Comments (18)
关于深度信息的问题:
(1)部署时深度相机的输入尺寸是多大,训练的时候original = (106, 60)然后resized = (87, 58),D435的输入远大于这个尺寸这个是怎么取,在youtube视频里目测的fov应该不是很大,所以可能是进行了crop操作,再进行resize,而不是直接resize
(2)在保存jit的时候为什么深度信息那个网络是单独保存的而不是一起保存,且使用save_jit.py保存出来的网络无法在play.py里面使用,这个play.py里的似乎是调试代码
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关于部署上的问题:
(1)参考walk these ways的部署方案,需要给obs_buf,但是本仓库里的get_obs()这个函数和walk these ways里的有很大的不同,如何将两者进行对应是这个问题,之前的issue也提到了类似的问题
(self.env_class != 17).float()[:, None], (self.env_class == 17).float()[:, None]
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Hi! I'm also trying to deploy it on my robot. how is your work going now? Do you know what these parameters mean?
They relate to the input dimension of the neural network. I find them in "save_jit.py" and "legged_robot_config.py"
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Related Issues (20)
- torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 106.00 MiB (GPU 0; 11.77 GiB total capacity; 6.69 GiB already allocated; 86.62 MiB free; 6.74 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF HOT 2
- KeyError: 'depth_actor_state_dict' HOT 3
- Blank Depth image screen for distillation policy video HOT 1
- The Loss_depth/depth_encoder is 0 when i train distillation policy
- How to deploy on a real robot HOT 5
- Delay difference on paper and code HOT 1
- After running, you can't see the simulation interface HOT 2
- There is no graphical interface after the code runs, can you help me? thank you. HOT 1
- Questions about step5 in README.md file HOT 4
- evaluation.py code
- the meaning of parameter
- AttributeError: 'env' object has no attribute 'n_priv_latent'
- Run error HOT 1
- Gym cuda error: an illegal memory access was encountered When using --device=cuda:1 HOT 1
- The system reported an error after 7K training HOT 5
- AttributeError: 'NoneType' object has no attribute 'unsqueeze'
- Issue about deployment HOT 1
- loss.backward()
- Migration to Isaac Sim?
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