代码实现图像的批量光照增强

批量光照增强可以通过数据增强来实现。下面是一个使用Python和OpenCV库实现的示例[代码](https://geek.csdn.net/educolumn/1572ef9b473b4e00f6b2bf6d428b7c27?spm=1055.2569.3001.10083)： ```python import cv2 import os # 设置光照增强的参数 gamma = 1.5 # 定义光照增强[函数](https://geek.csdn.net/educolumn/ba94496e6cfa8630df5d047358ad9719?dp_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpZCI6NDQ0MDg2MiwiZXhwIjoxNzA3MzcxOTM4LCJpYXQiOjE3MDY3NjcxMzgsInVzZXJuYW1lIjoid2VpeGluXzY4NjQ1NjQ1In0.RrTYEnMNYPC7AQdoij4SBb0kKEgHoyvF-bZOG2eGQvc&spm=1055.2569.3001.10083) def adjust_gamma([image](https://geek.csdn.net/educolumn/1defff92b42756fda40b623df99f03da?spm=1055.2569.3001.10083), gamma=1.0): invGamma = 1.0 / gamma table = [] for i in range(256): table.append(((i / 255.0) ** invGamma) * 255) table = np.array(table).[ast](https://geek.csdn.net/educolumn/1d2c256574d93ae646d4473629b198e6?spm=1055.2569.3001.10083)ype("uint8") return cv2.LUT(image, table) # 定义图像路径 image_path = 'your_image_folder_path' # 遍历图像文件夹中的所有图像文件进行光照增强 for filename in os.listdir(image_path): image = cv2.imread(os.path.join(image_path, filename)) # 对图像进行光照增强 image_gamma = adjust_gamma(image, gamma=gamma) # 保存光照增强后的图像 cv2.imwrite(os.path.join(image_path, 'gamma_' + filename), image_gamma) 在这个示例[代码](https://geek.csdn.net/educolumn/1572ef9b473b4e00f6b2bf6d428b7c27?spm=1055.2569.3001.10083)中，我们首