def select_image(): # grab a reference to the image panels global panelA, panelB # open a file chooser dialog and allow the user to select an input # image path = tkFileDialog.askopenfilename() # ensure a file path was selected if len(path) > 0: # load the image from disk, convert it to grayscale, and detect # edges in it image = t.readImage(path) shortestPath = t.solveMaze(image, (0,0), (19,19), 20, 20) img = image_enhancer.highlightPath(image, (0,0), (19,19), shortestPath) # convert the images to PIL format... image = Image.fromarray(image) edged = Image.fromarray(img) # ...and then to ImageTk format image = ImageTk.PhotoImage(image) edged = ImageTk.PhotoImage(edged) # if the panels are None, initialize them if panelA is None or panelB is None: # the first panel will store our original image panelA = Label(image=image) panelA.image = image panelA.pack(side="left", padx=10, pady=10) # while the second panel will store the edge map panelB = Label(image=edged) panelB.image = edged panelB.pack(side="right", padx=10, pady=10) # otherwise, update the image panels else: # update the pannels panelA.configure(image=image) panelB.configure(image=edged) panelA.image = image panelB.image = edged
CELL_SIZE) # number of cells in height of maze image
no_cells_width = int(width /
CELL_SIZE) # number of cells in width of maze image
initial_point = (0, 0) # start point coordinates of maze
final_point = ((no_cells_height - 1), (no_cells_width - 1)
) # end point coordinates of maze
try:
shortestPath = solveMaze(original_binary_img, initial_point,
final_point, no_cells_height, no_cells_width)
if len(shortestPath) > 2:
img = image_enhancer.highlightPath(original_binary_img,
initial_point, final_point,
shortestPath)
else:
print(
'\n[ERROR] shortestPath returned by solveMaze function is not complete !\n'
)
exit()
except TypeError as type_err:
print(
'\n[ERROR] solveMaze function is not returning shortest path in maze image in expected format !\n'
)
exit()
def isInPath(i, j, shortestPath, cell_img):
#########################################################################
# NOTE: YOU ARE NOT ALLOWED TO MAKE ANY CHANGE TO THIS FUNCTION
#
# Function Name: main
# Inputs: None
# Outputs: None
# Purpose: the function first takes 'maze00.jpg' as input and solves the maze by calling computeSum
# function, it then asks the user whether to repeat the same on all maze images
# present in 'task_1c_images' folder or not
if __name__ != '__main__':
curr_dir_path = os.getcwd()
# Importing task_1a and image_enhancer script
try:
task_1a_dir_path = curr_dir_path + '/../../Task 1A/codes'
sys.path.append(task_1a_dir_path)
import task_1a
import image_enhancer
except Exception as e:
print('\ntask_1a.py or image_enhancer.pyc file is missing from Task 1A folder !\n')
exit()
if __name__ == '__main__':
curr_dir_path = os.getcwd()
img_dir_path = curr_dir_path + '/../task_1c_images/' # path to directory of 'task_1c_images'
file_num = 0
img_file_path = img_dir_path + 'maze0' + str(file_num) + '.jpg' # path to 'maze00.jpg' image file
# Importing task_1a and image_enhancer script
try:
task_1a_dir_path = curr_dir_path + '/../../Task 1A/codes'
sys.path.append(task_1a_dir_path)
import task_1a
import image_enhancer
except Exception as e:
print('\n[ERROR] task_1a.py or image_enhancer.pyc file is missing from Task 1A folder !\n')
exit()
# modify the task_1a.CELL_SIZE to 40 since maze images
# in task_1c_images folder have cell size of 40 pixels
task_1a.CELL_SIZE = 40
print('\n============================================')
print('\nFor maze0' + str(file_num) + '.jpg')
try:
original_binary_img = task_1a.readImage(img_file_path)
height, width = original_binary_img.shape
except AttributeError as attr_error:
print('\n[ERROR] readImage function is not returning binary form of original image in expected format !\n')
exit()
no_cells_height = int(height/task_1a.CELL_SIZE) # number of cells in height of maze image
no_cells_width = int(width/task_1a.CELL_SIZE) # number of cells in width of maze image
initial_point = (0, 0) # start point coordinates of maze
final_point = ((no_cells_height-1),(no_cells_width-1)) # end point coordinates of maze
try:
shortestPath = task_1a.solveMaze(original_binary_img, initial_point, final_point, no_cells_height, no_cells_width)
if len(shortestPath) > 2:
img = image_enhancer.highlightPath(original_binary_img, initial_point, final_point, shortestPath)
else:
print('\n[ERROR] shortestPath returned by solveMaze function is not complete !\n')
exit()
except TypeError as type_err:
print('\n[ERROR] solveMaze function is not returning shortest path in maze image in expected format !\n')
exit()
print('\nShortest Path = %s \n\nLength of Path = %d' % (shortestPath, len(shortestPath)))
digits_list, digits_on_path, sum_of_digits_on_path = computeSum(img_file_path, shortestPath)
print('\nDigits in the image = ', digits_list)
print('\nDigits on shortest path in the image = ', digits_on_path)
print('\nSum of digits on shortest path in the image = ', sum_of_digits_on_path)
print('\n============================================')
cv2.imshow('canvas0' + str(file_num), img)
cv2.waitKey(0)
cv2.destroyAllWindows()
choice = input('\nWant to run your script on all maze images ? ==>> "y" or "n": ')
if choice == 'y':
file_count = len(os.listdir(img_dir_path))
for file_num in range(file_count):
img_file_path = img_dir_path + 'maze0' + str(file_num) + '.jpg' # path to 'maze00.jpg' image file
print('\n============================================')
print('\nFor maze0' + str(file_num) + '.jpg')
try:
original_binary_img = task_1a.readImage(img_file_path)
height, width = original_binary_img.shape
except AttributeError as attr_error:
print('\n[ERROR] readImage function is not returning binary form of original image in expected format !\n')
exit()
no_cells_height = int(height/task_1a.CELL_SIZE) # number of cells in height of maze image
no_cells_width = int(width/task_1a.CELL_SIZE) # number of cells in width of maze image
initial_point = (0, 0) # start point coordinates of maze
final_point = ((no_cells_height-1),(no_cells_width-1)) # end point coordinates of maze
try:
shortestPath = task_1a.solveMaze(original_binary_img, initial_point, final_point, no_cells_height, no_cells_width)
if len(shortestPath) > 2:
img = image_enhancer.highlightPath(original_binary_img, initial_point, final_point, shortestPath)
else:
print('\n[ERROR] shortestPath returned by solveMaze function is not complete !\n')
exit()
except TypeError as type_err:
print('\n[ERROR] solveMaze function is not returning shortest path in maze image in expected format !\n')
exit()
print('\nShortest Path = %s \n\nLength of Path = %d' % (shortestPath, len(shortestPath)))
digits_list, digits_on_path, sum_of_digits_on_path = computeSum(img_file_path, shortestPath)
print('\nDigits in the image = ', digits_list)
print('\nDigits on shortest path in the image = ', digits_on_path)
print('\nSum of digits on shortest path in the image = ', sum_of_digits_on_path)
print('\n============================================')
cv2.imshow('canvas0' + str(file_num), img)
cv2.waitKey(0)
cv2.destroyAllWindows()
else:
print('')
