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OpenCV_Starting.py
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OpenCV_Starting.py
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import matplotlib.pylab as plt
import cv2
import numpy as np
def region_of_interest(img, vertices):
mask = np.zeros_like(img)
#channel_count = img.shape[2]
match_mask_color = 255
cv2.fillPoly(mask, vertices, match_mask_color)
masked_image = cv2.bitwise_and(img, mask)
return masked_image
def draw_the_lines (img, lines):
img = np.copy (img)
blank_image = np.zeros((img.shape[0],img.shape[1], 3), dtype=np.uint8)
for line in lines:
for x1,y1,x2,y2 in line:
cv2.line(blank_image, (x1,y1), (x2,y2), (0,255,0), thickness=10)
img = cv2.addWeighted(img, 0.8, blank_image, 1, 0.0)
return img
def main(image):
# print(image.shape)
height = image.shape[0]
width = image.shape[1]
roi_vertices = [(0, height-70), (width / 2.3, height / 2.5), (width, height-70)]#ROI may vary from frame to frame, these values are for my input
gray_scale_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
canny_image = cv2.Canny(gray_scale_image, 100, 120)
cropped_image = region_of_interest(canny_image, np.array([roi_vertices], np.int32))
lines = cv2.HoughLinesP(cropped_image, rho=1, theta=np.pi / 180, threshold=100, lines=np.array([]),
minLineLength=80, maxLineGap=120)
image_with_lines = draw_the_lines(image, lines)
return image_with_lines
capture = cv2.VideoCapture('roadvideo.mov')
while(capture.isOpened()):
ret, frame = capture.read()
frame = main(frame)
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()