fix bug of converting BF16 tensor to pillow image

py/imagefunc.py

@@ -137,7 +137,15 @@ def tensor2np(tensor: torch.Tensor) -> List[np.ndarray]:
         return [np.clip(255.0 * t.cpu().numpy(), 0, 255).astype(np.uint8) for t in tensor]
 
 def tensor2pil(t_image: torch.Tensor)  -> Image:
-    return Image.fromarray(np.clip(255.0 * t_image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+    if t_image.dtype != torch.float32:
+        t_image = t_image.float()
+    return Image.fromarray(
+        np.clip(
+            255.0 * t_image.cpu().numpy().squeeze(),
+            0,
+            255
+        ).astype(np.uint8)
+    )
 
 def tensor2cv2(image:torch.Tensor) -> np.array:
     if image.dim() == 4:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_layerstyle"
 description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
-version = "2.0.32"
+version = "2.0.33"
 license = {text = "MIT License"}
 dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "scikit_learn", "opencv-contrib-python", "pymatting", "timm", "colour-science",  "transformers",  "blend_modes",  "huggingface_hub", "loguru"]