fix wsi

src/hest/wsi.py

@@ -10,6 +10,7 @@
 import numpy as np
 import openslide
 from PIL import Image
+from shapely import Polygon
 
 
 class CucimWarningSingleton:
@@ -115,7 +116,17 @@ def read_region(self, location, level, size) -> np.ndarray:
  img = self.img
  x_start, y_start = location[0], location[1]
  x_size, y_size = size[0], size[1]
- return img[y_start:y_start + y_size, x_start:x_start + x_size]
+ x_end, y_end = x_start + x_size, y_start + y_size
+ padding_left = max(0 - x_start, 0)
+ padding_top = max(0 - y_start, 0)
+ padding_right = max(x_start + x_size - self.width, 0)
+ padding_bottom = max(y_start + y_size - self.height, 0)
+ x_start, y_start = max(x_start, 0), max(y_start, 0)
+ x_end, y_end = min(x_end, self.width), min(y_end, self.height)
+ tile = img[y_start:y_end, x_start:x_end]
+ padded_tile = np.pad(tile, ((padding_top, padding_bottom), (padding_left, padding_right), (0, 0)), mode='constant', constant_values=0)
+
+ return padded_tile
 
  def get_thumbnail(self, width, height) -> np.ndarray:
  return cv2.resize(self.img, (width, height))
@@ -239,7 +250,8 @@ def __init__(
  overlap: int = 0,
  mask: gpd.GeoDataFrame = None,
  coords_only = False,
- custom_coords = None
+ custom_coords = None,
+ threshold = 0.15
  ):
  """ Initialize patcher, compute number of (masked) rows, columns.
 
@@ -251,6 +263,8 @@ def __init__(
  overlap (int, optional): overlap size in pixel before rescaling. Defaults to 0.
  mask (gpd.GeoDataFrame, optional): geopandas dataframe of Polygons. Defaults to None.
  coords_only (bool, optional): whenever to extract only the coordinates insteaf of coordinates + tile. Default to False.
+ threshold (float, optional): minimum proportion of the patch under tissue to be kept.
+ This argument is ignored if mask=None, passing threshold=0 will be faster
  """
  self.wsi = wsi
  self.overlap = overlap
@@ -283,9 +297,8 @@ def __init__(
  if round(custom_coords[0][0]) != custom_coords[0][0]:
  raise ValueError("custom_coords must be a (N, 2) array of int")
  coords = custom_coords
-
  if self.mask is not None:
- self.valid_patches_nb, self.valid_coords = self._compute_masked(coords)
+ self.valid_patches_nb, self.valid_coords = self._compute_masked(coords, threshold)
  else:
  self.valid_patches_nb, self.valid_coords = len(coords), coords
 
@@ -295,17 +308,43 @@ def _colrow_to_xy(self, col, row):
  y = row * (self.patch_size_src) - self.overlap * np.clip(row - 1, 0, None)
  return (x, y) 
 
- def _compute_masked(self, coords) -> None:
+ def _compute_masked(self, coords, threshold) -> None:
  """ Compute tiles which center falls under the tissue """
 
- # TODO spots are already at the center
- # Note: we don't take into account the overlap size we calculating centers
- xy_centers = coords + self.patch_size_src // 2
+ # Filter coordinates by bounding boxes of mask polygons
+ bounding_boxes = self.mask.geometry.bounds
+ valid_coords = []
+ for _, bbox in bounding_boxes.iterrows():
+ bbox_coords = coords[
+ (coords[:, 0] >= bbox['minx'] - self.patch_size_src) & (coords[:, 0] <= bbox['maxx'] + self.patch_size_src) & 
+ (coords[:, 1] >= bbox['miny'] - self.patch_size_src) & (coords[:, 1] <= bbox['maxy'] + self.patch_size_src)
+ ]
+ valid_coords.append(bbox_coords)
+
+ if len(valid_coords) > 0:
+ coords = np.vstack(valid_coords)
+ coords = np.unique(coords, axis=0)
+ else:
+ coords = np.array([])
+
 
  union_mask = self.mask.union_all()
-
- points = gpd.points_from_xy(xy_centers[:, 0], xy_centers[:, 1])
- valid_mask = gpd.GeoSeries(points).within(union_mask).values
+
+ squares = [
+ Polygon([
+ (xy[0], xy[1]), 
+ (xy[0] + self.patch_size_src, xy[1]), 
+ (xy[0] + self.patch_size_src, xy[1] + self.patch_size_src), 
+ (xy[0], xy[1] + self.patch_size_src)]) 
+ for xy in coords
+ ]
+ if threshold == 0:
+ valid_mask = gpd.GeoSeries(squares).intersects(union_mask).values
+ else:
+ gdf = gpd.GeoSeries(squares)
+ areas = gdf.area
+ valid_mask = gdf.intersection(union_mask).area >= threshold * areas
+
  valid_patches_nb = valid_mask.sum()
  valid_coords = coords[valid_mask]
  return valid_patches_nb, valid_coords