def crop(image_array, direction, n_pixels):
#####################################
##########YOUR CODE GOES HERE########
#####################################
#return output_array
'''
def rgb_to_grayscale(rgb_image_array):
#####################################
##########YOUR CODE GOES HERE########
#####################################
#return output_array
def invert_rgb(image_array):
#####################################
##########YOUR CODE GOES HERE########
#####################################
#return output_array
def gaussian_blur(image_array, sigma=0.84089):
#####################################
##########YOUR CODE GOES HERE########
#####################################
#return output_array
def image_to_drawing(image_array):
#####################################
##########YOUR CODE GOES HERE########
#####################################
#return output_array
'''
if (__name__ == "__main__"):
file = 'robot.png'
lists = flip_image(utilities.image_to_list(file),1)
utilities.write_image(lists, 'new.png')
final.append(row)
return final
def invert_rgb(image_array):
'''
(list) -> (list)
Takes in an rgb image array, and returns the inverted image array.
'''
m = len(image_array) # len rows
n = len(image_array[1][:])
rgim = image_array.copy()
for r in range(m):
for c in range(n):
for i in range(3):
rgim[r][c][i] = 255 - rgim[r][c][i]
return rgim
if (__name__ == "__main__"):
file = 'robot.png'
utilities.write_image(rgb_to_grayscale(
utilities.image_to_list(file)), 'gray.png')
[137, 111, 114],
[127, 105, 108],
[109, 90, 92],
[89, 75, 75],
[83, 73, 72],
[89, 79, 78],
[80, 74, 86],
[81, 75, 87],
[81, 73, 84],
[97, 87, 98],
[124, 112, 122],
[148, 132, 142],
[169, 152, 160],
[196, 175, 182],
[190, 164, 173],
[186, 156, 164],
[166, 135, 141],
[154, 119, 125],
[159, 123, 127],
[160, 121, 126],
[150, 109, 113],
[145, 104, 108],
[133, 92, 90],
[124, 83, 81],
[125, 84, 82],
[144, 103, 101],
[160, 119, 117]]
utilities.write_image(img, 'square.png')
utilities.write_image(crop(img, 'down', 7), 'cropped.png')
utilities.write_image(expected, 'expected.png')
returns an image that has more evenly distributed pixels throughout the image to allow it to have a better contrast level. This only works with grayscale images
examples:
>>>histogram_equalization([[1, 1, 0], [0, 0, 0], [0, 0, 1]])
[[170, 170, 0], [0, 0, 0], [0, 0, 170]]
'''
cdf = [0] * 256
size1 = len(img_array)
size2 = len(img_array[0])
output_array = []
for k in range(0, 256):
cdf.append(0)
for i in range(size1):
output_array.append([])
for j in range(size2):
output_array[i].append([])
cdf[img_array[i][j]] += 1
for i in range(size1):
for j in range(size2):
sum = 0
for k in range(0, img_array[i][j]):
sum += cdf[k]
output_array[i][j] = sum * 255 / size1 / size2
return output_array
if (__name__ == "__main__"):
file = 'gray.png'
img = utilities.image_to_list(file)
img2 = histogram_equalization(img)
utilities.write_image(img2, 'equal2.png')
k += 1
new_row.append(new_set)
new_set = []
j += 1
k = 0
output_array.append(new_row)
new_row = []
i += 1
j = 0
return output_array
'''
def gaussian_blur(image_array, sigma=0.84089):
#####################################
##########YOUR CODE GOES HERE########
#####################################
return output_array
def image_to_drawing(image_array):
#####################################
##########YOUR CODE GOES HERE########
#####################################
return output_array
'''
if (__name__ == "__main__"):
file = 'robot.png'
utilities.write_image(rotate_90_degrees(utilities.image_to_list(file),1), 'clockwise.png')