opencv/samples/python/opt_flow.py

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#!/usr/bin/env python
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'''
example to show optical flow
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USAGE: opt_flow.py [<video_source>]
Keys:
1 - toggle HSV flow visualization
2 - toggle glitch
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Keys:
ESC - exit
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'''
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# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2
import video
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def draw_flow(img, flow, step=16):
h, w = img.shape[:2]
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
lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
lines = np.int32(lines + 0.5)
vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
cv2.polylines(vis, lines, 0, (0, 255, 0))
for (x1, y1), (x2, y2) in lines:
cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
return vis
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def draw_hsv(flow):
h, w = flow.shape[:2]
fx, fy = flow[:,:,0], flow[:,:,1]
ang = np.arctan2(fy, fx) + np.pi
v = np.sqrt(fx*fx+fy*fy)
hsv = np.zeros((h, w, 3), np.uint8)
hsv[...,0] = ang*(180/np.pi/2)
hsv[...,1] = 255
hsv[...,2] = np.minimum(v*4, 255)
bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
return bgr
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def warp_flow(img, flow):
h, w = flow.shape[:2]
flow = -flow
flow[:,:,0] += np.arange(w)
flow[:,:,1] += np.arange(h)[:,np.newaxis]
res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
return res
if __name__ == '__main__':
import sys
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print(__doc__)
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try:
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)
ret, prev = cam.read()
prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)
show_hsv = False
show_glitch = False
cur_glitch = prev.copy()
while True:
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
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prevgray = gray
cv2.imshow('flow', draw_flow(gray, flow))
if show_hsv:
cv2.imshow('flow HSV', draw_hsv(flow))
if show_glitch:
cur_glitch = warp_flow(cur_glitch, flow)
cv2.imshow('glitch', cur_glitch)
ch = 0xFF & cv2.waitKey(5)
if ch == 27:
break
if ch == ord('1'):
show_hsv = not show_hsv
print('HSV flow visualization is', ['off', 'on'][show_hsv])
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if ch == ord('2'):
show_glitch = not show_glitch
if show_glitch:
cur_glitch = img.copy()
print('glitch is', ['off', 'on'][show_glitch])
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cv2.destroyAllWindows()