编程实现图像变暗，图像变亮，降低对比度，gamma变换代码

在编程中，特别是Python中，可以使用PIL（Pillow）库来进行图像处理。以下是一些基本操作的代码示例：

1. 图像变暗 (Brightness Decrease)：

from PIL import Image, ImageEnhance

def darken_image(image_path, factor=0.5):
    img = Image.open(image_path)
    enhancer = ImageEnhance.Brightness(img)
    dark_img = enhancer.enhance(factor)
    return dark_img.save('darkened_' + image_path)

# 使用
darken_image('original.jpg')

2. 图像变亮 (Brightness Increase):

def brighten_image(image_path, factor=1.5):
    # ... 相同的过程，只是enhance函数传入的是factor大于1的值
    enhancer = ImageEnhance.Brightness(img)
    bright_img = enhancer.enhance(factor)
    return bright_img.save('brightened_' + image_path)

3. 降低对比度 (Reduce Contrast):

def reduce_contrast(image_path, factor=0.5):
    img = Image.open(image_path)
    enhancer = ImageEnhance.Contrast(img)
    low_contrast_img = enhancer.enhance(factor)
    return low_contrast_img.save('low_contrast_' + image_path)

4. Gamma变换 (Non-linear contrast adjustment):

import cv2
import numpy as np

def gamma_correction(image_path, gamma=0.5):
    img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
    inv_gamma = 1.0 / gamma
    table = np.array([((i / 255.0) ** inv_gamma) * 255 for i in np.arange(0, 256)]).astype("uint8")
    corrected_img = cv2.LUT(img, table)
    return cv2.imwrite('corrected_' + image_path, corrected_img)

每个函数都需要对应的图片文件路径，并可以根据需要调整因素值。