Hi, I am trying to perform the evaluation on SSV2 (sth-sth) dataset, I've successfully evaluated the trained model on HO3D, however, I am working on a small project for a project at the university and would like to run it on SSV2. Would you be able to point me in the right direction - what part of the dataloader should be changed to be able work with SSV2 and how can I do that? Amazing work.

Thanks for your great work! I want to know how to draw joint figures in your paper.

When I ran your code, I find the 2d joints result (your model output "pred_joints") is below/ It seems like it's not in the pixel frame. I don't know how to visualize it (like joint figures in your paper). If it's not convenient to show me your code, please just tell me the procedure to do it! Thanks a lot!

Thank you for your excellent work! There some diffculties that I can't get the same or even closed results provided by your paper in Table 4(supervised with CR).And I find the hyper-parameters in the code is not configed as your paper.Do your mand providing your hyper-parameters to help me ? Thank you. Here my logs.

====== Options ====== HO3D_root: /datassd/huanyao/semi-hand/Semi-Hand-Object-master/assets/data/ho3d_v2 blocks: 1 channels: 256 epochs: 60 evaluate: False host_folder: /datassd/huanyao/semi-hand/Semi-Hand-Object-master/host_folder inp_res: 512 lambda_joints2d: 100.0 lambda_objects: 500.0 lr: 0.0001 lr_decay_gamma: 0.7 lr_decay_step: 10 mano_lambda_joints3d: 10000.0 mano_lambda_manopose: 10 mano_lambda_manoshape: 0.1 mano_lambda_regulpose: 1 mano_lambda_regulshape: 100.0 mano_lambda_verts3d: 10000.0 mano_neurons: [1024, 512] mano_root: assets/mano_models manual_seed: 0 momentum: 0.9 network: honet_transformer obj_model_root: assets/object_models resume: /datassd/huanyao/semi-hand/Semi-Hand-Object-master/model.pth save_results: True snapshot: 5 stacks: 1 test_batch: 16 test_freq: 10 train_batch: 24 transformer_depth: 1 transformer_head: 1 use_cuda: 1 weight_decay: 0.0005 workers: 16

Hi, your work is inspiring me a lot.

I found that you are using different a pointcloud from the original data for YCB objects. How did you get it?

Did you random sample from the original point cloud?

Hello! It's a great project. I am wondering if you could provide the code or some instructions for preprocessing. So that I could use it in other tasks? Thanks in advance!

Hi @stevenlsw ,

I've been trying to evaluate the trained model, but got result shown as below:

 Traceback (most recent call last):

    File "traineval.py", line 104, in <module>
        main(args)
    File "traineval.py", line 35, in main
        train_dat = get_dataset(args, mode="train")
    File "/home/yilin/Hand_est/Semi-Hand-Object/utils/utils.py", line 133, in get_dataset
        train_label_root="ho3d-process", mode=mode, inp_res=args.inp_res)
    File "/home/yilin/Hand_est/Semi-Hand-Object/dataset/ho3d.py", line 55, in __init__
        self.set_list = ho3d_util.load_names(os.path.join(train_label_root, "train.txt"))
    File "/home/yilin/Hand_est/Semi-Hand-Object/dataset/ho3d_util.py", line 14, in load_names
        with open(image_path) as f:
    FileNotFoundError: [Errno 2] No such file or directory: 'ho3d-process/train.txt'

And by tracing back to ho3d.py, it seems that train.txt in the HO3D dataset some preprocessed files train_K.json, train_joint.json, train_mano.json and train_obj.json are supposed to be loaded to the ho3d-process path. Am I missing some preprocessing process? Also, is it ok to use HO3D_v3 for training and testing?