from configs.config_base import config config['gpu'] = '1' config['lr'] = 0.0001 config['name'] = 'body_1' config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext, | \ flattened bottleneck with 128 latent_dim\ remove global orientation | \ fixed gender issue with deoriented bodies, again, aaand again | \ trained on 100 garments | \ remove multiplications with garment uv mask | \ larger bottleneck, low res output upscaled | \ larger batch size, 32 instead of 4 | \ calculate euclidean error on whole body, not just garment masked | \ ' config['dataset_in_memory'] = False config['batch_size'] = 32 config['signature_dynamic'] = { 'id': (), 'pose_shape': (72 + 11,), 'uv_body_posed': (3, 512, 256,), 'mesh_body_posed': (14475, 3,), } config['signature_static'] = { 'mesh_mask': (14475,), } config['cond_ae']['latent_dim'] = config['latent_dim'] config['cond_ae']['kernel_size'] = 7 config['cond_ae']['upscale_output'] = True config['cond_ae']['bottleneck_size'] = 512 config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3, 3] config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae']['bottleneck_size']] config['cond_ae']['decoder_input'] = (4, 2, config['cond_ae']['bottleneck_size']) config['cond_ae']['decoder_depths'] = [3, 3, 9, 3] config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 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]