In [2]:

    

http://warmspringwinds.github.io/tensorflow/tf-slim/2016/12/18/image-segmentation-with-tensorflow-using-cnns-and-conditional-random-fields/
import cv2
import matplotlib.pyplot as plt
%matplotlib inline
import sys
import pdb


    

In [61]:

    

ws = 6500
we = 7000
hs = 6500
he = 7000
img = cv2.imread('images/370fa009f51d3fb97bbf11c3baa01e9c.png')
img_crop = img[ws:we, hs:he]
plt.figure()
plt.imshow(img_crop)

img_bin = cv2.imread('images/1f1e36c93bee4ce4a0db479216db4709.png' )

img_bin_crop = img_bin[ws:we, hs:he]
# cv2.cvtColor(img_bin_crop, cv2.COLOR_BGR2GRAY)
plt.figure()
plt.imshow(img_bin_crop)

cv2.imwrite('images/cropped_image.png',img_crop)
cv2.imwrite('images/cropped_bin.png', img_bin_crop)


    

    
Out[61]:





True






    













    

In [99]:

    

fn_anno = 'images/cropped_bin.png'
anno_rgb = cv2.imread(fn_anno,0).astype(np.uint32)
# anno_rgb[anno_rgb>=125] = 1
plt.imshow(anno_rgb)
print anno_rgb.shape
print np.unique(anno_rgb)


    

    




(500, 500)
[ 0 29]






    

In [101]:

    

plt.figure()
plt.imshow(cv2.imread('images/cropped_image.png'))
plt.figure()
plt.imshow(cv2.imread('images/cropped_bin.png',0), cmap='gray')
plt.figure()
im = cv2.imread('output.png')
print np.unique(im)
plt.imshow(im)


    

    




[0]






    
Out[101]:





<matplotlib.image.AxesImage at 0x7f81f7d5e490>






    













    













    

In [98]:

    

plt.figure()
plt.imshow(cv2.imread('examples/im1.png'))
plt.figure()
anno = cv2.imread('examples/anno1.png',0)
print np.unique(anno)
plt.imshow(anno, cmap='gray')
plt.figure()
im = cv2.imread('out1.png',0)
print np.unique(im)
plt.imshow(im,cmap='gray')


    

    




[  0  50 105]
[37 94]






    
Out[98]:





<matplotlib.image.AxesImage at 0x7f81f7db05d0>