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96bf26611e
* moved DIS optical flow from opencv_contrib to opencv, moved TVL1 from opencv to opencv_contrib * fixed compile warning * TVL1 optical flow example moved to opencv_contrib
115 lines
3.4 KiB
Python
Executable File
115 lines
3.4 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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example to show optical flow estimation using DISOpticalFlow
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USAGE: dis_opt_flow.py [<video_source>]
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Keys:
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1 - toggle HSV flow visualization
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2 - toggle glitch
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3 - toggle spatial propagation of flow vectors
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4 - toggle temporal propagation of flow vectors
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ESC - exit
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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import video
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def draw_flow(img, flow, step=16):
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h, w = img.shape[:2]
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y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int)
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fx, fy = flow[y,x].T
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lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
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lines = np.int32(lines + 0.5)
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vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
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cv.polylines(vis, lines, 0, (0, 255, 0))
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for (x1, y1), (x2, y2) in lines:
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cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
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return vis
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def draw_hsv(flow):
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h, w = flow.shape[:2]
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fx, fy = flow[:,:,0], flow[:,:,1]
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ang = np.arctan2(fy, fx) + np.pi
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v = np.sqrt(fx*fx+fy*fy)
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hsv = np.zeros((h, w, 3), np.uint8)
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hsv[...,0] = ang*(180/np.pi/2)
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hsv[...,1] = 255
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hsv[...,2] = np.minimum(v*4, 255)
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bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)
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return bgr
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def warp_flow(img, flow):
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h, w = flow.shape[:2]
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flow = -flow
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flow[:,:,0] += np.arange(w)
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flow[:,:,1] += np.arange(h)[:,np.newaxis]
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res = cv.remap(img, flow, None, cv.INTER_LINEAR)
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return res
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if __name__ == '__main__':
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import sys
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print(__doc__)
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try:
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fn = sys.argv[1]
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except IndexError:
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fn = 0
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cam = video.create_capture(fn)
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ret, prev = cam.read()
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prevgray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY)
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show_hsv = False
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show_glitch = False
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use_spatial_propagation = False
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use_temporal_propagation = True
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cur_glitch = prev.copy()
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inst = cv.DISOpticalFlow.create(cv.DISOPTICAL_FLOW_PRESET_MEDIUM)
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inst.setUseSpatialPropagation(use_spatial_propagation)
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flow = None
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while True:
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ret, img = cam.read()
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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if flow is not None and use_temporal_propagation:
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#warp previous flow to get an initial approximation for the current flow:
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flow = inst.calc(prevgray, gray, warp_flow(flow,flow))
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else:
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flow = inst.calc(prevgray, gray, None)
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prevgray = gray
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cv.imshow('flow', draw_flow(gray, flow))
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if show_hsv:
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cv.imshow('flow HSV', draw_hsv(flow))
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if show_glitch:
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cur_glitch = warp_flow(cur_glitch, flow)
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cv.imshow('glitch', cur_glitch)
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ch = 0xFF & cv.waitKey(5)
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if ch == 27:
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break
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if ch == ord('1'):
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show_hsv = not show_hsv
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print('HSV flow visualization is', ['off', 'on'][show_hsv])
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if ch == ord('2'):
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show_glitch = not show_glitch
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if show_glitch:
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cur_glitch = img.copy()
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print('glitch is', ['off', 'on'][show_glitch])
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if ch == ord('3'):
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use_spatial_propagation = not use_spatial_propagation
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inst.setUseSpatialPropagation(use_spatial_propagation)
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print('spatial propagation is', ['off', 'on'][use_spatial_propagation])
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if ch == ord('4'):
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use_temporal_propagation = not use_temporal_propagation
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print('temporal propagation is', ['off', 'on'][use_temporal_propagation])
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cv.destroyAllWindows()
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