config = dict() # DON'T FORGET TO RESET SSIM LOSS USAGE # DON'T FORGET TO CHECK MODEL LOADING # DON'T FORGET TO CHECK IF STORE IN MEMORY # DON'T FORGET TO CHECK REG LOSS COEFF # DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512 # DON'T FORGET TO CHECK AVG GARMENT USED config['batch_size'] = 4 config['train_dir'] = '/home/workspace/local-data/train' config['valid_dir'] = '/home/workspace/local-data/valid' config['test_dir'] = '/home/workspace/data/dataset/test_ready' config['use_filled'] = False config['resolution'] = 512 config['is_skirt'] = False config['dataset_in_memory'] = False config['is_cape'] = False config['smpl_res'] = 14475 if config['is_cape']: config['smpl_res'] = 3638 config['latent_dim'] = 128 config['gpu'] = '1' config['name'] = 'ab_1' config['notes'] = '' config['pretrained_model'] = 'checkpoints/v2_5_2' config['resolution'] = 512 config['is_skirt'] = False config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision config['l2_coeff'] = 1 ############### config['lr'] = 0.0001# 0.0001 ############### config['starting_balancing_coeff'] = 0.0001 config['signature_dynamic'] = { 'id': (), 'pose_shape': (72 + 11,), 'uv_body_posed': (512, 256, 3), 'mesh_body_posed': (14475, 3,), 'mesh_posed': (14475, 3,), 'mesh_unposed': (14475, 3,), 'uv_unposed': (512, 256, 3), 'uv_curvature': (512, 256, 7), } config['signature_static'] = { 'uv_static': (512, 256, 3), 'mesh_mask': (14475,), 'uv_mask': (512, 256,), } config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv config['static_model'] = 'checkpoints/static_1' config['body_model'] = 'checkpoints/body_1' config['curvature_model'] = 'checkpoints/curv_1' config['upscale_enhancer'] = '' config['freeze_encoders'] = True config['use_one_hot'] = False config['cvae'] = dict() config['cvae']['is_label'] = False config['cvae']['latent_dim'] = config['latent_dim'] config['cvae']['add_noise'] = True config['cvae']['noise_amount'] = 0.025 config['cvae']['kernel_size'] = 7 config['cvae']['encoder_depths'] = [3, 3, 9, 3] config['cvae']['encoder_dims'] = [32, 64, 128, 256] config['cvae']['decoder_input'] = (16, 8, 80) config['cvae']['decoder_depths'] = [3, 3, 9, 3] config['cvae']['decoder_dims'] = [256, 128, 64, 16] config['cond_ae'] = dict() config['cond_ae']['is_label'] = False config['cond_ae']['upscale_output'] = False config['cond_ae']['latent_dim'] = config['latent_dim'] config['cond_ae']['kernel_size'] = 7 config['cond_ae']['bottleneck_size'] = 64 config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3] config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']] config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size']) config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3] config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16] config['cond_ae_body'] = dict() config['cond_ae_body']['latent_dim'] = config['latent_dim'] config['cond_ae_body']['kernel_size'] = 7 config['cond_ae_body']['upscale_output'] = True config['cond_ae_body']['bottleneck_size'] = 512 config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3] config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']] config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size']) config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3] config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]