delete as the new version is uploaded

TTP_tile_preprocessor.py

@@ -1,70 +0,0 @@
-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"
-}