def main():
global element
global left_side_pixel_value
global list_of_sides_white , list_of_pixels , average_of_pixels
list_of_sides = side_extractor_final_aug24.main()
file2 = []
global img
for i in list_of_sides:
file2.append(i)
#print("file2: " , file2)
#print(list_of_sides)
#print(list_of_sides['Piece_4.png'])
images, file1 = load_images_from_folder("Puzzle_pieces/White")
#print("file1: " , file1)
for i in range(len(file1)):
list_of_sides_white = keys_swap(file2[i], file1[i], list_of_sides)
#print(list_of_sides_white)
#print("list of sides: " , list_of_sides_white['Piece_1.png'])
count = 0
for image in images:
img = read_image(image)
print(img)
element = var_return(list_of_sides_white)
#print(element)
elm = file1[count]
#elm = "'%s'" %(element[count])
#print(elm)
left_side_pixel_value = pixel_extraction_left(img , elm)
left_side_pixel_value = np.array(left_side_pixel_value)
mean_left_side = np.mean(left_side_pixel_value , axis=0)
top_side_pixel_value = pixel_extraction_top(img , elm)
top_side_pixel_value = np.array(top_side_pixel_value)
mean_top_side = np.mean(top_side_pixel_value , axis=0)
right_side_pixel_value = pixel_extraction_right(img , elm)
right_side_pixel_value = np.array(right_side_pixel_value)
mean_right_side = np.mean(right_side_pixel_value , axis=0)
bottom_side_pixel_value = pixel_extraction_bottom(img , elm)
bottom_side_pixel_value = np.array(bottom_side_pixel_value)
mean_bottom_side = np.mean(bottom_side_pixel_value , axis=0)
#print(left_side_pixel_value)
#print("%s : %s " % (elm, left_side_pixel_value))
total = [left_side_pixel_value , top_side_pixel_value , right_side_pixel_value, bottom_side_pixel_value]
list_of_pixels.update({elm:total})
total_pixel_average = [mean_left_side , mean_top_side , mean_right_side , mean_bottom_side]
average_of_pixels.update({elm:total_pixel_average})
#print(top_side_pixel_value)
#print(right_side_pixel_value)
#print(bottom_side_pixel_value)
count = count +1
#print(list_of_pixels)
print(average_of_pixels)
def main():
global element
global left_side_pixel_value
global list_of_sides_white
list_of_sides = side_extractor_final_aug24.main()
file2 = []
global img
for i in list_of_sides:
file2.append(i)
#print("file2: " , file2)
#print(list_of_sides)
#print(list_of_sides['Piece_4.png'])
images, file1 = load_images_from_folder("Puzzle_pieces/White")
#print("file1: " , file1)
for i in range(len(file1)):
list_of_sides_white = keys_swap(file2[i], file1[i], list_of_sides)
#print(list_of_sides_white)
#print("list of sides: " , list_of_sides_white['Piece_1.png'])
count = 0
for image in images:
img = read_image(image)
element = var_return(list_of_sides_white)
print(element)
#elm = '%s' % element[count]
elm = '%s' % (element[count])
print(elm)
left_side_pixel_value = pixel_extraction_left(img, list_of_sides_white,
elm)
top_side_pixel_value = pixel_extraction_top(img, list_of_sides_white,
elm)
right_side_pixel_value = pixel_extraction_right(
img, list_of_sides_white, elm)
bottom_side_pixel_value = pixel_extraction_bottom(
img, list_of_sides_white, elm)
count = count + 1
print(left_side_pixel_value)
def main():
global element
global left_side_pixel_value
global list_of_sides_white, list_of_pixels, average_of_pixels
list_of_sides = side_extractor_final_aug24.main()
file2 = []
global img
for i in list_of_sides:
file2.append(i)
#print("file2: " , file2)
#print(list_of_sides)
#print(list_of_sides['Piece_4.png'])
images, file1 = load_images_from_folder("Puzzle_pieces/White")
#print("file1: " , file1)
for i in range(len(file1)):
list_of_sides_white = keys_swap(file2[i], file1[i], list_of_sides)
#print(list_of_sides_white)
#print("list of sides: " , list_of_sides_white['Piece_1.png'])
count = 0
for image in images:
img = read_image(image)
print(img)
element = var_return(list_of_sides_white)
#print(element)
elm = file1[count]
#elm = "'%s'" %(element[count])
#print(elm)
left_side_pixel_value = pixel_extraction_left(img, elm)
left_side_pixel_value = np.array(left_side_pixel_value)
mean_left_side = np.mean(left_side_pixel_value, axis=0)
#mean_left_side = mean_left_side.astype(float)
mean_left_side = mean_left_side[~np.isnan(mean_left_side)]
top_side_pixel_value = pixel_extraction_top(img, elm)
top_side_pixel_value = np.array(top_side_pixel_value)
mean_top_side = np.mean(top_side_pixel_value, axis=0)
#mean_top_side = mean_top_side.astype(float)
mean_top_side = mean_top_side[~np.isnan(mean_top_side)]
right_side_pixel_value = pixel_extraction_right(img, elm)
right_side_pixel_value = np.array(right_side_pixel_value)
mean_right_side = np.mean(right_side_pixel_value, axis=0)
#mean_right_side =mean_right_side.astype(float)
mean_right_side = mean_right_side[~np.isnan(mean_right_side)]
bottom_side_pixel_value = pixel_extraction_bottom(img, elm)
bottom_side_pixel_value = np.array(bottom_side_pixel_value)
mean_bottom_side = np.mean(bottom_side_pixel_value, axis=0)
#mean_bottom_side= mean_bottom_side.astype(float)
mean_bottom_side = mean_bottom_side[~np.isnan(mean_bottom_side)]
#print(left_side_pixel_value)
#print("%s : %s " % (elm, left_side_pixel_value))
total = [
left_side_pixel_value, top_side_pixel_value,
right_side_pixel_value, bottom_side_pixel_value
]
list_of_pixels.update({elm: total})
total_pixel_average = [
mean_left_side, mean_top_side, mean_right_side, mean_bottom_side
]
average_of_pixels.update({elm: total_pixel_average})
#print(top_side_pixel_value)
#print(right_side_pixel_value)
#print(bottom_side_pixel_value)
count = count + 1
#print(list_of_pixels)
print(average_of_pixels)
#average_of_pixels =
matching_pixels = {}
pixel_matching_list = []
for item in average_of_pixels.items():
#print(item[0][1])
pixel_matching_list.append(item)
print('pixel matching list', pixel_matching_list)
for j in range(len(pixel_matching_list)):
#A=[]
A = [
pixel_matching_list[j][1][0], pixel_matching_list[j][1][1],
pixel_matching_list[j][1][2], pixel_matching_list[j][1][3]
]
for k in A:
if len(k) == 0:
del k
print('A', A)
#A = A.tolist()
#print(A[1][0])
for i in range(0, len(pixel_matching_list) - 1):
W = [
np.array(0.05 * np.array(pixel_matching_list[i][1][0])),
np.array(0.05 * np.array(pixel_matching_list[i][1][1])),
np.array(0.1 * np.array(pixel_matching_list[i][1][2])),
np.array(0.3 * np.array(pixel_matching_list[i][1][3]))
]
D = [
np.subtract((pixel_matching_list[i][1][0]), W[0]),
np.subtract((pixel_matching_list[i][1][1]), W[1]),
np.subtract((pixel_matching_list[i][1][2]), W[2]),
np.subtract((pixel_matching_list[i][1][3]), W[3])
]
E = [
np.add((pixel_matching_list[i][1][0]), W[0]),
np.add((pixel_matching_list[i][1][1]), W[1]),
np.add((pixel_matching_list[i][1][2]), W[2]),
np.add((pixel_matching_list[i][1][3]), W[3])
]
if len(pixel_matching_list[i][1][0]) == 0 or len(
pixel_matching_list[i + 1][1][0]) == 0:
continue
#elif np.all(pixel_matching_list[i][1][0]) == np.all(A[0]) or np.all(pixel_matching_list[i][1][1]) == np.all(A[1]) or np.all(pixel_matching_list[i][1][2]) == np.all(A[2]) or np.all(pixel_matching_list[i][1][3]) == np.all(A[3]) :
#continue
else:
print('D', D)
print('A', A)
print(len(D))
print(len(A))
for k in range(len(A)):
for m in range(len(D)):
#A[k] = [A[k].remove(x) for x in A[k] if []]
#print(A[k])
#A[k][0]= A[k][0].astype(int)
#print(A[k].shape)
if len(A[k]) == 0 or len(D[m]) == 0 or len(E[m]) == 0:
continue
#print('D[m][0]' , D[m][0])
#print('A[k][0]' , A[k][0])
#print('E[m][0]' , E[m][0])
#print('D[m][1]' , D[m][1])
#print('A[k][1]' , A[k][1])
#print('E[m][1]' , E[m][1])
#print('D[m][2]' , D[m][2])
#print('A[k][2]' , A[k][2])
#print('E[m][2]' , E[m][2])
elif (D[m][0] <= A[k][0] <= E[m][0]) and (
D[m][1] <= A[k][1] <=
E[m][1]) and (D[m][2] <= A[k][2] <= E[m][2]):
print('success')
matching_pixels.update({
pixel_matching_list[j][0]:
A[k],
pixel_matching_list[i][0]:
pixel_matching_list[i][1][m]
})
print(matching_pixels)
print(matching_pixels)