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Open Source Computer Vision Library
https://opencv.org/
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80 lines
3.2 KiB
80 lines
3.2 KiB
import numpy as np |
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import cv2 |
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import video |
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from common import nothing, clock, draw_str |
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MHI_DURATION = 0.5 |
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DEFAULT_THRESHOLD = 32 |
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MAX_TIME_DELTA = 0.25 |
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MIN_TIME_DELTA = 0.05 |
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def draw_motion_comp(vis, (x, y, w, h), angle, color): |
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cv2.rectangle(vis, (x, y), (x+w, y+h), (0, 255, 0)) |
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r = min(w/2, h/2) |
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cx, cy = x+w/2, y+h/2 |
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angle = angle*np.pi/180 |
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cv2.circle(vis, (cx, cy), r, color, 3) |
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cv2.line(vis, (cx, cy), (int(cx+np.cos(angle)*r), int(cy+np.sin(angle)*r)), color, 3) |
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if __name__ == '__main__': |
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import sys |
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try: video_src = sys.argv[1] |
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except: video_src = 0 |
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cv2.namedWindow('motempl') |
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visuals = ['input', 'frame_diff', 'motion_hist', 'grad_orient'] |
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cv2.createTrackbar('visual', 'motempl', 2, len(visuals)-1, nothing) |
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cv2.createTrackbar('threshold', 'motempl', DEFAULT_THRESHOLD, 255, nothing) |
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cam = video.create_capture(video_src, fallback='synth:class=chess:bg=../cpp/lena.jpg:noise=0.01') |
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ret, frame = cam.read() |
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h, w = frame.shape[:2] |
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prev_frame = frame.copy() |
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motion_history = np.zeros((h, w), np.float32) |
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hsv = np.zeros((h, w, 3), np.uint8) |
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hsv[:,:,1] = 255 |
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while True: |
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ret, frame = cam.read() |
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frame_diff = cv2.absdiff(frame, prev_frame) |
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gray_diff = cv2.cvtColor(frame_diff, cv2.COLOR_BGR2GRAY) |
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thrs = cv2.getTrackbarPos('threshold', 'motempl') |
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ret, motion_mask = cv2.threshold(gray_diff, thrs, 1, cv2.THRESH_BINARY) |
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timestamp = clock() |
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cv2.updateMotionHistory(motion_mask, motion_history, timestamp, MHI_DURATION) |
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mg_mask, mg_orient = cv2.calcMotionGradient( motion_history, MAX_TIME_DELTA, MIN_TIME_DELTA, apertureSize=5 ) |
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seg_mask, seg_bounds = cv2.segmentMotion(motion_history, timestamp, MAX_TIME_DELTA) |
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visual_name = visuals[cv2.getTrackbarPos('visual', 'motempl')] |
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if visual_name == 'input': |
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vis = frame.copy() |
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elif visual_name == 'frame_diff': |
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vis = frame_diff.copy() |
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elif visual_name == 'motion_hist': |
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vis = np.uint8(np.clip((motion_history-(timestamp-MHI_DURATION)) / MHI_DURATION, 0, 1)*255) |
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vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR) |
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elif visual_name == 'grad_orient': |
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hsv[:,:,0] = mg_orient/2 |
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hsv[:,:,2] = mg_mask*255 |
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vis = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) |
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for i, rect in enumerate([(0, 0, w, h)] + list(seg_bounds)): |
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x, y, rw, rh = rect |
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area = rw*rh |
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if area < 64**2: |
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continue |
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silh_roi = motion_mask [y:y+rh,x:x+rw] |
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orient_roi = mg_orient [y:y+rh,x:x+rw] |
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mask_roi = mg_mask [y:y+rh,x:x+rw] |
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mhi_roi = motion_history[y:y+rh,x:x+rw] |
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if cv2.norm(silh_roi, cv2.NORM_L1) < area*0.05: |
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continue |
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angle = cv2.calcGlobalOrientation(orient_roi, mask_roi, mhi_roi, timestamp, MHI_DURATION) |
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color = ((255, 0, 0), (0, 0, 255))[i == 0] |
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draw_motion_comp(vis, rect, angle, color) |
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draw_str(vis, (20, 20), visual_name) |
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cv2.imshow('motempl', vis) |
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prev_frame = frame.copy() |
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if cv2.waitKey(5) == 27: |
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break |