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| import os | |
| import os.path as osp | |
| # will be update in exp | |
| num_gpus = -1 | |
| exp_name = 'output/exp1/pre_analysis' | |
| # quick access | |
| save_epoch = 1 | |
| lr = 1e-5 | |
| end_epoch = 10 | |
| train_batch_size = 32 | |
| syncbn = True | |
| bbox_ratio = 1.2 | |
| # continue | |
| continue_train = False | |
| start_over = True | |
| # dataset setting | |
| agora_fix_betas = True | |
| agora_fix_global_orient_transl = True | |
| agora_valid_root_pose = True | |
| # all data | |
| dataset_list = ['Human36M', 'MSCOCO', 'MPII', 'AGORA', 'EHF', 'SynBody', 'GTA_Human2', \ | |
| 'EgoBody_Egocentric', 'EgoBody_Kinect', 'UBody', 'PW3D', 'MuCo', 'PROX'] | |
| trainset_3d = ['MSCOCO','AGORA', 'UBody'] | |
| trainset_2d = ['PW3D', 'MPII', 'Human36M'] | |
| trainset_humandata = ['BEDLAM', 'SPEC', 'GTA_Human2','SynBody', 'PoseTrack', | |
| 'EgoBody_Egocentric', 'PROX', 'CrowdPose', | |
| 'EgoBody_Kinect', 'MPI_INF_3DHP', 'RICH', 'MuCo', 'InstaVariety', | |
| 'Behave', 'UP3D', 'ARCTIC', | |
| 'OCHuman', 'CHI3D', 'RenBody_HiRes', 'MTP', 'HumanSC3D', 'RenBody', | |
| 'FIT3D', 'Talkshow' , 'SSP3D', 'LSPET'] | |
| testset = 'EHF' | |
| use_cache = True | |
| # downsample | |
| BEDLAM_train_sample_interval = 5 | |
| EgoBody_Kinect_train_sample_interval = 10 | |
| train_sample_interval = 10 # UBody | |
| MPI_INF_3DHP_train_sample_interval = 5 | |
| InstaVariety_train_sample_interval = 10 | |
| RenBody_HiRes_train_sample_interval = 5 | |
| ARCTIC_train_sample_interval = 10 | |
| # RenBody_train_sample_interval = 10 | |
| FIT3D_train_sample_interval = 10 | |
| Talkshow_train_sample_interval = 10 | |
| # strategy | |
| data_strategy = 'balance' # 'balance' need to define total_data_len | |
| total_data_len = 4500000 | |
| # model | |
| smplx_loss_weight = 1.0 #2 for agora_model for smplx shape | |
| smplx_pose_weight = 10.0 | |
| smplx_kps_3d_weight = 100.0 | |
| smplx_kps_2d_weight = 1.0 | |
| net_kps_2d_weight = 1.0 | |
| agora_benchmark = 'agora_model' # 'agora_model', 'test_only' | |
| model_type = 'smpler_x_s' | |
| encoder_config_file = 'main/transformer_utils/configs/smpler_x/encoder/body_encoder_small.py' | |
| encoder_pretrained_model_path = 'pretrained_models/vitpose_small.pth' | |
| feat_dim = 384 | |
| ## =====FIXED ARGS============================================================ | |
| ## model setting | |
| upscale = 4 | |
| hand_pos_joint_num = 20 | |
| face_pos_joint_num = 72 | |
| num_task_token = 24 | |
| num_noise_sample = 0 | |
| ## UBody setting | |
| train_sample_interval = 10 | |
| test_sample_interval = 100 | |
| make_same_len = False | |
| ## input, output size | |
| input_img_shape = (512, 384) | |
| input_body_shape = (256, 192) | |
| output_hm_shape = (16, 16, 12) | |
| input_hand_shape = (256, 256) | |
| output_hand_hm_shape = (16, 16, 16) | |
| output_face_hm_shape = (8, 8, 8) | |
| input_face_shape = (192, 192) | |
| focal = (5000, 5000) # virtual focal lengths | |
| princpt = (input_body_shape[1] / 2, input_body_shape[0] / 2) # virtual principal point position | |
| body_3d_size = 2 | |
| hand_3d_size = 0.3 | |
| face_3d_size = 0.3 | |
| camera_3d_size = 2.5 | |
| ## training config | |
| print_iters = 100 | |
| lr_mult = 1 | |
| ## testing config | |
| test_batch_size = 32 | |
| ## others | |
| num_thread = 2 | |
| vis = False | |
| ## directory | |
| output_dir, model_dir, vis_dir, log_dir, result_dir, code_dir = None, None, None, None, None, None | |