image = np.pad(image,((0,0),(diff//2,diff//2)),'constant')
else:
image = np.pad(image,((diff//2,diff//2),(0,0)),'constant')
image = dilation(image,disk(max(sx,sy)/32))
image = misc.imresize(image,(32,32))
if np.max(image) > 1:
image = image/255.
return image
if __name__ == '__main__':
model_path = join(getcwd(), "model", "model.ckpt")
with tf.Session() as sess:
sr = SymbolRecognition(sess, model_path, trainflag=False)
imgFolderPath = getcwd() + sep + "equations"
files = [f for f in listdir(imgFolderPath) if isfile(join(imgFolderPath, f)) and imghdr.what(join(imgFolderPath, f))=='png']
for fname in files:
# fname='./equations/SKMBT_36317040717260_eq16.png'
print fname
seg = Segmentation(join(imgFolderPath, fname))
d = seg.get_labels()
mst = MinimumSpanningTree(d).get_mst()
pa = Partition(mst,seg,sess,sr)
print pa.getList()
pa.calculateCount()
print pa.getCount()
# for label in seg.labels.keys():
# # print label
# stroke = seg.get_stroke(label)
# scipy.misc.imsave('./tmp/'+ str(label)+'.png', stroke)
