Comments (3)
Well done , I have already managed to solve it on my own , by tracing back the problem in pytorch3d library .
It had to do with the renderer.shader function , in your script I have done the following
# add these imports
from pytorch3d.renderer.blending import BlendParams, hard_rgb_blend
from pytorch3d.renderer.mesh.shading import flat_shading
# replace these lines (206)
# images = renderer.shader(fragments, meshes_batch, lights=lights, cameras=cams)
texels = meshes_batch.sample_textures(fragments)
colors = flat_shading(meshes=meshes_batch, fragments=fragments, lights=lights, cameras=cams, materials=renderer.shader.materials, texels=texels)
images = hard_rgb_blend(colors[0], fragments, BlendParams())
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It works like a charm with #21
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Hi, this is probably a pytorch3d
version problem. We were working with an old version, and the new version is incompatible. I update the installation part in the fix/install
branch. Could you check it out and create the environment again to see if you still have an issue? Things work fine on my side with this new installation.
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Related Issues (20)
- Missing positional argument when constructing empy PointFragment HOT 1
- undefined symbol HOT 1
- Several errors HOT 6
- Confused about learn_color HOT 3
- Using custom renderer to generate mvr data HOT 4
- How to compute the gradient of the regularization terms and update point and normal( Eq 15,16)?
- Supporting for newer pytorch version HOT 1
- Negative GVdets
- issue about Iso-Points
- AttributeError: _evt HOT 2
- ValueError: Invalid vertices in file. HOT 2
- Visualization of the results HOT 2
- Unused config learning rate
- Reproduce Results in Fig. 3 HOT 3
- Pix2Pix results
- Issue with running demo HOT 2
- problem with dense depth HOT 1
- imageio version 2.8.0 does not support exr! HOT 2
- Confused with the backward of RasterizeAutograd HOT 2
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