| 80 | |
| 81 | |
| 82 | class ImageDataset(Dataset): |
| 83 | def __init__( |
| 84 | self, |
| 85 | resolution, |
| 86 | image_paths, |
| 87 | classes=None, |
| 88 | shard=0, |
| 89 | num_shards=1, |
| 90 | random_crop=False, |
| 91 | random_flip=True, |
| 92 | ): |
| 93 | super().__init__() |
| 94 | self.resolution = resolution |
| 95 | self.local_images = image_paths[shard:][::num_shards] |
| 96 | self.local_classes = None if classes is None else classes[shard:][::num_shards] |
| 97 | self.random_crop = random_crop |
| 98 | self.random_flip = random_flip |
| 99 | |
| 100 | def __len__(self): |
| 101 | return len(self.local_images) |
| 102 | |
| 103 | def __getitem__(self, idx): |
| 104 | path = self.local_images[idx] |
| 105 | with bf.BlobFile(path, "rb") as f: |
| 106 | pil_image = Image.open(f) |
| 107 | pil_image.load() |
| 108 | pil_image = pil_image.convert("RGB") |
| 109 | |
| 110 | if self.random_crop: |
| 111 | arr = random_crop_arr(pil_image, self.resolution) |
| 112 | else: |
| 113 | arr = center_crop_arr(pil_image, self.resolution) |
| 114 | |
| 115 | if self.random_flip and random.random() < 0.5: |
| 116 | arr = arr[:, ::-1] |
| 117 | |
| 118 | arr = arr.astype(np.float32) / 127.5 - 1 |
| 119 | |
| 120 | out_dict = {} |
| 121 | if self.local_classes is not None: |
| 122 | out_dict["y"] = np.array(self.local_classes[idx], dtype=np.int64) |
| 123 | return np.transpose(arr, [2, 0, 1]), out_dict |
| 124 | |
| 125 | |
| 126 | def center_crop_arr(pil_image, image_size): |