| import cv2 | |
| import h5py | |
| import copy | |
| import os | |
| import random | |
| import numpy | |
| import numpy as np | |
| from PIL import Image | |
| def gettext(index): | |
| with h5py.File('/root/lihui/StoryVisualization/pororo.h5', 'r') as h5: | |
| story = list() | |
| h5 = h5['test'] | |
| # 读取当前索引处的文本，并使用decode方法将其解码为UTF-8 | |
| texts = h5['text'][index].decode('utf-8').split('|') | |
| symbol = '\n' | |
| texts = symbol.join(texts) | |
| texts = 'Story<' + str(index) + '> :' + '\n' + texts | |
| print(texts) | |
| return texts | |
| # for i in range(1000): | |
| # gettext(i) | |
| # 截取前100的数据集 | |
| # ###正确的############## | |
| # # import h5py | |
| # # import numpy as np | |
| # # from PIL import Image | |
| # # | |
| # # | |
| # # # 创建名为“images”的子目录来保存图像 | |
| # # os.makedirs("train_images", exist_ok=True) | |
| # # | |
| # # 创建一个h5文件 | |
| # nf = h5py.File('/root/lihui/StoryVisualization/pororo_100.h5', "w") | |
| # with h5py.File('/root/lihui/StoryVisualization/pororo.h5', 'r') as f: | |
| # test_group = f['test'] | |
| # texts = np.array(test_group['text'][()]) | |
| # ngroup = nf.create_group('test') | |
| # ntext = ngroup.create_dataset('text', (100,), dtype=h5py.string_dtype(encoding='utf-8')) | |
| # for i in range(100): | |
| # ntext[i]=texts[i] | |
| # print(f"样本 {i}:") | |
| # # for j in range(5): | |
| # # # 创建一个固定的文件名来保存图像 | |
| # # # filename = os.path.join("images", f"image_{i}_{j}.png") | |
| # # # # 将HDF5文件中的图像数据保存到文件中 | |
| # # # with open(filename, "wb") as img_file: | |
| # # # img_file.write(test_group[f'image{j}'][i]) | |
| # # # 打印文本信息和文件名 | |
| # # ntext[i]='|'.join(texts[i].decode('utf-8').split('|')[j]) | |
| # # print(f"图像{j}已保存到文件：{filename}") | |
| # print(ntext[i]) | |
| # nf.close() | |
| #保存测试集图像，随机截取视频帧 | |
| with h5py.File(r'C:\Users\zjlab\Desktop\StoryVisualization\pororo.h5', 'r') as h5: | |
| h5 = h5['test'] | |
| for index in range(len(h5['text'])): #len(h5['text']) | |
| # index = int(index + 1) | |
| # print(index) | |
| images = list() | |
| for i in range(5): | |
| # 从h5文件中读取一组图像和对应的文本。 | |
| im = h5['image{}'.format(i)][index] | |
| # print(im) | |
| # pil_img = Image.fromarray(im) | |
| # # 保存图像 | |
| # pil_img.save(os.path.join('/root/lihui/StoryVisualization/ori_test_images', '{:04d}.png'.format(i))) | |
| # 对每个图像解码 | |
| im = cv2.imdecode(im, cv2.IMREAD_COLOR) | |
| # 随机选择一个128像素的图像切片 | |
| idx = random.randint(0, im.shape[0] / 128 - 1) | |
| # 将切片后的图像加到images列表中 | |
| images.append(im[idx * 128: (idx + 1) * 128]) | |
| # 深拷贝，后续不随images变化 | |
| # ori_images = copy.deepcopy(images) | |
| # 保存test原始图像 | |
| # for i, im in enumerate(images): | |
| # file_path = 'C:/Users/zjlab/Desktop/StoryVisualization/test_images/group{:02d}_image{:02d}.png'.format( | |
| # index + 1, | |
| # i + 1) | |
| # cv2.imwrite(file_path, im) | |
| ori_images_pil = Image.fromarray(images[i])#numpy.uint8(images[i].detach().cpu().squeeze().float().numpy())).convert("RGB") | |
| ori_images_pil.save( | |
| os.path.join('C:/Users/zjlab/Desktop/StoryVisualization/test_images', | |
| 'group{:02d}_image{:02d}.png'.format(index + 1,i + 1))) |