| import os | |
| import json | |
| import numpy as np | |
| from PIL import Image | |
| import torch | |
| from torch.utils.data import Dataset | |
| class DatasetJson(Dataset): | |
| def __init__(self, data_path, transform=None): | |
| super().__init__() | |
| self.data_path = data_path | |
| self.transform = transform | |
| json_path = os.path.join(data_path, 'image_paths.json') | |
| assert os.path.exists(json_path), f"please first run: python3 tools/openimage_json.py" | |
| with open(json_path, 'r') as f: | |
| self.image_paths = json.load(f) | |
| def __len__(self): | |
| return len(self.image_paths) | |
| def __getitem__(self, idx): | |
| for _ in range(20): | |
| try: | |
| return self.getdata(idx) | |
| except Exception as e: | |
| print(f"Error details: {str(e)}") | |
| idx = np.random.randint(len(self)) | |
| raise RuntimeError('Too many bad data.') | |
| def getdata(self, idx): | |
| image_path = self.image_paths[idx] | |
| image_path_full = os.path.join(self.data_path, image_path) | |
| image = Image.open(image_path_full).convert('RGB') | |
| if self.transform: | |
| image = self.transform(image) | |
| return image, torch.tensor(0) | |
| def build_openimage(args, transform): | |
| return DatasetJson(args.data_path, transform=transform) | |