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@pknowledge
Created August 31, 2019 15:24
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OpenCV Python Tutorial For Beginners - Road Lane Line Detection with OpenCV (Part 3)
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 drow_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
# = cv2.imread('road.jpg')
#image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
def process(image):
print(image.shape)
height = image.shape[0]
width = image.shape[1]
region_of_interest_vertices = [
(0, height),
(width/2, height/2),
(width, height)
]
gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
canny_image = cv2.Canny(gray_image, 100, 120)
cropped_image = region_of_interest(canny_image,
np.array([region_of_interest_vertices], np.int32),)
lines = cv2.HoughLinesP(cropped_image,
rho=2,
theta=np.pi/180,
threshold=50,
lines=np.array([]),
minLineLength=40,
maxLineGap=100)
image_with_lines = drow_the_lines(image, lines)
return image_with_lines
cap = cv2.VideoCapture('test.mp4')
while cap.isOpened():
ret, frame = cap.read()
frame = process(frame)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
@Salma6591
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Hello! thanks very much for this Tutorial ,I want instead of using the video to work with raspberry camera what should I do?

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