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| template = """ | |
| @dataset_register( | |
| name='VQAv2_split1_c_{}', | |
| classes=all_classes[0: 100], | |
| task_type='Visual Question Answering', | |
| object_type='Generic Object', | |
| class_aliases=[], | |
| shift_type=None | |
| ) | |
| class VQAv2_split1_c_{}(ABDataset): | |
| def create_dataset(self, root_dir: str, split: str, transform: Optional[Compose], | |
| classes: List[str], ignore_classes: List[str], idx_map: Optional[Dict[int, int]]): | |
| if transform is None: | |
| transform = None | |
| self.transform = transform | |
| dataset = _VQAv2_split1_c(root_dir, split, "{}", classes, ignore_classes, idx_map) | |
| return dataset | |
| """ | |
| # for c in 'gaussian_noise, shot_noise, impulse_noise, defocus_blur, glass_blur, motion_blur, zoom_blur, snow, frost, fog, brightness, contrast, elastic_transform, pixelate, jpeg_compression, speckle_noise, gaussian_blur, spatter, saturate'.split(', '): | |
| # print(template.format(c, c, c)) | |
| # print() | |
| # break | |
| classes_name = [f'VQAv2_split1_c_{c}' for c in 'gaussian_noise, shot_noise, impulse_noise, defocus_blur, glass_blur, motion_blur, zoom_blur, snow, frost, fog, brightness, contrast, elastic_transform, pixelate, jpeg_compression, speckle_noise, gaussian_blur, spatter, saturate'.split(', ')] | |
| print(', '.join(classes_name)) |