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import cv2
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import numpy as np
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def video_Frames(clip_path,img_size = 64):
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video = cv2.VideoCapture(clip_path)
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frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
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for count in range(frame_count):
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flag, frame = video.read()
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if not flag:
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break
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frame = cv2.resize(frame,(img_size,img_size))
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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frame = frame/255.0
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yield frame
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video.release()
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def load_video(folder_path):
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imgs = []
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frames_generator = video_Frames(folder_path)
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frames_array = np.array(list(frames_generator))
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imgs.append(frames_array)
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real_imgs = np.array(imgs)
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return imgs
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def eval_real(real_imgs, model):
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pred1 = model.predict(real_imgs)
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pred1_max = pred1.argmax()
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return pred1_max |
