| 17 | return self.samples[x] |
| 18 | |
| 19 | def load_samples_deca(self): |
| 20 | label_zip = zipfile.ZipFile(self.file_path) |
| 21 | label_files = [x for x in label_zip.namelist() if x.endswith('.pth')] |
| 22 | print("loading deca light coefficients") |
| 23 | label_files = sorted(label_files) |
| 24 | for i, label_fname in enumerate(label_files): |
| 25 | with label_zip.open(label_fname, 'r') as f: |
| 26 | label_data = torch.load(f) |
| 27 | self.samples.append(label_data['light'].squeeze().numpy()) |
| 28 | if i == self.n_samples: |
| 29 | break |
| 30 | |
| 31 | def load_deca_center_light(self): |
| 32 | light_center = np.array([[ 3.2057941 , 3.19894958, 3.20620155], |