lazyslide.models.tile_prediction.PathProfilerQC#
- class PathProfilerQC(model_path=None, token=None)#
Bases:
TilePredictionModelGitHub Paper Params: 11.2M GPL-3.0 [Haghighat et al., 2022] Quality assessment of histology images
- predict(image)#
Predict the class of the input image using the PathProfiler model. The model expects a tensor of shape [B, C, H, W].
Suggested Name
Description
diagnostic_quality
Whether usable for diagnosis (1=good)
visual_cleanliness
Normal & artefact-free (1=clean)
focus_issue
Focus issue: 1=severe, 0.5=slight, 0=none
staining_issue
Staining issue: 1=severe, 0.5=slight, 0=none
tissue_folding_present
Tissue folding present (1=yes)
misc_artifacts_present
Other artefacts present (1=yes)