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Correctly download model
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@ -123,6 +123,18 @@ class Embeddings:
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device="GPU" if config.semantic_search.model_size == "large" else "CPU",
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device="GPU" if config.semantic_search.model_size == "large" else "CPU",
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)
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)
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if self.config.face_recognition.enabled:
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self.face_embedding = GenericONNXEmbedding(
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model_name="facedet",
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model_file="facedet.onnx",
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download_urls={
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"facedet.onnx": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/facedet.onnx",
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"landmarkdet.yaml": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/landmarkdet.yaml",
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},
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model_type=ModelTypeEnum.face,
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requestor=self.requestor,
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)
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self.lpr_detection_model = None
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self.lpr_detection_model = None
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self.lpr_classification_model = None
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self.lpr_classification_model = None
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self.lpr_recognition_model = None
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self.lpr_recognition_model = None
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@ -163,7 +163,7 @@ class FaceClassificationModel:
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self.config = config
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self.config = config
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self.db = db
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self.db = db
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self.landmark_detector = cv2.face.createFacemarkLBF()
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self.landmark_detector = cv2.face.createFacemarkLBF()
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self.landmark_detector.loadModel("/config/model_cache/facenet/lbfmodel.yaml")
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self.landmark_detector.loadModel("/config/model_cache/facenet/landmarkdet.yaml")
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self.recognizer: cv2.face.LBPHFaceRecognizer = (
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self.recognizer: cv2.face.LBPHFaceRecognizer = (
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cv2.face.LBPHFaceRecognizer_create(
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cv2.face.LBPHFaceRecognizer_create(
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radius=2, threshold=(1 - config.threshold) * 1000
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radius=2, threshold=(1 - config.threshold) * 1000
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