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Thanks for your work. In the function sdf2weights, if all the predicted SDF values of a ray are positive, the inds of the ray is 0 since the the mechanism of torch.argmax() that if all inputs are the same value, 0 will be output. inds = torch.argmax(mask, axis=1)
So the corresponding z_min will be the config["cam"]["near"]. When the predicted SDF is all positive, it should indicates the z_min should be infinite, which makes me confused. What's more, this will make the elements in acc_map in function raw2output always equal 1.
The text was updated successfully, but these errors were encountered:
Thanks for your work. In the function sdf2weights, if all the predicted SDF values of a ray are positive, the inds of the ray is 0 since the the mechanism of torch.argmax() that if all inputs are the same value, 0 will be output.
inds = torch.argmax(mask, axis=1)
So the corresponding z_min will be the config["cam"]["near"]. When the predicted SDF is all positive, it should indicates the z_min should be infinite, which makes me confused. What's more, this will make the elements in acc_map in function raw2output always equal 1.
The text was updated successfully, but these errors were encountered: