Upload TTP_tile_preprocessor.py

update the comfyui custom_node for image preprocess. can simulate the webui pre-processor effect for controlnet image adjustment

TTP_tile_preprocessor.py

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+import cv2
+import numpy as np
+import torch
+from PIL import Image
+
+NODE_NAME = 'TTPlanet_Tile_Preprocessor'
+
+# 图像转换函数
+def pil2tensor(image: Image) -> torch.Tensor:
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+        
+def tensor2pil(t_image: torch.Tensor) -> Image:
+    return Image.fromarray(np.clip(255.0 * t_image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+class TTPlanet_Tile_Preprocessor:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # 输入的tensor图像
+                "scale_factor": ("FLOAT", {"default": 2.0, "min": 1.0, "max": 8.0, "step": 0.1}),  # 缩放因子
+            },
+            "optional": {}
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image_output",)
+    FUNCTION = 'process_image'
+    CATEGORY = 'TTP_TILE'
+
+    def process_image(self, image, scale_factor):
+        ret_images = []
+    
+        for i in image:
+            # Convert tensor to PIL for processing
+            _canvas = tensor2pil(torch.unsqueeze(i, 0)).convert('RGB')
+            
+            # Convert PIL to OpenCV format
+            img_np = np.array(_canvas)[:, :, ::-1]
+    
+            # 获取原始尺寸
+            height, width = img_np.shape[:2]
+    
+            # 计算新尺寸
+            new_width = int(width / scale_factor)
+            new_height = int(height / scale_factor)
+    
+            # 1. 使用cv2.INTER_AREA方法缩小图像
+            resized_down = cv2.resize(img_np, (new_width, new_height), interpolation=cv2.INTER_AREA)
+    
+            # 2. 使用linear方法放大回原尺寸
+            resized_img = cv2.resize(resized_down, (width, height), interpolation=cv2.INTER_CUBIC)
+            
+            # Convert OpenCV back to PIL and then to tensor
+            pil_img = Image.fromarray(resized_img[:, :, ::-1])
+            tensor_img = pil2tensor(pil_img)
+            ret_images.append(tensor_img)
+        
+        return (torch.cat(ret_images, dim=0),)
+
+NODE_CLASS_MAPPINGS = {
+    "Image Processing: TTPlanet_Tile_Preprocessor": TTPlanet_Tile_Preprocessor
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "Image Processing: TTPlanet_Tile_Preprocessor": "TTPlanet Tile Preprocessor"
+}