mirror of
https://github.com/blakeblackshear/frigate.git
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03c8e5ce8d
* Validate faces using cosine distance and SVC * Formatting * Use opencv instead of face embedding * Update docs for training data * Adjust to score system * Set bounds * remove face embeddings * Update writing images * Add face library page * Add ability to select file * Install opencv deps * Cleanup * Use different deps * Move deps * Cleanup * Only show face library for desktop * Implement deleting * Add ability to upload image * Add support for uploading images
60 lines
1.7 KiB
Python
60 lines
1.7 KiB
Python
"""Object classification APIs."""
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import logging
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import os
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from fastapi import APIRouter, Request, UploadFile
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from fastapi.responses import JSONResponse
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from pathvalidate import sanitize_filename
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from frigate.api.defs.tags import Tags
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from frigate.const import FACE_DIR
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from frigate.embeddings import EmbeddingsContext
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logger = logging.getLogger(__name__)
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router = APIRouter(tags=[Tags.events])
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@router.get("/faces")
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def get_faces():
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face_dict: dict[str, list[str]] = {}
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for name in os.listdir(FACE_DIR):
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face_dict[name] = []
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for file in os.listdir(os.path.join(FACE_DIR, name)):
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face_dict[name].append(file)
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return JSONResponse(status_code=200, content=face_dict)
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@router.post("/faces/{name}")
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async def register_face(request: Request, name: str, file: UploadFile):
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context: EmbeddingsContext = request.app.embeddings
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context.register_face(name, await file.read())
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return JSONResponse(
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status_code=200,
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content={"success": True, "message": "Successfully registered face."},
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)
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@router.post("/faces/{name}/delete")
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def deregister_faces(request: Request, name: str, body: dict = None):
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json: dict[str, any] = body or {}
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list_of_ids = json.get("ids", "")
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if not list_of_ids or len(list_of_ids) == 0:
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return JSONResponse(
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content=({"success": False, "message": "Not a valid list of ids"}),
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status_code=404,
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)
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context: EmbeddingsContext = request.app.embeddings
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context.delete_face_ids(
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name, map(lambda file: sanitize_filename(file), list_of_ids)
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)
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return JSONResponse(
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content=({"success": True, "message": "Successfully deleted faces."}),
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status_code=200,
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)
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