def start(filename):
print "filename is ", filename
#filename = "53.jpg"
try:
img = cv2.imread(filename, 0)
plt.imshow(img, 'gray') #original image
plt.show()
except:
print "oops! unable to open image, try again"
import pathgui
return
print "Before preprocess"
image_object = ip.image_processing(img)
print "After preprocess object"
image_object.preprocess()
print "After preprocessing"
image_object.find_contour()
plt.imshow(image_object.canvas, 'gray')
plt.show()
print "After contour"
image_object.find_corners()
print "After corners"
image_object.straighten_image()
print "After straight image"
sudoku_grid = image_object.isolate_digits()
image_object.print_grid()
solver_object = ss.solve_sudoku(sudoku_grid)
print "The given sudoku grid has ", solver_object.count, " solutions."
if solver_object.count > 0:
image_object.paint_image(solver_object.all[0])
plt.imshow(image_object.original_img, 'gray') #output
plt.show()
import pathgui
#start("1.JPG")
import preprocessing as ppr
import os
#Parameters
raw_data = 'rawdata'
data_path = 'data'
height = 100
width = 100
if not os.path.exists(data_path):
ppr.image_processing(raw_data, data_path, height, width)
all_classes = os.listdir(data_path)
number_of_classes = len(all_classes)
color_channels = 3
epochs = 300
batch_size = 10
batch_counter = 0
model_save_name = 'checkpoints/'
def main():
train_gen, test_gen = image_processing()
classifier(train_gen, test_gen)
def build_seq_with_processing(self, frames, shape, BW):
'''Frames is a list of paths to the frames of a given video'''
return [
image_processing(img, self.image_shape, as_BW=BW) for img in frames
]