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Python調(diào)整圖像hue值結(jié)合ImageEnhance庫(kù)以實(shí)現(xiàn)色調(diào)增強(qiáng)

更新時(shí)間：2023年09月23日 09:45:50 作者：TracelessLe

這篇文章主要介紹了Python調(diào)整圖像hue值結(jié)合ImageEnhance庫(kù)以實(shí)現(xiàn)色調(diào)增強(qiáng),PIL庫(kù)中的ImageEnhance類(lèi)可用于圖像增強(qiáng),可以調(diào)節(jié)圖像的亮度、對(duì)比度、色度和銳度,通過(guò)RGB到HSV的變換加調(diào)整可以對(duì)圖像的色調(diào)進(jìn)行調(diào)整,需要的朋友可以參考下

前言

PIL庫(kù)中的ImageEnhance類(lèi)可用于圖像增強(qiáng)，可以調(diào)節(jié)圖像的亮度、對(duì)比度、色度和銳度。

在這里插入圖片描述

通過(guò)RGB到HSV的變換加調(diào)整可以對(duì)圖像的色調(diào)進(jìn)行調(diào)整。兩種方法結(jié)合可以達(dá)到更大程度的圖像色調(diào)增強(qiáng)。

調(diào)整hue值

__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.)  # 調(diào)整hue值
out.save('out.png')

其中 hueChange 方法實(shí)現(xiàn)如下：

__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 arrays 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 arrays 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')

基于ImageEnhance方法調(diào)節(jié)圖像色度

在這里插入圖片描述

__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')

合并操作

__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 arrays 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 arrays 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')

到此這篇關(guān)于Python調(diào)整圖像hue值結(jié)合ImageEnhance庫(kù)以實(shí)現(xiàn)色調(diào)增強(qiáng)的文章就介紹到這了,更多相關(guān)ImageEnhance庫(kù)實(shí)現(xiàn)色調(diào)增強(qiáng)內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！

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