34 lines
962 B
Python
34 lines
962 B
Python
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import cv2
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import numpy as np
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from tensorflow.keras.preprocessing.image import img_to_array
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from tensorflow.keras.applications.vgg16 import preprocess_input
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def preprocess_frame(frame, target_size=(224, 224)):
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frame = cv2.resize(frame, target_size)
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frame = img_to_array(frame)
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frame = np.expand_dims(frame, axis=0)
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frame = preprocess_input(frame)
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return frame
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def generate_video_embedding(video_path, model):
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cap = cv2.VideoCapture(video_path)
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frames = []
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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frames.append(preprocess_frame(frame))
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if len(frames) >= 16: # Process 16 frames at a time
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break
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cap.release()
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if not frames:
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return None
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# Generate embeddings
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embeddings = model.predict(np.vstack(frames))
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# Average the embeddings
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avg_embedding = np.mean(embeddings, axis=0)
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return avg_embedding
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