Foreword
The ImageEnhance class in the PIL library can be used for image enhancement, which can adjust the brightness, contrast, hue and sharpness of the image.
The hue of the image can be adjusted by converting from RGB to HSV and adjusting.
The combination of the two methods can achieve a greater degree of image tone enhancement.
Adjust hue value
__author__ = 'TracelessLe'
__website__ = 'https://blog.csdn.net/TracelessLe'
import numpy as np
from PIL import Image, ImageEnhance
filename = 'test.png'
pil_img = Image.open(filename).convert('RGB')
hue = np.random.randint(0, 360)
out = hueChange(pil_img, hue/360.) # adjust the hue value
out.save('out.png')
The hueChange method is implemented as follows:
__author__ = 'TracelessLe'
__website__ = 'https://blog.csdn.net/TracelessLe'
import numpy as np
from PIL import Image
def rgb_to_hsv(rgb):
# Translated from source of colorsys.rgb_to_hsv
# r,g,b should be a numpy array with values between 0 and 255
# rgb_to_hsv returns an array of floats between 0.0 and 1.0.
rgb = rgb.astype('float')
hsv = np.zeros_like(rgb)
# in case an RGBA array was passed, just copy the A channel
hsv[..., 3:] = rgb[..., 3:]
r, g, b = rgb[..., 0], rgb[..., 1], rgb[..., 2]
maxc = np.max(rgb[..., :3], axis=-1)
minc = np.min(rgb[..., :3], axis=-1)
hsv[..., 2] = maxc
mask = maxc != minc
hsv[mask, 1] = (maxc - minc)[mask] / maxc[mask]
rc = np.zeros_like(r)
gc = np.zeros_like(g)
bc = np.zeros_like(b)
rc[mask] = (maxc - r)[mask] / (maxc - minc)[mask]
gc[mask] = (maxc - g)[mask] / (maxc - minc)[mask]
bc[mask] = (maxc - b)[mask] / (maxc - minc)[mask]
hsv[..., 0] = np. select(
[r == maxc, g == maxc], [bc - gc, 2.0 + rc - bc], default=4.0 + gc - rc)
hsv[..., 0] = (hsv[..., 0] / 6.0) % 1.0
return hsv
def hsv_to_rgb(hsv):
# Translated from source of colorsys.hsv_to_rgb
# h,s should be a numpy array with values between 0.0 and 1.0
# v should be a numpy array with values between 0.0 and 255.0
# hsv_to_rgb returns an array of uints between 0 and 255.
rgb = np.empty_like(hsv)
rgb[..., 3:] = hsv[..., 3:]
h, s, v = hsv[..., 0], hsv[..., 1], hsv[..., 2]
i = (h * 6.0).astype('uint8')
f = (h * 6.0) - i
p = v * (1.0 - s)
q = v * (1.0 - s * f)
t = v * (1.0 - s * (1.0 - f))
i = i % 6
conditions = [s == 0.0, i == 1, i == 2, i == 3, i == 4, i == 5]
rgb[..., 0] = np. select(conditions, [v, q, p, p, t, v], default=v)
rgb[..., 1] = np. select(conditions, [v, v, v, q, p, p], default=t)
rgb[..., 2] = np. select(conditions, [v, p, t, v, v, q], default=p)
return rgb.astype('uint8')
def hueChange(img, hue):
arr = np.array(img)
hsv = rgb_to_hsv(arr)
hsv[..., 0] = hue
rgb = hsv_to_rgb(hsv)
return Image.fromarray(rgb, 'RGB')
See reference [1] for the principle of hue adjustment based on the hue value.
The source code here can be found in reference [2].
Adjust image chroma based on ImageEnhance method
__author__ = 'TracelessLe'
__website__ = 'https://blog.csdn.net/TracelessLe'
import random
import numpy as np
from PIL import Image, ImageEnhance
filename = 'test.png'
pil_img = Image.open(filename).convert('RGB')
enh_col = ImageEnhance.Color(pil_img)
factor = random. random() * 1.0 + 0.5
out = enh_col.enhance(factor)
out.save('out.png')
Merge operation
__author__ = 'TracelessLe'
__website__ = 'https://blog.csdn.net/TracelessLe'
import random
import numpy as np
from PIL import Image, ImageEnhance
def rgb_to_hsv(rgb):
# Translated from source of colorsys.rgb_to_hsv
# r,g,b should be a numpy array with values between 0 and 255
# rgb_to_hsv returns an array of floats between 0.0 and 1.0.
rgb = rgb.astype('float')
hsv = np.zeros_like(rgb)
# in case an RGBA array was passed, just copy the A channel
hsv[..., 3:] = rgb[..., 3:]
r, g, b = rgb[..., 0], rgb[..., 1], rgb[..., 2]
maxc = np.max(rgb[..., :3], axis=-1)
minc = np.min(rgb[..., :3], axis=-1)
hsv[..., 2] = maxc
mask = maxc != minc
hsv[mask, 1] = (maxc - minc)[mask] / maxc[mask]
rc = np.zeros_like(r)
gc = np.zeros_like(g)
bc = np.zeros_like(b)
rc[mask] = (maxc - r)[mask] / (maxc - minc)[mask]
gc[mask] = (maxc - g)[mask] / (maxc - minc)[mask]
bc[mask] = (maxc - b)[mask] / (maxc - minc)[mask]
hsv[..., 0] = np. select(
[r == maxc, g == maxc], [bc - gc, 2.0 + rc - bc], default=4.0 + gc - rc)
hsv[..., 0] = (hsv[..., 0] / 6.0) % 1.0
return hsv
def hsv_to_rgb(hsv):
# Translated from source of colorsys.hsv_to_rgb
# h,s should be a numpy array with values between 0.0 and 1.0
# v should be a numpy array with values between 0.0 and 255.0
# hsv_to_rgb returns an array of uints between 0 and 255.
rgb = np.empty_like(hsv)
rgb[..., 3:] = hsv[..., 3:]
h, s, v = hsv[..., 0], hsv[..., 1], hsv[..., 2]
i = (h * 6.0).astype('uint8')
f = (h * 6.0) - i
p = v * (1.0 - s)
q = v * (1.0 - s * f)
t = v * (1.0 - s * (1.0 - f))
i = i % 6
conditions = [s == 0.0, i == 1, i == 2, i == 3, i == 4, i == 5]
rgb[..., 0] = np. select(conditions, [v, q, p, p, t, v], default=v)
rgb[..., 1] = np. select(conditions, [v, v, v, q, p, p], default=t)
rgb[..., 2] = np. select(conditions, [v, p, t, v, v, q], default=p)
return rgb.astype('uint8')
def hueChange(img, hue):
arr = np.array(img)
hsv = rgb_to_hsv(arr)
hsv[..., 0] = hue
rgb = hsv_to_rgb(hsv)
return Image.fromarray(rgb, 'RGB')
if __name__ == "__main__":
filename = 'test.png'
pil_img = Image.open(filename).convert('RGB')
hue = np.random.randint(0, 360)
pil_img2 = hueChange(pil_img, hue/360.)
enh_col = ImageEnhance.Color(pil_img2)
factor = random. random() * 1.0 + 0.5
out = enh_col.enhance(factor)
out.save('out.png')
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References
[1] Image color knowledge and python to achieve image tone conversion – Know about
[2] RGB to HSV Python, change Hue continuously – Stack Overflow
[3] [python image processing] image enhancement (Detailed explanation of ImageEnhance class)_PHILOS_THU’s Blog-CSDN Blog
[4] How to use Python to change the color of photos_VIP_CQCRE’s Blog-CSDN Blog
[5] ImageEnhance Module – Pillow (PIL Fork) 9.5.0 documentation