python图像代码

引用:记录几段常用的图像处理python代码 非原创，基本都是把网上代码修修改改，增加了批处理等输入输出 图像处理相关 图像叠加 。 引用:将某目录下两张命名一致的jpg和png图像按照一定权重叠加，叠加后图片输出在当前目录下 import cv2 import numpy as np import os # 需要输入图像的路径 path = "../eval" for _image in os.listdir(path): if _image.split('.') == "jpg": # 将同名的jpg和png文件进行叠加 image_jpg = os.path.join(path, _image) _image_png = _image.split('.') ".png" image_png = os.path.join(path, _image_png) img_a = cv2.imread(image_jpg) img_b = cv2.imread(image_png) # 图像叠加权重 weight = 0.4 img_a = cv2.resize(img_a, (img_b.shape, img_b.shape)) img_c = weight * img_b (1 - weight) * img_a img_c = img_c.astype(np.uint8) img_c = np.clip(img_c, 0, 255) # 文件名前加result，输出在本目录下 cv2.imwrite("result" _image_png, img_c) 。 引用:https://blog.csdn.net/jacke121/article/details/106630957 求路径下所有图像的平均图 import cv2 import numpy as np import os # 需要输入图像的路径，需保证路径下所有图像尺度一致 path = "./1/" count = 1 img_b = None for _image in os.listdir(path): print(_image) image_jpg = os.path.join(path, _image) img_a = cv2.imread(image_jpg) img_a = img_a.astype(np.float32) if img_b is None: img_b = img_a continue img_b = img_b img_a count = count 1 img_b = img_b / count img_b = img_b.astype(np.uint8) img_b = np.clip(img_b, 0, 255) # 输出在本目录下 cv2.imwrite("result.png", img_b) 。