feat: The flag for removing boundary objects was added to the config

config/dataset_config.py

@@ -11,6 +11,7 @@ class DatasetCommonConfig(BaseModel):
     device: str = "cuda:0"          # Device used for training/testing (e.g., 'cpu' or 'cuda')
     use_amp: bool = False           # Flag to use Automatic Mixed Precision (AMP)
     roi_size: int = 512             # The size of the square window for cropping
+    remove_boundary_objects: bool = True    # Flag to remove boundary objects when testing
     masks_subdir: str = ""          # Subdirectory where the required masks are located, e.g. 'masks/cars'
     predictions_dir: str = "."      # Directory to save predictions
     pretrained_weights: str = ""    # Path to pretrained weights

core/segmentator.py

@@ -648,6 +648,8 @@ class CellSegmentator:
         logger.info(f"├─ Seed: {common.seed}")
         logger.info(f"├─ Device: {common.device}")
         logger.info(f"├─ Use AMP: {'yes' if common.use_amp else 'no'}")
+        logger.info(f"├─ ROI size: {common.roi_size}")
+        logger.info(f"├─ Remove boundary objects: {'yes' if common.remove_boundary_objects else 'no'}")
         logger.info(f"├─ Masks subdirectory: {common.masks_subdir}")
         logger.info(f"└─ Predictions output dir: {common.predictions_dir}")
         logger.info(f"├─ Pretrained weights: {common.pretrained_weights or 'None'}")
@@ -1124,7 +1126,7 @@ class CellSegmentator:
             batch_prediction=predicted_masks,
             iou_threshold=iou_threshold,
             return_error_masks=return_error_masks,
-            remove_boundary_objects=True
+            remove_boundary_objects=self._dataset_setup.common.remove_boundary_objects
         )
         tp = stats["tp"]
         fp = stats["fp"]