Hello author, I found that in the evaluation, the Minkunet model output of SPCONV and Torchsparse ++ is different,(artifact-p2 evaluate.py, model output cosine similarity is approximately 0.81 ). I make sure each backend using same input point clouds. And, the cosine similarity between ME and Torchsparse++ output is approximately 0.99.I am not very familiar with this field and may have made some naive mistakes. Looking forward to your reply.
this line in artifact-p2 evaluate.py
out = model(inputs["pts_input"])
Hello author, I found that in the evaluation, the Minkunet model output of SPCONV and Torchsparse ++ is different,(artifact-p2 evaluate.py, model output cosine similarity is approximately 0.81 ). I make sure each backend using same input point clouds. And, the cosine similarity between ME and Torchsparse++ output is approximately 0.99.I am not very familiar with this field and may have made some naive mistakes. Looking forward to your reply. this line in artifact-p2 evaluate.py
out = model(inputs["pts_input"])