unaligned_data_loader.py 文件源码

def load_image_for_prediction(opt, image_path):
    """
    load image for prediction, pre process as the same of train, and also return a dict
    :param opt:
    :param image_path:
    :return:
    """
    image = Image.open(image_path)
    transformations = transforms.Compose([transforms.Scale(opt.loadSize),
                                          transforms.RandomCrop(opt.fineSize),
                                          transforms.ToTensor(),
                                          transforms.Normalize((0.5, 0.5, 0.5),
                                                               (0.5, 0.5, 0.5))])
    image_tensor = transformations(image).float()
    image_tensor.unsqueeze_(0)
    return {'A': image_tensor, 'A_paths': image_path,
            'B': image_tensor, 'B_paths': image_path}