v 2.1.1

Modular utils
Typo `create_image_grid_by_columns` -> `create_images_grid_by_columns`
Typo `create_image_grid_by_rows` -> `create_images_grid_by_rows`

src/nodes/images_grid.py

@@ -4,8 +4,8 @@ from ..base import BaseNode, Image
 from ..utils import (
     tensor_to_pillow,
     pillow_to_tensor,
-    create_image_grid_by_columns,
-    create_image_grid_by_rows,
+    create_images_grid_by_columns,
+    create_images_grid_by_rows,
 )
 
 
@@ -36,7 +36,7 @@ class ImagesGridByColumnsNode(BaseImagesGridNode):
         return cls._create_input_types("max_columns")
 
     def execute(self, images: Image, **kw) -> tuple[Image]:
-        return self._create_execute(images, create_image_grid_by_columns, kw)
+        return self._create_execute(images, create_images_grid_by_columns, kw)
 
 
 class ImagesGridByRowsNode(BaseImagesGridNode):
@@ -45,4 +45,4 @@ class ImagesGridByRowsNode(BaseImagesGridNode):
         return cls._create_input_types("max_rows")
 
     def execute(self, images: Image, **kw) -> tuple[Image]:
-        return self._create_execute(images, create_image_grid_by_rows, kw)
+        return self._create_execute(images, create_images_grid_by_rows, kw)

src/utils.py

@@ -1,53 +0,0 @@
-import typing as t
-
-import torch
-import numpy as np
-from PIL import Image
-
-
-def tensor_to_pillow(image):
-    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
-
-
-def pillow_to_tensor(image):
-    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
-
-
-def create_image_grid_by_columns(
-    images: t.List[Image.Image],
-    gap: int,
-    max_columns: int,
-) -> Image.Image:
-    max_rows = (len(images) + max_columns - 1) // max_columns
-    return create_image_grid(images=images, gap=gap, max_columns=max_columns, max_rows=max_rows)
-
-
-def create_image_grid_by_rows(
-    images: t.List[Image.Image],
-    gap: int,
-    max_rows: int,
-) -> Image.Image:
-    max_columns = (len(images) + max_rows - 1) // max_rows
-    return create_image_grid(images=images, gap=gap, max_columns=max_columns, max_rows=max_rows)
-
-
-def create_image_grid(
-    images: t.List[Image.Image],
-    gap: int,
-    max_columns: int,
-    max_rows: int,
-) -> Image.Image:
-    size = images[0].size
-
-    width = size[0] * max_columns + (max_columns - 1) * gap
-    height = size[1] * max_rows + (max_rows - 1) * gap
-
-    grid_image = Image.new("RGB", (width, height), color="white")
-
-    for i, image in enumerate(images):
-        x = (i % max_columns) * (size[0] + gap)
-        y = (i // max_columns) * (size[1] + gap)
-
-        grid_image.paste(image, (x, y))
-
-    return grid_image

src/utils/__init__.py

@@ -0,0 +1,5 @@
+from .images_grid import (
+    create_images_grid_by_columns,
+    create_images_grid_by_rows,
+)
+from .tensor_convert import tensor_to_pillow, pillow_to_tensor

src/utils/grid_annotations.py

@@ -0,0 +1,6 @@
+from __future__ import annotations
+
+import typing as t
+
+
+def create_grid_annotations() -> None: ...

src/utils/images_grid.py

@@ -0,0 +1,64 @@
+import typing as t
+
+from PIL import Image, ImageDraw, ImageFont
+
+
+def create_images_grid_by_columns(
+    images: t.List[Image.Image],
+    gap: int,
+    max_columns: int,
+) -> Image.Image:
+    max_rows = (len(images) + max_columns - 1) // max_columns
+    return _create_images_grid(images=images, gap=gap, max_columns=max_columns, max_rows=max_rows)
+
+
+def create_images_grid_by_rows(
+    images: t.List[Image.Image],
+    gap: int,
+    max_rows: int,
+) -> Image.Image:
+    max_columns = (len(images) + max_rows - 1) // max_rows
+    return _create_images_grid(images=images, gap=gap, max_columns=max_columns, max_rows=max_rows)
+
+
+def _create_images_grid(
+    images: t.List[Image.Image],
+    gap: int,
+    max_columns: int,
+    max_rows: int,
+) -> Image.Image:
+    size = images[0].size
+
+    grid_width = size[0] * max_columns + (max_columns - 1) * gap
+    grid_height = size[1] * max_rows + (max_rows - 1) * gap
+
+    grid_image = Image.new("RGB", (grid_width, grid_height), color="white")
+
+    for i, image in enumerate(images):
+        image = image.crop((0, 0, size[0], size[1]))
+        x = (i % max_columns) * (size[0] + gap)
+        y = (i // max_columns) * (size[1] + gap)
+
+        grid_image.paste(image, (x, y))
+
+    return grid_image
+
+
+def _draw_center_text(
+  text: str,
+  draw: ImageDraw.ImageDraw,
+  font: ImageFont.ImageFont,
+  fill: int = 128,
+):
+  image = draw.im  # type: ignore
+  _, _, *text_size = draw.textbbox((0, 0), text, font=font)
+  draw.text(
+    (
+      (image.size[0]-text_size[0])/2,
+      (image.size[1]-text_size[1])/2,
+    ),
+    text,
+    font=font,
+    fill=fill,
+  )
+  return image

src/utils/tensor_convert.py

@@ -0,0 +1,13 @@
+import typing as t
+
+import torch
+import numpy as np
+from PIL import Image
+
+
+def tensor_to_pillow(image: t.Any) -> Image.Image:
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+
+def pillow_to_tensor(image: Image.Image) -> t.Any:
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)