fix: ⚡️ a few missing __doc__

nodes/faceenhance.py

@@ -16,6 +16,8 @@ from typing import Tuple
 
 
 class LoadFaceEnhanceModel:
+    """Loads a GFPGan or RestoreFormer model for face enhancement."""
+
     def __init__(self) -> None:
         pass
 
@@ -118,6 +120,8 @@ import sys
 
 
 class RestoreFace:
+    """Uses GFPGan to restore faces"""
+
     def __init__(self) -> None:
         pass
 

nodes/image_interpolation.py

@@ -33,6 +33,10 @@ def get_image(filename, subfolder, folder_type):
 
 
 class GetBatchFromHistory:
+    """Experimental node to load images from the history of the server.
+
+    Queue item without output are ignore in the count."""
+
     @classmethod
     def INPUT_TYPES(cls):
         return {

nodes/image_processing.py

@@ -276,6 +276,35 @@ class ImageCompare:
         return (torch.from_numpy(image),)
 
 
+import requests
+
+
+class LoadImageFromUrl:
+    """Load an image from the given URL"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "url": (
+                    "STRING",
+                    {
+                        "default": "https://upload.wikimedia.org/wikipedia/commons/thumb/a/a7/Example.jpg/800px-Example.jpg"
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "load"
+    CATEGORY = "image"
+
+    def load(self, url):
+        # get the image from the url
+        image = Image.open(requests.get(url, stream=True).raw)
+        return (pil2tensor(image),)
+
+
 class Denoise:
     """Denoise an image using total variation minimization."""
 
@@ -477,9 +506,7 @@ class ImagePremultiply:
 
 
 class ImageResizeFactor:
-    """
-    Extracted mostly from WAS Node Suite, with a few edits (most notably multiple image support) and less features.
-    """
+    """Extracted mostly from WAS Node Suite, with a few edits (most notably multiple image support) and less features."""
 
     def __init__(self):
         pass
@@ -717,4 +744,5 @@ __nodes__ = [
     ImagePremultiply,
     ImageResizeFactor,
     SaveImageGrid,
+    LoadImageFromUrl,
 ]

nodes/mask.py

@@ -2,7 +2,10 @@ from rembg import remove
 from ..utils import pil2tensor, tensor2pil
 from PIL import Image
 
+
 class ImageRemoveBackgroundRembg:
+    """Removes the background from the input using Rembg."""
+
     def __init__(self):
         pass
 
@@ -11,47 +14,80 @@ class ImageRemoveBackgroundRembg:
         return {
             "required": {
                 "image": ("IMAGE",),
-                "alpha_matting": (["True","False"], {"default":"False"},),
-                "alpha_matting_foreground_threshold": ("INT", {"default":240, "min": 0, "max": 255},),
-                "alpha_matting_background_threshold": ("INT", {"default":10, "min": 0, "max": 255},),
-                "alpha_matting_erode_size": ("INT", {"default":10, "min": 0, "max": 255},),
-                "post_process_mask": (["True","False"], {"default":"False"},),
-                "bgcolor": ("COLOR", {"default":"black"},),
-                
+                "alpha_matting": (
+                    ["True", "False"],
+                    {"default": "False"},
+                ),
+                "alpha_matting_foreground_threshold": (
+                    "INT",
+                    {"default": 240, "min": 0, "max": 255},
+                ),
+                "alpha_matting_background_threshold": (
+                    "INT",
+                    {"default": 10, "min": 0, "max": 255},
+                ),
+                "alpha_matting_erode_size": (
+                    "INT",
+                    {"default": 10, "min": 0, "max": 255},
+                ),
+                "post_process_mask": (
+                    ["True", "False"],
+                    {"default": "False"},
+                ),
+                "bgcolor": (
+                    "COLOR",
+                    {"default": "black"},
+                ),
             },
         }
 
-    RETURN_TYPES = ("IMAGE","MASK","IMAGE",)
-    RETURN_NAMES = ("Image (rgba)","Mask","Image",)
+    RETURN_TYPES = (
+        "IMAGE",
+        "MASK",
+        "IMAGE",
+    )
+    RETURN_NAMES = (
+        "Image (rgba)",
+        "Mask",
+        "Image",
+    )
     FUNCTION = "remove_background"
     CATEGORY = "image"
+
     # bgcolor: Optional[Tuple[int, int, int, int]]
-    def remove_background(self, image, alpha_matting, alpha_matting_foreground_threshold, alpha_matting_background_threshold, alpha_matting_erode_size, post_process_mask, bgcolor):
+    def remove_background(
+        self,
+        image,
+        alpha_matting,
+        alpha_matting_foreground_threshold,
+        alpha_matting_background_threshold,
+        alpha_matting_erode_size,
+        post_process_mask,
+        bgcolor,
+    ):
         image = remove(
-                data=tensor2pil(image),
-                alpha_matting=alpha_matting == "True",
-                alpha_matting_foreground_threshold=alpha_matting_foreground_threshold,
-                alpha_matting_background_threshold=alpha_matting_background_threshold,
-                alpha_matting_erode_size=alpha_matting_erode_size,
-                session=None,
-                only_mask=False,
-                post_process_mask=post_process_mask == "True",
-                bgcolor=None
-            )
-        
-        
+            data=tensor2pil(image),
+            alpha_matting=alpha_matting == "True",
+            alpha_matting_foreground_threshold=alpha_matting_foreground_threshold,
+            alpha_matting_background_threshold=alpha_matting_background_threshold,
+            alpha_matting_erode_size=alpha_matting_erode_size,
+            session=None,
+            only_mask=False,
+            post_process_mask=post_process_mask == "True",
+            bgcolor=None,
+        )
+
         # extract the alpha to a new image
         mask = image.getchannel(3)
-        
+
         # add our bgcolor behind the image
         image_on_bg = Image.new("RGBA", image.size, bgcolor)
-        
+
         image_on_bg.paste(image, mask=mask)
-        
-        
+
         return (pil2tensor(image), pil2tensor(mask), pil2tensor(image_on_bg))
 
 
 __nodes__ = [
     ImageRemoveBackgroundRembg,
-]
+]

nodes/number.py

@@ -1,3 +1,27 @@
+class IntToBool:
+    """Basic int to bool conversion"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "int": (
+                    "INT",
+                    {
+                        "default": 0,
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("BOOL",)
+    FUNCTION = "int_to_bool"
+    CATEGORY = "number"
+
+    def int_to_bool(self, int):
+        return (bool(int),)
+
+
 class IntToNumber:
     """Node addon for the WAS Suite. Converts a "comfy" INT to a NUMBER."""
 
@@ -8,7 +32,16 @@ class IntToNumber:
     def INPUT_TYPES(cls):
         return {
             "required": {
-                "int": ("INT", {"default": 0, "min": 0, "max": 1e9, "step": 1}),
+                "int": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": -1e9,
+                        "max": 1e9,
+                        "step": 1,
+                        "forceInput": True,
+                    },
+                ),
             }
         }
 
@@ -17,10 +50,46 @@ class IntToNumber:
     CATEGORY = "number"
 
     def int_to_number(self, int):
+        return (int,)
+
+
+class FloatToNumber:
+    """Node addon for the WAS Suite. Converts a "comfy" FLOAT to a NUMBER."""
+
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "float": (
+                    "FLOAT",
+                    {
+                        "default": 0,
+                        "min": -1e9,
+                        "max": 1e9,
+                        "step": 1,
+                        "forceInput": True,
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("NUMBER",)
+    FUNCTION = "float_to_number"
+    CATEGORY = "number"
+
+    def float_to_number(self, float):
+        return (float,)
+
+
 
         return (int,)
 
 __nodes__ = [
+    FloatToNumber,
+    IntToBool,
     IntToNumber,
 
 ]