Computer_Vision/Chapter18/detecting_lanes_in_the_image_of_a_road.ipynb

!wget https://www.dropbox.com/s/vgd22go8a6k721t/road_image.png

--2020-10-05 17:11:28--  https://www.dropbox.com/s/vgd22go8a6k721t/road_image.png
Resolving www.dropbox.com (www.dropbox.com)... 162.125.9.1, 2620:100:601d:1::a27d:501
Connecting to www.dropbox.com (www.dropbox.com)|162.125.9.1|:443... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: /s/raw/vgd22go8a6k721t/road_image.png [following]
--2020-10-05 17:11:29--  https://www.dropbox.com/s/raw/vgd22go8a6k721t/road_image.png
Reusing existing connection to www.dropbox.com:443.
HTTP request sent, awaiting response... 302 Found
Location: https://ucf145594d0280419127c347de41.dl.dropboxusercontent.com/cd/0/inline/BAspiWKFI1iwzcOvDUuAPzYC2BCDMeSMTcfG75YdsfJRG7ugn_lq6JpnTUwL8Ru40q0FWI3w3U8t8MLgu6in-_qZ_KKEaThWkGkbRZCCuEV--RroiMHHkph3hhfhJ-LtN80/file# [following]
--2020-10-05 17:11:29--  https://ucf145594d0280419127c347de41.dl.dropboxusercontent.com/cd/0/inline/BAspiWKFI1iwzcOvDUuAPzYC2BCDMeSMTcfG75YdsfJRG7ugn_lq6JpnTUwL8Ru40q0FWI3w3U8t8MLgu6in-_qZ_KKEaThWkGkbRZCCuEV--RroiMHHkph3hhfhJ-LtN80/file
Resolving ucf145594d0280419127c347de41.dl.dropboxusercontent.com (ucf145594d0280419127c347de41.dl.dropboxusercontent.com)... 162.125.5.15, 2620:100:601f:15::a27d:90f
Connecting to ucf145594d0280419127c347de41.dl.dropboxusercontent.com (ucf145594d0280419127c347de41.dl.dropboxusercontent.com)|162.125.5.15|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 608479 (594K) [image/png]
Saving to: ‘road_image.png’

road_image.png      100%[===================>] 594.22K  --.-KB/s    in 0.1s    

2020-10-05 17:11:30 (4.37 MB/s) - ‘road_image.png’ saved [608479/608479]

!pip install torch_snippets
from torch_snippets import show, read, subplots, cv2, np
IMG = read('road_image.png')
img = np.uint8(IMG.copy())

Collecting torch_snippets
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Collecting immutables>=0.9
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edges = cv2.Canny(img,50,150)
show(edges)

lines = cv2.HoughLines(edges,1,np.pi/180,150)

lines = lines[:,0,:]
for rho,theta in lines:
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a*rho
    y0 = b*rho
    x1 = int(x0 + 10000*(-b))
    y1 = int(y0 + 10000*(a))
    x2 = int(x0 - 10000*(-b))
    y2 = int(y0 - 10000*(a))
    cv2.line(img,(x1,y1),(x2,y2),(0,0,255),2)

show(img)