Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Missing parameters of layers #360

Open
KevinzhouCUC opened this issue Nov 1, 2022 · 1 comment
Open

Missing parameters of layers #360

KevinzhouCUC opened this issue Nov 1, 2022 · 1 comment

Comments

@KevinzhouCUC
Copy link

Thanks so much for sharing the code and solving problems.
I've encounterd a similiar problem as #116 but not the same. I have already downloaded the fine tuned model ROMP_HRNet32_V1.pkl
but it still cannot process my images.

python -m romp.predict.image --inputs /root/autodl-tmp/data/my_video/output/images --output_dir /root/autodl-tmp/data/my_video/output/smpl_pred

No configs_yml is set, set it to the default --configs_yml=configs/image.yml
yaml_timestamp /root/autodl-tmp/neuman/preprocess/ROMP/active_configs/active_context_2022-11-01_21_11_05.yaml
Loading the configurations from configs/image.yml
INFO:root:{'tab': 'hrnet_cm64_process_images', 'configs_yml': 'configs/image.yml', 'inputs': '/root/autodl-tmp/data/my_video/output/images', 'output_dir': '/root/autodl-tmp/data/my_video/output/smpl_pred', 'interactive_vis': False, 'show_largest_person_only': False, 'show_mesh_stand_on_image': False, 'soi_camera': 'far', 'make_tracking': False, 'temporal_optimization': False, 'save_dict_results': True, 'save_visualization_on_img': True, 'fps_save': 24, 'character': 'smpl', 'renderer': 'pytorch3d', 'f': None, 'model_return_loss': False, 'model_version': 1, 'multi_person': True, 'new_training': False, 'perspective_proj': False, 'FOV': 60, 'focal_length': 443.4, 'lr': 0.0003, 'adjust_lr_factor': 0.1, 'weight_decay': 1e-06, 'epoch': 120, 'fine_tune': True, 'GPUS': 0, 'batch_size': 64, 'input_size': 512, 'master_batch_size': -1, 'nw': 4, 'optimizer_type': 'Adam', 'pretrain': 'simplebaseline', 'fix_backbone_training_scratch': False, 'backbone': 'hrnet', 'model_precision': 'fp32', 'deconv_num': 0, 'head_block_num': 2, 'merge_smpl_camera_head': False, 'use_coordmaps': True, 'hrnet_pretrain': '/root/autodl-tmp/neuman/preprocess/ROMP/trained_models/pretrain_hrnet.pkl', 'resnet_pretrain': '/root/autodl-tmp/neuman/preprocess/ROMP/trained_models/pretrain_resnet.pkl', 'loss_thresh': 1000, 'max_supervise_num': -1, 'supervise_cam_params': False, 'match_preds_to_gts_for_supervision': False, 'matching_mode': 'all', 'supervise_global_rot': False, 'HMloss_type': 'MSE', 'eval': False, 'eval_datasets': 'pw3d', 'val_batch_size': 4, 'test_interval': 2000, 'fast_eval_iter': -1, 'top_n_error_vis': 6, 'eval_2dpose': False, 'calc_pck': False, 'PCK_thresh': 150, 'calc_PVE_error': False, 'centermap_size': 64, 'centermap_conf_thresh': 0.25, 'collision_aware_centermap': False, 'collision_factor': 0.2, 'center_def_kp': True, 'local_rank': 0, 'distributed_training': False, 'distillation_learning': False, 'teacher_model_path': '/export/home/suny/CenterMesh/trained_models/3dpw_88_57.8.pkl', 'print_freq': 50, 'model_path': 'trained_models/ROMP_HRNet32_V1.pkl', 'log_path': '/root/autodl-tmp/neuman/preprocess/log/', 'learn_2dpose': False, 'learn_AE': False, 'learn_kp2doffset': False, 'shuffle_crop_mode': False, 'shuffle_crop_ratio_3d': 0.9, 'shuffle_crop_ratio_2d': 0.1, 'Synthetic_occlusion_ratio': 0, 'color_jittering_ratio': 0.2, 'rotate_prob': 0.2, 'dataset_rootdir': '/root/autodl-tmp/neuman/preprocess/dataset/', 'dataset': 'h36m,mpii,coco,aich,up,ochuman,lsp,movi', 'voc_dir': '/root/autodl-tmp/neuman/preprocess/dataset/VOCdevkit/VOC2012/', 'max_person': 64, 'homogenize_pose_space': False, 'use_eft': True, 'smpl_mesh_root_align': False, 'Rot_type': '6D', 'rot_dim': 6, 'cam_dim': 3, 'beta_dim': 10, 'smpl_joint_num': 22, 'smpl_model_path': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/parameters', 'smpl_J_reg_h37m_path': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/parameters/J_regressor_h36m.npy', 'smpl_J_reg_extra_path': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/parameters/J_regressor_extra.npy', 'smpl_uvmap': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/parameters/smpl_vt_ft.npz', 'wardrobe': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/wardrobe', 'mesh_cloth': 'ghostwhite', 'nvxia_model_path': '/root/autodl-tmp/neuman/preprocess/ROMP/model_data/characters/nvxia', 'track_memory_usage': False, 'adjust_lr_epoch': [], 'kernel_sizes': [5], 'collect_subdirs': False, 'save_mesh': True, 'save_centermap': False}
INFO:root:------------------------------------------------------------------
visualize in gpu mode
INFO:root:start building model.
Using ROMP v1
Confidence: 0.25
INFO:root:using fine_tune model: trained_models/ROMP_HRNet32_V1.pkl
INFO:root:missing parameters of layers:['_result_parser.params_map_parser.smpl_model.betas', '_result_parser.params_map_parser.smpl_model.faces_tensor', '_result_parser.params_map_parser.smpl_model.v_template', '_result_parser.params_map_parser.smpl_model.shapedirs', '_result_parser.params_map_parser.smpl_model.J_regressor', '_result_parser.params_map_parser.smpl_model.J_regressor_extra9', '_result_parser.params_map_parser.smpl_model.J_regressor_h36m17', '_result_parser.params_map_parser.smpl_model.posedirs', '_result_parser.params_map_parser.smpl_model.parents', '_result_parser.params_map_parser.smpl_model.lbs_weights', '_result_parser.params_map_parser.smpl_model.vertex_joint_selector.extra_joints_idxs']
INFO:root:Train all layers, except: ['_result_parser.params_map_parser.smpl_model.betas']
visualize in gpu mode
Initialization finished!
Processing /root/autodl-tmp/data/my_video/output/images, saving to /root/autodl-tmp/data/my_video/output/smpl_pred
INFO:root:gathering datasets
Loading 23 images to process
Processed 0 / 23 images

Then it terminates. I really have no idea what to do. Could you please help me out of the situation?

@Arthur151
Copy link
Owner

@KevinzhouCUC
Please try the simple romp
https://github.com/Arthur151/ROMP/tree/master/simple_romp
It is much easier to use and install with a clean implementation for inference only.
Best,
Yu

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants