BiggestTissueBoxMask as default extraction_mask in Tiler(s)

src/histolab/filters/image_filters.py

@@ -40,7 +40,7 @@ class Filter(Protocol):
     def __call__(
         self, img: Union[PIL.Image.Image, np.ndarray]
     ) -> Union[PIL.Image.Image, np.ndarray]:
-        pass
+        pass  # pragma: no cover
 
     def __repr__(self) -> str:
         return self.__class__.__name__ + "()"
@@ -52,7 +52,7 @@ class ImageFilter(Filter, Protocol):
 
     @abstractmethod
     def __call__(self, img: PIL.Image.Image) -> Union[PIL.Image.Image, np.ndarray]:
-        pass
+        pass  # pragma: no cover
 
 
 class Compose(ImageFilter):

src/histolab/filters/morphological_filters.py

@@ -37,7 +37,7 @@ class MorphologicalFilter(Filter, Protocol):
 
     @abstractmethod
     def __call__(self, np_mask: np.ndarray) -> np.ndarray:
-        pass
+        pass  # pragma: no cover
 
 
 class RemoveSmallObjects(MorphologicalFilter):

src/histolab/masks.py

@@ -56,7 +56,7 @@ def __call__(self, slide):
     @abstractmethod
     def _mask(self, slide):  # pragma: no cover
         # This property will be supplied by the inheriting classes individually
-        pass
+        pass  # pragma: no cover
 
 
 class BiggestTissueBoxMask(BinaryMask):

src/histolab/scorer.py

@@ -41,7 +41,7 @@ class Scorer(Protocol):
 
     @abstractmethod
     def __call__(self, tile: Tile) -> float:
-        pass
+        pass  # pragma: no cover
 
 
 class RandomScorer(Scorer):

src/histolab/tiler.py

@@ -75,13 +75,18 @@ def box_mask(self, slide: Slide) -> np.ndarray:
         return biggest_tissue_box_mask(slide)
 
     @abstractmethod
-    def extract(self, slide: Slide, extraction_mask: BinaryMask, log_level: str):
-        pass
+    def extract(
+        self,
+        slide: Slide,
+        log_level: str,
+        extraction_mask: BinaryMask = BiggestTissueBoxMask(),
+    ):
+        pass  # pragma: no cover
 
     def locate_tiles(
         self,
         slide: Slide,
-        extraction_mask: BinaryMask,
+        extraction_mask: BinaryMask = BiggestTissueBoxMask(),
         scale_factor: int = 32,
         alpha: int = 128,
         outline: str = "red",
@@ -94,6 +99,7 @@ def locate_tiles(
             Slide reference where placing the tiles
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`
         scale_factor: int
             Scaling factor for the returned image. Default is 32.
         alpha: int
@@ -172,9 +178,9 @@ def _tile_filename(
         return tile_filename
 
     def _tiles_generator(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> Tuple[Tile, CoordinatePair]:
-        pass
+        pass  # pragma: no cover
 
     def _validate_level(self, slide: Slide) -> None:
         """Validate the Tiler's level according to the Slide.
@@ -259,7 +265,10 @@ def __init__(
         self.suffix = suffix
 
     def extract(
-        self, slide: Slide, extraction_mask: BinaryMask, log_level: str = "INFO"
+        self,
+        slide: Slide,
+        extraction_mask: BinaryMask = BiggestTissueBoxMask(),
+        log_level: str = "INFO",
     ) -> None:
         """Extract tiles arranged in a grid and save them to disk, following this
         filename pattern:
@@ -271,6 +280,7 @@ def extract(
             Slide from which to extract the tiles
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
         log_level : str, {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}
             Threshold level for the log messages. Default "INFO"
 
@@ -351,7 +361,7 @@ def _grid_coordinates_from_bbox_coordinates(
                 yield tile_wsi_coords
 
     def _grid_coordinates_generator(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> CoordinatePair:
         """Generate Coordinates at level 0 of grid tiles within the tissue.
 
@@ -362,6 +372,7 @@ def _grid_coordinates_generator(
             tissue area.
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Yields
         -------
@@ -384,7 +395,7 @@ def _grid_coordinates_generator(
             )
 
     def _tiles_generator(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> Tuple[Tile, CoordinatePair]:
         """Generator of tiles arranged in a grid.
 
@@ -394,6 +405,7 @@ def _tiles_generator(
             Slide from which to extract the tiles
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Yields
         -------
@@ -504,7 +516,10 @@ def __init__(
         self.suffix = suffix
 
     def extract(
-        self, slide: Slide, extraction_mask: BinaryMask, log_level: str = "INFO"
+        self,
+        slide: Slide,
+        extraction_mask: BinaryMask = BiggestTissueBoxMask(),
+        log_level: str = "INFO",
     ) -> None:
         """Extract random tiles and save them to disk, following this filename pattern:
         `{prefix}tile_{tiles_counter}_level{level}_{x_ul_wsi}-{y_ul_wsi}-{x_br_wsi}-{y_br_wsi}{suffix}`
@@ -515,6 +530,7 @@ def extract(
             Slide from which to extract the tiles
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
         log_level: str, {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}
             Threshold level for the log messages. Default "INFO"
 
@@ -566,7 +582,7 @@ def tile_size(self, tile_size_: Tuple[int, int]):
     # ------- implementation helpers -------
 
     def _random_tile_coordinates(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> CoordinatePair:
         """Return 0-level Coordinates of a tile picked at random within the box.
 
@@ -576,6 +592,7 @@ def _random_tile_coordinates(
             Slide from which calculate the coordinates. Needed to calculate the box.
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Returns
         -------
@@ -608,7 +625,7 @@ def _random_tile_coordinates(
         return tile_wsi_coords
 
     def _tiles_generator(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> Tuple[Tile, CoordinatePair]:
         """Generate Random Tiles within a slide box.
 
@@ -622,6 +639,7 @@ def _tiles_generator(
             The Whole Slide Image from which to extract the tiles.
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Yields
         ------
@@ -714,7 +732,7 @@ def __init__(
     def extract(
         self,
         slide: Slide,
-        extraction_mask: BinaryMask,
+        extraction_mask: BinaryMask = BiggestTissueBoxMask(),
         report_path: str = None,
         log_level: str = "INFO",
     ) -> None:
@@ -730,6 +748,7 @@ def extract(
             Slide from which to extract the tiles
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
         report_path : str, optional
             Path to the CSV report. If None, no report will be saved
         log_level: str, {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}
@@ -773,7 +792,7 @@ def extract(
     # ------- implementation helpers -------
 
     def _tiles_generator(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> Tuple[List[Tuple[float, CoordinatePair]], List[Tuple[float, CoordinatePair]]]:
         r"""Calculate the tiles with the highest scores and their extraction coordinates
 
@@ -783,6 +802,7 @@ def _tiles_generator(
             The slide to extract the tiles from.
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Returns
         -------
@@ -892,7 +912,7 @@ def _scale_scores(
         return list(zip(scores_scaled, coords))
 
     def _scores(
-        self, slide: Slide, extraction_mask: BinaryMask
+        self, slide: Slide, extraction_mask: BinaryMask = BiggestTissueBoxMask()
     ) -> List[Tuple[float, CoordinatePair]]:
         """Calculate the scores for all the tiles extracted from the ``slide``.
 
@@ -902,6 +922,7 @@ def _scores(
             The slide to extract the tiles from.
         extraction_mask : BinaryMask
             BinaryMask object defining how to compute a binary mask from a Slide.
+            Default `BiggestTissueBoxMask`.
 
         Returns
         -------

tests/integration/test_tiler.py

@@ -210,11 +210,12 @@ def it_locates_tiles_on_the_slide(
             r"Input image must be RGB. NOTE: the image will be converted to RGB before"
             r" HED conversion."
         )
-        binary_mask = BiggestTissueBoxMask()
 
         with pytest.warns(UserWarning, match=expected_warning_regex):
+            # no binary mask object passed to locate_tiles
+            # default value = BiggestTissueBoxMask
             tiles_location_img = scored_tiles_extractor.locate_tiles(
-                slide, binary_mask, scale_factor=10
+                slide, scale_factor=10
             )
         # --- Expanding test report with actual and expected images ---
         expand_tests_report(request, expected=expected_img, actual=tiles_location_img)