initial (EnhanceDetail only)

TODO.txt

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+guided filter for seg/mask
+bilateral filter image
+deconvolution?

__init__.py

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+from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+
+__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']

import_error_install.bat

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+@echo off
+
+set "requirements_txt=%~dp0\requirements.txt"
+set "python_exec=..\..\..\python_embeded\python.exe"
+
+echo installing requirements...
+
+if exist "%python_exec%" (
+    echo Installing with ComfyUI Portable
+	%python_exec% -s -m pip uninstall opencv-python opencv-contrib-python opencv-python-headless opencv-contrib-python-headless
+    for /f "delims=" %%i in (%requirements_txt%) do (
+        %python_exec% -s -m pip install "%%i"
+    )
+) else (
+    echo Installing with system Python
+	pip uninstall opencv-python opencv-contrib-python opencv-python-headless opencv-contrib-python-headless
+    for /f "delims=" %%i in (%requirements_txt%) do (
+        pip install "%%i"
+    )
+)
+
+pause

install.bat

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+@echo off
+
+set "requirements_txt=%~dp0\requirements.txt"
+set "python_exec=..\..\..\python_embeded\python.exe"
+
+echo installing requirements...
+
+if exist "%python_exec%" (
+    echo Installing with ComfyUI Portable
+    for /f "delims=" %%i in (%requirements_txt%) do (
+        %python_exec% -s -m pip install "%%i"
+    )
+) else (
+    echo Installing with system Python
+    for /f "delims=" %%i in (%requirements_txt%) do (
+        pip install "%%i"
+    )
+)
+
+pause

nodes.py

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+import torch
+import os
+import sys
+
+import numpy as np
+import cv2
+from cv2.ximgproc import guidedFilter
+import copy
+
+
+class EnhanceDetail:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "filter_radius": ("INT", {
+                    "default": 2,
+                    "min": 1,
+                    "max": 64,
+                    "step": 1
+                }),
+                "sigma": ("FLOAT", {
+                    "default": 0.01,
+                    "min": 0.01,
+                    "max": 10.0,
+                    "step": 0.01
+                }),
+                "denoise": ("FLOAT", {
+                    "default": 0.01,
+                    "min": 0.0,
+                    "max": 1.0,
+                    "step": 0.01
+                }),
+                "detail_mult": ("FLOAT", {
+                    "default": 2.0,
+                    "min": 0.0,
+                    "max": 100.0,
+                    "step": 0.1
+                }),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "enhance"
+
+    CATEGORY = "image/filters"
+
+    def enhance(self, images: torch.Tensor, filter_radius: int, sigma: float, denoise: float, detail_mult: float):
+        
+        if filter_radius == 0:
+            return (images,)
+        
+        d = filter_radius * 2 + 1
+        
+        dup = copy.deepcopy(images.cpu().numpy())
+        
+        for i in range(len(dup)):
+            image = dup[i]
+            imgB = image
+            if denoise>0.0:
+                imgB = cv2.bilateralFilter(image, d, denoise, d)
+            
+            imgG = guidedFilter(image, image, d, sigma)
+            
+            details = (imgB/imgG - 1) * detail_mult + 1
+            dup[i] = details*imgG - imgB + image
+        
+        return (torch.from_numpy(dup),)
+
+
+NODE_CLASS_MAPPINGS = {
+    #"SaveTiff": SaveTiff,
+    "EnhanceDetail": EnhanceDetail,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    #"SaveTiff": "Save Tiff",
+    "EnhanceDetail": "Enhance Detail",
+}

requirements.txt

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+opencv-contrib-python