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findlanes.py
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findlanes.py
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from lanefinder import LaneFinder
import sys
import numpy as np
import cv2
from moviepy.editor import VideoFileClip
def plot( img, y0, y, color):
x = np.mgrid[0:len(y)]
y1 = 10*y/max(y) + y0
poly=np.vstack([x, y1]).T
cv2.polylines( img, [np.asarray(poly, dtype=np.int32)], isClosed=False, color=color, thickness=2)
def preview( lanefinder ):
def f( img ):
cv2.imwrite('tmp.bmp', img)
result = lanefinder.process_image( img )
cv2.imshow("result", cv2.cvtColor(result, cv2.COLOR_RGB2BGR))
persp = cv2.cvtColor(lanefinder.viz['perspective'], cv2.COLOR_RGB2BGR)
for idx, yslice in enumerate(lanefinder.viz['slice']):
#plot( persp, (yslice[1]+yslice[0])/2, lanefinder.viz['hist'][idx], (0,0,255) )
plot( persp, (yslice[1]+yslice[0])/2, lanefinder.viz['dhist'][idx], (0,255,0) )
plot( persp, (yslice[1]+yslice[0])/2, lanefinder.viz['dilated'][idx], (128,0,255) )
cv2.imshow("perspective", persp )
#dI = lanefinder.viz['gradient']
#minVal, maxVal, minLoc, maxLoc = cv2.minMaxLoc(dI)
#cv2.imshow("gradient", (dI-minVal)/(maxVal-minVal))
cv2.waitKey(10)
return result
return f
if __name__ == "__main__":
infname = sys.argv[1]
calibfname = sys.argv[2]
outfname = sys.argv[3]
arr = np.load(calibfname)
lanefinder = LaneFinder( image_size=tuple(arr['image_size']), cameraMatrix=arr['cameraMatrix'], distCoeffs=arr['distCoeffs'], newcameramtx=arr['newcameramtx'] )
cv2.namedWindow("result")
cv2.namedWindow("perspective")
input_clip = VideoFileClip( infname )
output_clip = input_clip.fl_image( preview(lanefinder) )
output_clip.write_videofile(outfname, audio=False)