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| import cv2
import numpy as np
capture = cv2.VideoCapture('race.mp4')
while cv2.waitKey(33) < 0:
if capture.get(cv2.CAP_PROP_POS_FRAMES) == capture.get(cv2.CAP_PROP_FRAME_COUNT):
capture.get(cv2.CAP_PROP_POS_FRAMES, 0)
ret, frame = capture.read()
trap_bottom_width = 0.85
trap_top_width = 0.075
trap_height = 0.43
def region_of_interest(frame):
frame_mask = np.zeros_like(frame)
if frame.ndim > 2:
channel_count = frame.shape[2]
ignore_mask_color = (255, 255, 255)
else:
ignore_mask_color = 255
imshape = frame.shape
vertices = np.array([[ \
((imshape[1] * (1 - trap_bottom_width)) // 2, imshape[0]), \
((imshape[1] * (1 - trap_top_width)) // 2, imshape[0] - imshape[0] * trap_height), \
(imshape[1] - (imshape[1] * (1 - trap_top_width)) // 2, imshape[0] - imshape[0] * trap_height), \
(imshape[1] - (imshape[1] * (1 - trap_bottom_width)) // 2, imshape[0])]] \
, dtype=np.int32)
cv2.fillPoly(frame_mask, vertices, ignore_mask_color)
frame = cv2.bitwise_and(frame, frame_mask)
return frame
if __name__ == '__main__':
frame = cv2.imread("line.png", cv2.IMREAD_COLOR)
frame_gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame_gray = cv2.GaussianBlur(frame_gray, (5,5), 0)
frame_canny = cv2.Canny(frame_gray, 95, 200)
frame_canny = region_of_interest(frame_canny)
rho = 2
theta = 1 * np.pi/180
threshold = 15
min_line_len = 10
max_line_gap = 20
lines = cv2.HoughLinesP(frame_canny, rho, theta, threshold, np.array([]), \
minLineLength=min_line_len, maxLineGap=max_line_gap)
for i, line in enumerate(lines):
cv2.line(frame, (line[0][0],line[0][1]),(line[0][2],line[0][3]), \
(0,255,0), 2)
cv2.imshow("src",frame)
capture.release()
cv2.destroyAllWindows()
|