| 96 | |
| 97 | |
| 98 | class HyperSim(Dataset): |
| 99 | def __init__(self, data_dir_root): |
| 100 | # image paths are of the form <data_dir_root>/<scene>/images/scene_cam_#_final_preview/*.tonemap.jpg |
| 101 | # depth paths are of the form <data_dir_root>/<scene>/images/scene_cam_#_final_preview/*.depth_meters.hdf5 |
| 102 | self.image_files = glob.glob(os.path.join( |
| 103 | data_dir_root, '*', 'images', 'scene_cam_*_final_preview', '*.tonemap.jpg')) |
| 104 | self.depth_files = [r.replace("_final_preview", "_geometry_hdf5").replace( |
| 105 | ".tonemap.jpg", ".depth_meters.hdf5") for r in self.image_files] |
| 106 | self.transform = ToTensor() |
| 107 | |
| 108 | def __getitem__(self, idx): |
| 109 | image_path = self.image_files[idx] |
| 110 | depth_path = self.depth_files[idx] |
| 111 | |
| 112 | image = np.asarray(Image.open(image_path), dtype=np.float32) / 255.0 |
| 113 | |
| 114 | # depth from hdf5 |
| 115 | depth_fd = h5py.File(depth_path, "r") |
| 116 | # in meters (Euclidean distance) |
| 117 | distance_meters = np.array(depth_fd['dataset']) |
| 118 | depth = hypersim_distance_to_depth( |
| 119 | distance_meters) # in meters (planar depth) |
| 120 | |
| 121 | # depth[depth > 8] = -1 |
| 122 | depth = depth[..., None] |
| 123 | |
| 124 | sample = dict(image=image, depth=depth) |
| 125 | sample = self.transform(sample) |
| 126 | |
| 127 | if idx == 0: |
| 128 | print(sample["image"].shape) |
| 129 | |
| 130 | return sample |
| 131 | |
| 132 | def __len__(self): |
| 133 | return len(self.image_files) |
| 134 | |
| 135 | |
| 136 | def get_hypersim_loader(data_dir_root, batch_size=1, **kwargs): |
no outgoing calls
no test coverage detected