONFIG_DIR}/frigate.db"
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MODEL_CACHE_DIR = f"{CONFIG_DIR}/model_cache"
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BASE_DIR = "/media/frigate"
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CLIPS_DIR = f"{BASE_DIR}/clips"
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EXPORT_DIR = f"{BASE_DIR}/exports"
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FACE_DIR = f"{CLIPS_DIR}/faces"
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RECORD_DIR = f"{BASE_DIR}/recordings"
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BIRDSEYE_PIPE = "/tmp/cache/birdseye"
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CACHE_DIR = "/tmp/cache"
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FRIGATE_LOCALHOST = "http://127.0.0.1:5000"
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PLUS_ENV_VAR = "PLUS_API_KEY"
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PLUS_API_HOST = "https://api.frigate.video"
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# Attribute & Object constants
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DEFAULT_ATTRIBUTE_LABEL_MAP = {
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"person": ["amazon", "face"],
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"car": [
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"amazon",
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"an_post",
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"dhl",
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"dpd",
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"fedex",
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"gls",
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"license_plate",
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"nzpost",
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"postnl",
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"postnord",
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"purolator",
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"ups",
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"usps",
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],
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}
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LABEL_CONSOLIDATION_MAP = {
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"car": 0.8,
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"face": 0.5,
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}
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LABEL_CONSOLIDATION_DEFAULT = 0.9
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LABEL_NMS_MAP = {
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"car": 0.6,
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}
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LABEL_NMS_DEFAULT = 0.4
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# Audio constants
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AUDIO_DURATION = 0.975
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AUDIO_FORMAT = "s16le"
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AUDIO_MAX_BIT_RANGE = 32768.0
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AUDIO_SAMPLE_RATE = 16000
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AUDIO_MIN_CONFIDENCE = 0.5
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# DB constants
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MAX_WAL_SIZE = 10 # MB
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# Ffmpeg constants
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DEFAULT_FFMPEG_VERSION = "7.0"
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INCLUDED_FFMPEG_VERSIONS = ["7.0", "5.0"]
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FFMPEG_HWACCEL_NVIDIA = "preset-nvidia"
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FFMPEG_HWACCEL_VAAPI = "preset-vaapi"
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FFMPEG_HWACCEL_VULKAN = "preset-vulkan"
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# Regex constants
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REGEX_CAMERA_NAME = r"^[a-zA-Z0-9_-]+$"
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REGEX_RTSP_CAMERA_USER_PASS = r":\/\/[a-zA-Z0-9_-]+:[\S]+@"
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REGEX_HTTP_CAMERA_USER_PASS = r"user=[a-zA-Z0-9_-]+&password=[\S]+"
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REGEX_JSON = re.compile(r"^\s*\{")
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# Known Driver Names
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DRIVER_ENV_VAR = "LIBVA_DRIVER_NAME"
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DRIVER_AMD = "radeonsi"
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DRIVER_INTEL_i965 = "i965"
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DRIVER_INTEL_iHD = "iHD"
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# Preview Values
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PREVIEW_FRAME_TYPE = "webp"
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# Record Values
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CACHE_SEGMENT_FORMAT = "%Y%m%d%H%M%S%z"
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MAX_PRE_CAPTURE = 60
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MAX_SEGMENT_DURATION = 600
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MAX_SEGMENTS_IN_CACHE = 6
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MAX_PLAYLIST_SECONDS = 7200 # support 2 hour segments for a single playlist to account for cameras with inconsistent segment times
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# Internal Comms Topics
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INSERT_MANY_RECORDINGS = "insert_many_recordings"
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INSERT_PREVIEW = "insert_preview"
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REQUEST_REGION_GRID = "request_region_grid"
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UPSERT_REVIEW_SEGMENT = "upsert_review_segment"
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CLEAR_ONGOING_REVIEW_SEGMENTS = "clear_ongoing_review_segments"
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UPDATE_CAMERA_ACTIVITY = "update_camera_activity"
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UPDATE_EVENT_DESCRIPTION = "update_event_description"
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UPDATE_MODEL_STATE = "update_model_state"
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UPDATE_EMBEDDINGS_REINDEX_PROGRESS = "handle_embeddings_reindex_progress"
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# Stats Values
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FREQUENCY_STATS_POINTS = 15
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# Autotracking
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AUTOTRACKING_MAX_AREA_RATIO = 0.6
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AUTOTRACKING_MOTION_MIN_DISTANCE = 20
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AUTOTRACKING_MOTION_MAX_POINTS = 500
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AUTOTRACKING_MAX_MOVE_METRICS = 500
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AUTOTRACKING_ZOOM_OUT_HYSTERESIS = 1.1
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AUTOTRACKING_ZOOM_IN_HYSTERESIS = 0.95
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AUTOTRACKING_ZOOM_EDGE_THRESHOLD = 0.05
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# Auth
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JWT_SECRET_ENV_VAR = "FRIGATE_JWT_SECRET"
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PASSWORD_HASH_ALGORITHM = "pbkdf2_sha256"
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