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samples/python/dis_opt_flow.py

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+#!/usr/bin/env python
+
+'''
+example to show optical flow estimation using DISOpticalFlow
+
+USAGE: dis_opt_flow.py [<video_source>]
+
+Keys:
+ 1  - toggle HSV flow visualization
+ 2  - toggle glitch
+ 3  - toggle spatial propagation of flow vectors
+ 4  - toggle temporal propagation of flow vectors
+ESC - exit
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+import video
+
+
+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)
+    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 = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
+    cv.polylines(vis, lines, 0, (0, 255, 0))
+    for (x1, y1), (_x2, _y2) in lines:
+        cv.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
+    return vis
+
+
+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 = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)
+    return bgr
+
+
+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 = cv.remap(img, flow, None, cv.INTER_LINEAR)
+    return res
+
+
+def main():
+    import sys
+    print(__doc__)
+    try:
+        fn = sys.argv[1]
+    except IndexError:
+        fn = 0
+
+    cam = video.create_capture(fn)
+    _ret, prev = cam.read()
+    prevgray = cv.cvtColor(prev, cv.COLOR_BGR2GRAY)
+    show_hsv = False
+    show_glitch = False
+    use_spatial_propagation = False
+    use_temporal_propagation = True
+    cur_glitch = prev.copy()
+    inst = cv.DISOpticalFlow.create(cv.DISOPTICAL_FLOW_PRESET_MEDIUM)
+    inst.setUseSpatialPropagation(use_spatial_propagation)
+
+    flow = None
+    while True:
+        _ret, img = cam.read()
+        gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+        if flow is not None and use_temporal_propagation:
+            #warp previous flow to get an initial approximation for the current flow:
+            flow = inst.calc(prevgray, gray, warp_flow(flow,flow))
+        else:
+            flow = inst.calc(prevgray, gray, None)
+        prevgray = gray
+
+        cv.imshow('flow', draw_flow(gray, flow))
+        if show_hsv:
+            cv.imshow('flow HSV', draw_hsv(flow))
+        if show_glitch:
+            cur_glitch = warp_flow(cur_glitch, flow)
+            cv.imshow('glitch', cur_glitch)
+
+        ch = 0xFF & cv.waitKey(5)
+        if ch == 27:
+            break
+        if ch == ord('1'):
+            show_hsv = not show_hsv
+            print('HSV flow visualization is', ['off', 'on'][show_hsv])
+        if ch == ord('2'):
+            show_glitch = not show_glitch
+            if show_glitch:
+                cur_glitch = img.copy()
+            print('glitch is', ['off', 'on'][show_glitch])
+        if ch == ord('3'):
+            use_spatial_propagation = not use_spatial_propagation
+            inst.setUseSpatialPropagation(use_spatial_propagation)
+            print('spatial propagation is', ['off', 'on'][use_spatial_propagation])
+        if ch == ord('4'):
+            use_temporal_propagation = not use_temporal_propagation
+            print('temporal propagation is', ['off', 'on'][use_temporal_propagation])
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()