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| import pickle as pkl | |
| import torch | |
| # see also /is/cluster/work/nrueegg/icon_pifu_related/barc_for_bite/data/smal_data/new_dog_models/additional_info/debugging_only_info_scanned_toys_for_dog_model_creation.py | |
| def load_dog_betas_for_3dcgmodel_loss(data_path, smal_model_type): | |
| assert smal_model_type in {'barc', '39dogs_diffsize', '39dogs_norm', '39dogs_norm_newv2', '39dogs_norm_newv3'} | |
| # load betas for the figures which were used to create the dog model | |
| if smal_model_type in ['barc', '39dogs_norm', '39dogs_norm_newv2', '39dogs_norm_newv3']: | |
| with open(data_path, 'rb') as f: | |
| data = pkl.load(f) | |
| dog_betas_unity = data['dogs_betas'] | |
| elif smal_model_type == '39dogs_diffsize': | |
| with open(data_path, 'rb') as f: | |
| u = pkl._Unpickler(f) | |
| u.encoding = 'latin1' | |
| data = u.load() | |
| dog_betas_unity = data['toys_betas'] | |
| # load correspondencies between those betas and the breeds | |
| if smal_model_type == 'barc': | |
| dog_betas_for_3dcgloss = {29: torch.tensor(dog_betas_unity[0, :]).float(), | |
| 91: torch.tensor(dog_betas_unity[1, :]).float(), | |
| 84: torch.tensor(0.5*dog_betas_unity[3, :] + 0.5*dog_betas_unity[14, :]).float(), | |
| 85: torch.tensor(dog_betas_unity[5, :]).float(), | |
| 28: torch.tensor(dog_betas_unity[6, :]).float(), | |
| 94: torch.tensor(dog_betas_unity[7, :]).float(), | |
| 92: torch.tensor(dog_betas_unity[8, :]).float(), | |
| 95: torch.tensor(dog_betas_unity[10, :]).float(), | |
| 20: torch.tensor(dog_betas_unity[11, :]).float(), | |
| 83: torch.tensor(dog_betas_unity[12, :]).float(), | |
| 99: torch.tensor(dog_betas_unity[16, :]).float()} | |
| elif smal_model_type in ['39dogs_diffsize', '39dogs_norm', '39dogs_norm_newv2', '39dogs_norm_newv3']: | |
| dog_betas_for_3dcgloss = {84: torch.tensor(dog_betas_unity[0, :]).float(), | |
| 99: torch.tensor(dog_betas_unity[2, :]).float(), | |
| 81: torch.tensor(dog_betas_unity[6, :]).float(), | |
| 9: torch.tensor(dog_betas_unity[9, :]).float(), | |
| 40: torch.tensor(dog_betas_unity[10, :]).float(), | |
| 29: torch.tensor(dog_betas_unity[11, :]).float(), | |
| 10: torch.tensor(dog_betas_unity[13, :]).float(), | |
| 11: torch.tensor(dog_betas_unity[14, :]).float(), | |
| 44: torch.tensor(dog_betas_unity[15, :]).float(), | |
| 91: torch.tensor(dog_betas_unity[16, :]).float(), | |
| 28: torch.tensor(dog_betas_unity[17, :]).float(), | |
| 108: torch.tensor(dog_betas_unity[20, :]).float(), | |
| 80: torch.tensor(dog_betas_unity[21, :]).float(), | |
| 85: torch.tensor(dog_betas_unity[23, :]).float(), | |
| 68: torch.tensor(dog_betas_unity[24, :]).float(), | |
| 94: torch.tensor(dog_betas_unity[25, :]).float(), | |
| 95: torch.tensor(dog_betas_unity[26, :]).float(), | |
| 20: torch.tensor(dog_betas_unity[27, :]).float(), | |
| 62: torch.tensor(dog_betas_unity[28, :]).float(), | |
| 57: torch.tensor(dog_betas_unity[30, :]).float(), | |
| 102: torch.tensor(dog_betas_unity[31, :]).float(), | |
| 8: torch.tensor(dog_betas_unity[35, :]).float(), | |
| 83: torch.tensor(dog_betas_unity[36, :]).float(), | |
| 96: torch.tensor(dog_betas_unity[37, :]).float(), | |
| 46: torch.tensor(dog_betas_unity[38, :]).float()} | |
| return dog_betas_for_3dcgloss |