A possible bug in inference.py

[CWHer]

At line 473 of inference.py, it writes

decision = stroke_decision.view(1, h, w, stroke_num).contiguous().bool()

However, this float to bool convert seems to behave wrongly. It almost always yields all true decisions. (I didn't find a document that specifies the converting rule in PyTorch. However, in other languages, float with non-zero values are treated as true.) Consequently, this causes so-called lattice artifacts in the final result.

The following code fixes this issue. 🤗

decision = stroke_decision.view(1, h, w, stroke_num).contiguous() > 0