(self, train_sample_interval=1)
| 79 | |
| 80 | |
| 81 | def load_data(self, train_sample_interval=1): |
| 82 | |
| 83 | content = np.load(self.annot_path, allow_pickle=True) |
| 84 | |
| 85 | try: |
| 86 | frame_range = content['frame_range'] |
| 87 | except KeyError: |
| 88 | frame_range = \ |
| 89 | np.array([[i, i + 1] for i in range(self.num_data)]) |
| 90 | |
| 91 | num_examples = len(frame_range) |
| 92 | |
| 93 | if 'meta' in content: |
| 94 | meta = content['meta'].item() |
| 95 | print('meta keys:', meta.keys()) |
| 96 | else: |
| 97 | meta = None |
| 98 | print( |
| 99 | 'No meta info provided! Please give height and width manually') |
| 100 | |
| 101 | print( |
| 102 | f'Start loading humandata {self.annot_path} into memory...\nDataset includes: {content.files}' |
| 103 | ) |
| 104 | tic = time.time() |
| 105 | image_path = content['image_path'] |
| 106 | |
| 107 | if meta is not None and 'height' in meta: |
| 108 | height = np.array(meta['height']) |
| 109 | width = np.array(meta['width']) |
| 110 | image_shape = np.stack([height, width], axis=-1) |
| 111 | else: |
| 112 | image_shape = None |
| 113 | |
| 114 | if meta is not None and 'gender' in meta and len(meta['gender']) != 0: |
| 115 | gender = meta['gender'] |
| 116 | else: |
| 117 | gender = None |
| 118 | |
| 119 | if meta is not None and 'is_kid' in meta and len(meta['is_kid']) != 0: |
| 120 | is_kid = meta['is_kid'] |
| 121 | else: |
| 122 | is_kid = None |
| 123 | |
| 124 | bbox_xywh = content['bbox_xywh'] |
| 125 | |
| 126 | if 'smplx' in content: |
| 127 | smplx = content['smplx'].item() |
| 128 | as_smplx = 'smplx' |
| 129 | elif 'smpl' in content: |
| 130 | smplx = content['smpl'].item() |
| 131 | as_smplx = 'smpl' |
| 132 | elif 'smplh' in content: |
| 133 | smplx = content['smplh'].item() |
| 134 | as_smplx = 'smplh' |
| 135 | # TODO: temp solution, should be more general. But SHAPY is very special |
| 136 | elif self.__class__.__name__ == 'SHAPY': |
| 137 | smplx = {} |
| 138 | else: |
no test coverage detected