nodes: add model router

README.md

@@ -22,3 +22,11 @@ image_layering:
 color_correction:
 - Adjusts the color of the target image according to another image; ported from stable diffusion WebUI
 
+
+
+## External Nodes
+
+[WAS Node suite](https://civitai.com/models/20793/was-node-suites-comfyui) 
+- Image Blend by Mask: Blend two images by a mask (but all nodes are very good)
+
+and even look this: https://civitai.com/models/24869/comfyui-custom-nodes-by-xss

__init__.py

@@ -1,9 +1,12 @@
 import custom_nodes.comfy_nodes_trojblue.image_layering as image_layering
 import custom_nodes.comfy_nodes_trojblue.color_correction as color_correction
+import custom_nodes.comfy_nodes_trojblue.model_router as model_router
+
 
 
 NODE_CLASS_MAPPINGS = {
     "layering": image_layering.Layering,                      # Layering
     "color_correction": color_correction.ColorCorrectionNode,  # ColorCorrectionNode
+    "trRouter": model_router.ModelRouterPlugin,          # ModelRouterPlugin
 
 }

color_correction.py

@@ -13,11 +13,12 @@ class ColorCorrectionNode:
                 "original_image": ("IMAGE",),
                 "target_image": ("IMAGE",),
             },
+
         }
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "color_correct"
-    CATEGORY = "trojblue_folder"
+    CATEGORY = "trNodes"
 
     def tensor_to_pil(self, img):
         if img is not None:

image_compress.py

@@ -0,0 +1,64 @@
+# import torch
+# from PIL import Image
+# import numpy as np
+#
+#
+# jpg_quality_input = ("INT", {"default": 95,
+#                "min": 50,
+#                "max": 100,
+#                "step": 1})
+# class JpgConvertNode:
+#     @classmethod
+#     def INPUT_TYPES(s):
+#         return {
+#             "required": {
+#                 "original_image": ("IMAGE",),
+#                 "jpg_quality": jpg_quality_input
+#             },
+#
+#         }
+#
+#     RETURN_TYPES = ("IMAGE",)
+#     FUNCTION = "to_jpg"
+#     CATEGORY = "trNodes"
+#
+#     def tensor_to_pil(self, img):
+#         if img is not None:
+#             i = 255. * img.cpu().numpy().squeeze()
+#             img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+#         return img
+#
+#     def apply_color_correction(self, correction, original_image):
+#
+#         # https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/22bcc7be428c94e9408f589966c2040187245d81/modules/processing.py#L44
+#
+#         correction_target = cv2.cvtColor(np.asarray(correction.copy()), cv2.COLOR_RGB2LAB)
+#
+#         image = Image.fromarray(cv2.cvtColor(exposure.match_histograms(
+#             cv2.cvtColor(
+#                 np.asarray(original_image),
+#                 cv2.COLOR_RGB2LAB
+#             ),
+#             correction_target,
+#             channel_axis=2
+#         ), cv2.COLOR_LAB2RGB).astype("uint8"))
+#
+#         image = blendLayers(image, original_image, BlendType.LUMINOSITY)
+#         return image
+#
+#     def png_to_jpg(self, png_file, jpg_file, quality=75):
+#         with Image.open(png_file) as img:
+#             img = img.convert('RGB')
+#             img.save(jpg_file, format='JPEG', quality=quality)
+#     def color_correct(self, original_image, jpg_quality):
+#         original_image = self.tensor_to_pil(original_image)
+#
+#
+#         target_image = self.tensor_to_pil(target_image)
+#
+#
+#         return (target_image,)
+#
+# NODE_CLASS_MAPPINGS = {
+#     "JpgConvertNode": JpgConvertNode
+# }

image_layering.py

@@ -37,7 +37,7 @@ class Layering:
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "apply_blend"
-    CATEGORY = "trojblue_folder"
+    CATEGORY = "trNodes"
 
     def tensor_to_pil(self, img):
         if img is not None:

model_router.py

@@ -0,0 +1,51 @@
+class ModelRouterPlugin:
+    """
+    An example node
+
+    Class methods
+    -------------
+    INPUT_TYPES (dict):
+        Tell the main program input parameters of nodes.
+
+    Attributes
+    ----------
+    RETURN_TYPES (`tuple`):
+        The type of each element in the output tulple.
+    FUNCTION (`str`):
+        The name of the entry-point method. For example, if `FUNCTION = "execute"` then it will run Example().execute()
+    OUTPUT_NODE ([`bool`]):
+        If this node is an output node that outputs a result/image from the graph. The SaveImage node is an example.
+        The backend iterates on these output nodes and tries to execute all their parents if their parent graph is properly connected.
+        Assumed to be False if not present.
+    CATEGORY (`str`):
+        The category the node should appear in the UI.
+    execute(s) -> tuple || None:
+        The entry point method. The name of this method must be the same as the value of property `FUNCTION`.
+        For example, if `FUNCTION = "execute"` then this method's name must be `execute`, if `FUNCTION = "foo"` then it must be `foo`.
+    """
+
+    FUNCTION = "execute"
+    CATEGORY = "trNodes"
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "CONDITIONING", "CONDITIONING")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "optional": {
+                "model": ("MODEL",),
+                "clip": ("CLIP",),
+                "vae": ("VAE",),
+                "conditioning1": ("CONDITIONING",),
+                "conditioning2": ("CONDITIONING",),
+            }
+        }
+
+    def execute(self, model=None, clip=None, vae=None, conditioning1=None, conditioning2=None):
+        return model, clip, vae, conditioning1, conditioning2
+
+
+# A dictionary that contains all nodes you want to export with their names
+# NOTE: names should be globally unique
+NODE_CLASS_MAPPINGS = {
+    "trRouter": ModelRouterPlugin
+}