(args)
| 31 | return mesh |
| 32 | |
| 33 | def test(args): |
| 34 | Path(args.output_dir).mkdir(parents=True, exist_ok=True) |
| 35 | torch.set_default_dtype(torch.float32) |
| 36 | # torch.set_num_threads(8) |
| 37 | # Constrain all sources of randomness |
| 38 | torch.manual_seed(args.seed) |
| 39 | torch.cuda.manual_seed(args.seed) |
| 40 | torch.cuda.manual_seed_all(args.seed) |
| 41 | random.seed(args.seed) |
| 42 | np.random.seed(args.seed) |
| 43 | torch.backends.cudnn.benchmark = False |
| 44 | torch.backends.cudnn.deterministic = True |
| 45 | |
| 46 | objbase, extension = os.path.splitext(os.path.basename(args.obj_path)) |
| 47 | # Check that isn't already done |
| 48 | if (not args.overwrite) and os.path.exists(os.path.join(args.output_dir, "loss.png")) and \ |
| 49 | os.path.exists(os.path.join(args.output_dir, f"{objbase}_final.obj")): |
| 50 | print(f"Already done with {args.output_dir}") |
| 51 | exit() |
| 52 | elif args.overwrite and os.path.exists(os.path.join(args.output_dir, "loss.png")) and \ |
| 53 | os.path.exists(os.path.join(args.output_dir, f"{objbase}_final.obj")): |
| 54 | import shutil |
| 55 | for filename in os.listdir(args.output_dir): |
| 56 | file_path = os.path.join(args.output_dir, filename) |
| 57 | try: |
| 58 | if os.path.isfile(file_path) or os.path.islink(file_path): |
| 59 | os.unlink(file_path) |
| 60 | elif os.path.isdir(file_path): |
| 61 | shutil.rmtree(file_path) |
| 62 | except Exception as e: |
| 63 | print('Failed to delete %s. Reason: %s' % (file_path, e)) |
| 64 | |
| 65 | n_augs = args.n_augs |
| 66 | dir = args.output_dir |
| 67 | |
| 68 | model = NeuralStyleField(args.material_random_pe_numfreq, |
| 69 | args.material_random_pe_sigma, |
| 70 | args.num_lgt_sgs, |
| 71 | args.max_delta_theta, |
| 72 | args.max_delta_phi, |
| 73 | args.normal_nerf_pe_numfreq, |
| 74 | args.normal_random_pe_numfreq, |
| 75 | args.symmetry, |
| 76 | args.radius, |
| 77 | args.background, |
| 78 | args.init_r_and_s, |
| 79 | args.width, |
| 80 | args.init_roughness, |
| 81 | args.init_specular, |
| 82 | args.material_nerf_pe_numfreq, |
| 83 | args.normal_random_pe_sigma, |
| 84 | args.if_normal_clamp |
| 85 | ) |
| 86 | state_dict = torch.load(args.model_dir) |
| 87 | model.load_state_dict(state_dict['model']) |
| 88 | model.eval() |
| 89 | envmap = compute_envmap(lgtSGs=model.svbrdf_network.get_light(), H=256, W=512, upper_hemi=model.svbrdf_network.upper_hemi) |
| 90 | envmap = envmap.cpu().numpy() |
no test coverage detected