Create Lane-detect.py

Author: shubhcoder2104

Lane-detect.py

@@ -0,0 +1,41 @@
+import matplotlib.pylab as plt
+import cv2 as cv
+import numpy as np
+image=cv.imread('lane.jpeg')
+image=cv.cvtColor(image,cv.COLOR_BGR2RGB)
+
+#print(image.shape)
+height=image.shape[0]
+width=image.shape[1]
+
+def draw_the_line(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:
+            cv.line(blank_image,(x1,y1),(x2,y2),(255,255,0),thickness=2)
+    img=cv.addWeighted(img,0.8,blank_image,1,0.0)
+    return img
+
+
+def region_of_interst(img,vertices):
+    mask=np.zeros_like(img)
+    #channel_count=img.shape[2]
+    match_mask_color=255
+    cv.fillPoly(mask,vertices,match_mask_color)
+    mask_image=cv.bitwise_and(img,mask)
+    return mask_image
+
+
+region_of_interst_vertices=[(0,height),(width/2,height/2),(width,height)]
+gray=cv.cvtColor(image,cv.COLOR_BGR2GRAY)
+canny=cv.Canny(gray,100,200)
+
+cropped=region_of_interst(canny,np.array([region_of_interst_vertices],np.int32))
+line1=cv.HoughLinesP(cropped,rho=6,theta=np.pi/60,threshold=160,lines=np.array([]),minLineLength=40,maxLineGap=20)
+
+
+image_width_line=draw_the_line(image,line1)
+plt.imshow(image_width_line)
+plt.show()