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ValueError: index can't contain negative values #18
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Did you change the ninput_edges flag to 3000 (the default is 750)? Do that by passing: |
oh. I forgot to change the default ninput_edges to 3000. you mean that I need to retrain it with the new pooling size?as we know, the real meshes vary from hundreds to hundreds of thousabds, is there a way to handle this with one net,instead of training once for each size. I am trying to use meshcnn as a new method to handle mesh simplification.just like what simplygon does. |
The You can re-train the network on your data, define new hyper-parameters for your set, and use the same one for train / test. |
@sutongkui - closing this issue as I haven't heard from you in a while. If you still need further clarification , let me know. |
As described in #46, I run into this error with files normalized to 300 or 600 faces resulting in about 500 or 1000 edges. I have to set the number of input edges to 2000 to overcome the error. |
Works for me now, I have used problematic input data before. |
I used classification pretrained parameters, the test works well for edges 750, but then I subdivide the mesh to 3000 edges(apply 1 loop, still manifold), and set
--pool_res 2500 2000 1500 1000
, error occurs below, do I have to use the fixed edges(like 750) as input? How to deal with dense meshes, do we need to retrain it?The text was updated successfully, but these errors were encountered: