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