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View Code? Open in Web Editor NEWThis repository contains codes of ICCV2021 paper: SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation
License: Apache License 2.0
This repository contains codes of ICCV2021 paper: SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation
License: Apache License 2.0
Hi @shangbuhuan13 , I have seen HERE that you have uploaded the metrics for LMO and YCB-V. Can you also upload the results for LM?
Best,
D
Hi! Thanks for opensourcing the code! I cannot download models by the link: https://drive.google.com/file/d/136ExcMykxsVVSzOiGQVYspq1fx9Hjd6R/view?usp=sharing (error is: "Sorry, the file you have requested does not exist."). Does it work?
您好!
我准备使用gdrn_selfocc_multistep_40E.py
配置文件复现实验,但是我发现在生成xyz后lm/train_pbr/xyz_crop已经很大,并且准备生成train_pbr/Q0,但是这个我估计要3T的存储空间,所以想问下配置文件中TRAIN2=("lmo_pbr_train",),
的这个是否必要?
Hi, I have a small question about the results on linemod dataset.
I see that in the paper, the backbone should be ResNet34, however, in the codebase, it seems like ResNet50 (
).I also run the linemod experiments with exact the config file in the repo, getting result ADI.10 ~95.5 with ResNet50. So I would like to confirm with you what is the Backbone used in linemod results?
Hi,
Thanks for your great work! I have a question about the backbone in LM datasets. In your paper, you said that "As backbone we leverage ResNet34 [6] for all experiments on the LM dataset", but the config files in this repo seems different:
BACKBONE=dict(
FREEZE=False,
PRETRAINED="mmcls://resnet50_v1d",
INIT_CFG=dict(
_delete_=True,
type="mm/ResNetV1d",
depth=50,
in_channels=3,
out_indices=(3,),
),
),
and the output feature dimension is 2048, not 512 as in GDR-Net.
Could you help to clarify this? Thanks!
您好,我之前在研究gdrnet的相关工作,但一直无法成功运行生成xyz_crop的程序。而我在您开源的这份代码的readme中看到您提及generate p.py对应的是2d-3d matching的groundtruth,这里生成的是否就是gdrnet中需要的xyz_crop呢。如果是的话,我是应该运行generate_pbr_P.py还是generate_pbr_P_fast.py呢?生成的xyz_crop和gdrnet中要求的是否一致呢?
在模型文件GDRN.py中用到了"Q0_DEF_LW"和"HANDLE_SYM"这两个参数,但在configs/gdrn_selfocc/lm 文件夹中的配置文件没有设置这两个参数,请问这两个参数应该设置什么数值?
Hi,
Thanks again for your great work. I have a question about the implementation of 2D consistency loss
I am confused why the loss is divide by 572.3. In datasets/BOP_DATASETS/lm/camera.json
I see the camera information is
{
"cx": 325.2611,
"cy": 242.04899,
"depth_scale": 1.0,
"fx": 572.4114,
"fy": 573.57043,
"height": 480,
"width": 640
}
Also, will this impact YCBV dataset, since it has different camera intrinsic parameters? Thanks!
您好!
您的工作真的太棒了。
其次想问下您,“ Please refer to generate_*.py.” 真实的自遮挡坐标需要我们运行什么指令才可以生成吗?还是说在训练的过程中,自己就会生成呢,
sorry to be a bother, when I run this python file, it shows an error called "AssertionError: /home/fxj/SO-Pose-main/datasets/BOP_DATASETS/lm/train_pbr/xyz_crop/000000/000000_000001-xyz.pkl", where can I find"000000_000001-xyz.pkl"?
Could you provide a brief script to show how to evaluate the trained model on YCBV dataset? I just found it is hard to run the evaluation based on your current descriptions. Thx.
Hey, How can I inference the results? (3d boundingbox or pointcloud draw)
作者您好,我对您的工作十分感兴趣,在复现论文的过程中,我发现在lmo数据集实验中,有关于real+syn的实验设置,但是我发现syn数据的生成有很大的随机性,请问您可以分享一下syn数据集吗?十分感谢您!
您好,我在运行lmo_2_vis_poses.py时出现了错误,提示ModuleNotFoundError: No module named 'lib.egl_renderer',可以麻烦提供一下吗,谢谢!
sorry to be a bother, when I run generate_pbr_P_fast.py, it shows an error called "'ref' has no attribute 'lm_full'", trace back from line 110, how can I fixed it?
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