drop skimage dependency (#57)

* drop dependency

* bump patch version and remove virtualenv dependency

CCAgT_utils/converters/CCAgT.py

@@ -509,7 +509,7 @@ def single_core_to_PS_COCO(
     if df['image_width'].nunique() == df['image_height'].nunique() == 1:
         w = int(df['image_width'].unique()[0])
         h = int(df['image_height'].unique()[0])
-        output_template = np.zeros((h, w, 3), dtype=np.uint8)
+        output_template = Image.fromarray(np.zeros((h, w, 3), dtype=np.uint8))
     else:
         output_template = None
 
@@ -532,15 +532,15 @@ def single_core_to_PS_COCO(
 
         segments_info = []
 
-        if isinstance(output_template, np.ndarray):
+        if isinstance(output_template, Image.Image):
             out = output_template.copy()
         else:
             w = int(df_by_img['image_width'].unique()[0])
             h = int(df_by_img['image_height'].unique()[0])
-            out = np.zeros((h, w, 3), dtype=np.uint8)
+            out = Image.fromarray(np.zeros((h, w, 3), dtype=np.uint8))
 
         for ann in annotations_sorted:
-            out = draw_annotation(out, ann, ann.color.rgb, out.shape[:2])
+            out = draw_annotation(out, ann, ann.color.rgb)
             segments_info.append({
                 'id': COCO_PS.color_to_id(ann.color),
                 'category_id': ann.category_id,
@@ -555,7 +555,7 @@ def single_core_to_PS_COCO(
             _out_dir = os.path.join(out_dir, df_by_img.iloc[0]['slide_id'])
 
         output_filename = os.path.join(_out_dir, output_basename)
-        Image.fromarray(out).save(output_filename)
+        out.save(output_filename)
         annotations_panoptic.append(panoptic_record)
     return annotations_panoptic
 

CCAgT_utils/converters/masks.py

@@ -3,7 +3,8 @@
 import collections
 
 import numpy as np
-from skimage.draw import polygon
+from PIL import Image
+from PIL import ImageDraw
 
 from CCAgT_utils.categories import Categories
 from CCAgT_utils.types.annotation import Annotation
@@ -39,23 +40,21 @@ def annotations_to_mask(
 
     annotations_sorted = order_annotations_to_draw(annotations)
 
-    out = np.zeros(shape, dtype=np.uint8)
+    out = Image.fromarray(np.zeros(shape, dtype=np.uint8))
     for ann in annotations_sorted:
-        out = draw_annotation(out, ann, ann.category_id, shape)
+        out = draw_annotation(out, ann, ann.category_id)
 
-    return Mask(out)
+    return Mask(np.array(out))
 
 
 def draw_annotation(
-    target: np.ndarray,
+    target: Image.Image,
     annotation: Annotation,
     value: int | tuple[int, int, int],
-    shape: tuple[int, int] | None = None,
-) -> np.ndarray:
+) -> Image.Image:
     for geo in annotation:
         pol_x, pol_y = geo.exterior.coords.xy
-
-        _x, _y = polygon(pol_y, pol_x, shape)
-        target[_x, _y] = value
+        coords = list(zip(pol_x, pol_y))
+        ImageDraw.Draw(target).polygon(coords, fill=value)
 
     return target

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = CCAgT_utils
-version = 0.2.3-alpha
+version = 0.2.4-alpha
 description = A framework of utilities to help at the use of the CCAgT dataset
 long_description = file: README.md
 long_description_content_type = text/markdown
@@ -29,9 +29,7 @@ install_requires =
     pandas>=1.1.5
     pillow>=9.0.1
     pyarrow>=7.0.0
-    scikit-image>=0.19.2
     shapely>=1.8.0
-    virtualenv>=20.0.8
 python_requires = >=3.7
 
 [options.packages.find]