def adjust_contrast(image, factor, mid):
# adjust the contrast by increasing the difference from the user-defined midpoint by factor amount
x_pixels, y_pixels, num_channels = image.array.shape # represents x, y pixels of image, # channels (R, G, B)
new_im = Image(
x_pixels=x_pixels, y_pixels=y_pixels,
num_channels=num_channels) # making a new array to copy values to!
new_im.array = (image.array - mid) * factor + mid
return new_im
def brighten(image, factor):
x_pixels, y_pixels, num_channels = image.array.shape
new_image = Image(x_pixels=x_pixels,
y_pixels=y_pixels,
num_channels=num_channels)
#for x in range(x_pixels):
# for y in range(y_pixels):
# for c in range(num_channels):
# new_image.array[x, y, c] = image.array[x, y, c] * factor
new_image.array = image.array * factor
return new_image
def adjust_contrast(image, factor, mid=0.5):
# adjust the contrast by increasing the difference from the user-defined
# midpoint by factor amount
x_pixels, y_pixels, num_channels = image.array.shape
new_im = Image(x_pixels=x_pixels, y_pixels=y_pixels, num_channels=num_channels)
for x in range(x_pixels):
for y in range(y_pixels):
for c in range(num_channels):
new_im.array[x, y, c] = (image.array[x, y, c ] - mid) * factor + mid
new_im.array = (image.array - mid) * factor + mid
return new_im
def brighten(image, factor):
# when we brighten, we just want to make each channel higher by some amount
# factor is a value > 0, how much you want to brighten the image by (< 1 = darken, > 1 = brighten)
x_pixels, y_pixels, num_channels = image.array.shape # represents x, y pixels of image, # channels (R, G, B)
# make new image to prevent change to the previous one
new_im = Image(
x_pixels=x_pixels, y_pixels=y_pixels,
num_channels=num_channels) # making a new array to copy values to!
# vectorized version using numpy
new_im.array = image.array * factor
return new_im
def adjust_brightness(image, factor):
# when we brighten, we just want to make each channel higher by some amount
# factor is a value > 0, how much you want to brighten the image by (< 1 = darken, > 1 = brighten)
x_pixels, y_pixels, num_channels = image.array.shape
new_im = Image(x_pixels=x_pixels, y_pixels=y_pixels, num_channels=num_channels)
# for x in range(x_pixels):
# for y in range(y_pixels):
# for c in range(num_channels):
# new_im.array[x, y, c] = image.array[x, y, c ] * factor
# vectorized version
new_im.array = image.array * factor
return new_im
def brighten(image, factor):
# when we brighten, we just want to make each channel higher by some amount
# factor is a value > 0, how much you want to brighten the image by (< 1 = darken, > 1 = brighten)
x_pixels, y_pixels, num_channels = image.array.shape # represents x, y pixels of image, # channels (R, G, B)
new_im = Image(
x_pixels=x_pixels, y_pixels=y_pixels,
num_channels=num_channels) # making a new array to copy values to!
# # this is the non vectorized version
# for x in range(x_pixels):
# for y in range(y_pixels):
# for c in range(num_channels):
# new_im.array[x, y, c] = image.array[x, y, c] * factor
# faster version that leverages numpy
new_im.array = image.array * factor
return new_im
def adjust_brightness(image, factor):
# when we brighten, we just want to make each channel higher by some amount
# factor is a value > 0, how much you want to brighten the image by (< 1 = darken, > 1 = brighten)
x_pixels, y_pixels, num_channels = image.array.shape
# make an empty image so we don't actually modify the original one
new_im = Image(x_pixels=x_pixels,
y_pixels=y_pixels,
num_channels=num_channels)
# this is the most intuitive way to do this (non-vectorized)
# for x in range(x_pixels):
# for y in range(y_pixels):
# for c in range(num_channels):
# new_im.array[x, y, c] = image.array[x, y, c] * factor
# vectorized version
new_im.array = image.array * factor
return new_im
