JANK

__init__.py

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

nodes.py

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+import os
+
+import cv2
+import numpy as np
+import torch
+import torchvision.transforms as transforms
+
+from .PixelOE.pixeloe import pixelize
+
+script_directory = os.path.dirname(os.path.abspath(__file__))
+
+
+class PixelOE:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "img": ("IMAGE",),
+                "mode": (["contrast"],),
+                "target_size": ("INT", {
+                    "default": 128,
+                    "min": 0,
+                    "max": 4096,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "patch_size": ("INT", {
+                    "default": 16,
+                    "min": 0,
+                    "max": 4096,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "thickness": ("INT", {
+                    "default": 2,
+                    "min": 0,
+                    "max": 4096,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "color_matching": ("BOOLEAN", {
+                    "default": True
+                }),
+                "contrast": ("FLOAT", {
+                    "default": 1.0,
+                    "min": 0.0,
+                    "max": 10.0,
+                    "step": 0.01,
+                    "round": 0.001,
+                    "display": "number"
+                }),
+                "saturation": ("FLOAT", {
+                    "default": 1.0,
+                    "min": 0.0,
+                    "max": 10.0,
+                    "step": 0.01,
+                    "round": 0.001,
+                    "display": "number"
+                }),
+                "colors": ("INT", {
+                    "default": 0,
+                    "min": 0,
+                    "max": 4096,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "no_upscale": ("BOOLEAN", {
+                    "default": False
+                }),
+                "no_downscale": ("BOOLEAN", {
+                    "default": False
+                }),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "process"
+
+    CATEGORY = "Pixelize"
+
+    def process(self, img, mode, target_size, patch_size, thickness, color_matching, contrast, saturation, colors, no_upscale, no_downscale):
+
+        # Convert image from PyTorch tensor to NumPy array
+        img = img.squeeze().numpy()
+
+        # Convert image from float32 to uint8
+        img = (img * 255).astype(np.uint8)
+
+        # Convert image from RGB to BGR
+        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+        print(img.shape)
+
+        img_pix = pixelize(img, mode, target_size, patch_size, thickness, color_matching, contrast, saturation, colors, no_upscale, no_downscale)
+
+        img_pix = cv2.cvtColor(img_pix, cv2.COLOR_BGR2RGB)
+        img_pix_t = np.array(img_pix).astype(np.float32) / 255.0
+        img_pix_t = torch.from_numpy(img_pix_t)[None,]
+        return (img_pix_t,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "PixelOE": PixelOE,
+}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "PixelOE": "PixelOE",
+}

requirements.txt

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+torch
+torchvision
+opencv-python
+numpy