kistf001 / simple_supertrack Goto Github PK
View Code? Open in Web Editor NEWimplementaion of superTrack
License: MIT License
implementaion of superTrack
License: MIT License
Hello! When I run the viewer.py, I have encountered such a problem.
/home/anaconda3/envs/clip/lib/python3.8/site-packages/glfw/__init__.py:916: GLFWError: (65543) b'GLX: Failed to create context: BadLength (poly request too large or internal Xlib length error)'
warnings.warn(message, GLFWError)
Traceback (most recent call last):
File "viewer.py", line 9, in <module>
A.env.render()
File "/home/supertrack/simple_superTrack-main/algorithm/env.py", line 64, in render
return self.inside.render(640, 480, camera_id=0)
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/mujoco/engine.py", line 223, in render
camera = Camera(
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/mujoco/engine.py", line 711, in __init__
if self._physics.contexts.mujoco is not None:
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/mujoco/engine.py", line 533, in contexts
self._make_rendering_contexts()
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/mujoco/engine.py", line 519, in _make_rendering_contexts
mujoco_context = wrapper.MjrContext(self.model, render_context)
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/mujoco/wrapper/core.py", line 603, in __init__
ptr = ctx.call(mujoco.MjrContext, model.ptr, font_scale)
File "/home/anaconda3/envs/clip/lib/python3.8/site-packages/dm_control/_render/executor/render_executor.py", line 138, in call
return func(*args, **kwargs)
mujoco.FatalError: gladLoadGL error
Is this due to an issue with OpenGL?
Although the server is equipped with RTX 3080 and graphics card driver 510.47.03, my server can still only install OpenGL3.1 Mesa 21.2.6. Is this a problem with graphics card drivers? Is there anything else I need to do to upgrade OpenGL version to 3.2 or higher?
I would also like to ask how should I modify this code if training a dataset like LAFAN? Do I only need to modify the reward function in the Physics0 class?
Is this project still developing?
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