add a cropmodel sanity check for predicted boxes with less than one p…

…ixel width

src/deepforest/predict.py

@@ -216,13 +216,19 @@ def _predict_crop_model_(crop_model,
         print("No predictions to run crop model on, returning empty dataframe")
         return results
 
+    # Remove any boxes where xmin = xmax or ymin = ymax
+    results = results[results.xmin != results.xmax]
+    results = results[results.ymin != results.ymax]
+
     bounding_box_dataset = dataset.BoundingBoxDataset(
         results,
         root_dir=os.path.dirname(raster_path),
         transform=transform,
         augment=augment)
+
     crop_dataloader = crop_model.predict_dataloader(bounding_box_dataset)
     crop_results = trainer.predict(crop_model, crop_dataloader)
+
     stacked_outputs = np.vstack(np.concatenate(crop_results))
     label = np.argmax(stacked_outputs, 1)
     score = np.max(stacked_outputs, 1)