41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
import numpy as np
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import numpy.typing as npt
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import cv2
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import uz_framework.image as uz_image
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from matplotlib import pyplot as plt
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VIDEO_PATH = "./datam/raw_recording.webm"
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MY_SIFT = False
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def start_realtime_keypoint_detection():
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# Read video
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cap = cv2.VideoCapture(VIDEO_PATH)
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count = 0
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sift = cv2.SIFT_create()
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while cap.isOpened():
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ret,frame = cap.read()
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frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) # Convert to grayscale
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if MY_SIFT:
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#sift_keypoints,_ = uz_image.hessian(frame)
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_, sift_keypoints = uz_image.hessian_points(frame, 3, 0.004)
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sift_keypoints = np.float64(sift_keypoints)
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kps = []
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for keypoint in sift_keypoints:
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y, x = keypoint
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kps.append(cv2.KeyPoint(x=x, y=y, size=1))
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else:
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kps, _ = sift.detectAndCompute(frame, None)
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frame = cv2.drawKeypoints(frame, kps, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
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#cv2.imshow('hello', frame)
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cv2.imwrite("./datam/true_sift/%d.jpg" % count, frame)
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print(f'{count} <- frame')
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count = count + 1
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#if cv2.waitKey(10) & 0xFF == ord('q'):
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#break
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cap.release()
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cv2.destroyAllWindows() # destroy all opened windows
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if __name__ == '__main__':
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start_realtime_keypoint_detection()
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