代码： import cv2 import torchvision.transforms as transforms import torch to_tensor = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.485,0.456,0.406), (0.229, 0.224,0.225)) ]) filename1 = "modelSegmentation.pt" model = torch.jit.load(filename1) model.eval() image = cv2.imread('a.jpg') H, W = image.shape[:2] image = cv2.resize(image, (512, 512), cv2.INTER_AREA) origin_image = image.copy() image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) image = to_tensor(image).unsqueeze(0) output = model(image) print(output.size()) label = output.argmax(1) \ .repeat(3, 1, 1) \ .to(dtype=torch.uint8) \ .permute((1, 2, 0)) \ .numpy() origin_image *= label origin_image[label == 0] = 255 origin_image = cv2.resize(origin_image, (W, H), cv2.INTER_CUBIC) cv2.imshow('test', origin_image) cv2.waitKey() 结果：