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2024年2月27日发(作者:java程序设计基础第6版陈国君答案)
('flower class distribution') () return train_images_path, train_images_label, val_images_path, val_images_labeldef plot_data_loader_image(data_loader): batch_size = data__size plot_num = min(batch_size, 4) json_path = './class_' assert (json_path), json_path + " does not exist." json_file = open(json_path, 'r') class_indices = (json_file) for data in data_loader: images, labels = data for i in range(plot_num): # [C, H, W] -> [H, W, C] transpose调整顺序 img = images[i].numpy().transpose(1, 2, 0) #
反Normalize操作 img = (img * [0.229, 0.224, 0.225] + [0.485, 0.456, 0.406]) * 255 label = labels[i].item() t(1, plot_num, i+1) (class_indices[str(label)]) ([]) #
去掉x轴的刻度 ([]) #
去掉y轴的刻度 (('uint8')) ()def write_pickle(list_info: list, file_name: str): with open(file_name, 'wb') as f: (list_info, f)def read_pickle(file_name: str) -> list: with open(file_name, 'rb') as f: info_list = (f) return info_listmydataset
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