Bug description
When training a centered instance model and scaling the input, the visualization of validation during training appears to show a much wider crop than expected. My guess is that the crop is being applied after scaling, rather than before.
Expected behaviour
Visualization of the centered instance model's validation during training would show a down-sampled (scaled) image that is a crop, or subset, of the larger video.
Actual behaviour
Visualization shows a crop that is much larger than the video itself.
Your personal set up
- SLEAP installation method (listed here):
powershell install
Environment packages
# paste output of `pip freeze` or `conda list` here
Logs
# paste relevant logs here, if any
Screenshots
The above is sourced from a video that's 1200h x 1680 w, with a scale of 0.5 and a crop of 832 pixels.