Delete web_roi.py

web_roi.py

@@ -1,64 +0,0 @@
-import torch
-import numpy as np
-from PIL import Image
-import base64
-from io import BytesIO
-import re
-
-class WebROICapture:
-    def __init__(self):
-        pass
-  
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                # 必须有这个输入项，前端JS才会把图片数据塞进来
-                "image_data": ("STRING", {"default": "", "multiline": True}), 
-            },
-            "optional": {
-                # 用作触发器，每次数字变化时触发
-                "trigger_always": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "forceInput": True}),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("image",)
-    FUNCTION = "capture_screen"
-    CATEGORY = "WebROI"
-
-    def capture_screen(self, image_data, trigger_always=0):
-        try:
-            # 1. 检查数据是否为空
-            if not image_data or "," not in image_data:
-                # 返回一张黑图防止报错
-                print("⚠️ WebROI: Waiting for image data...")
-                empty_img = torch.zeros((1, 512, 512, 3), dtype=torch.float32)
-                return (empty_img,)
-
-            # 2. 解码 Base64
-            base64_data = image_data.split(",")[1]
-            image_bytes = base64.b64decode(base64_data)
-            img = Image.open(BytesIO(image_bytes))
-          
-            # 3. 转换为 ComfyUI 格式 (Tensor)
-            img = img.convert("RGB")
-            img_np = np.array(img).astype(np.float32) / 255.0
-            img_tensor = torch.from_numpy(img_np)[None,]
-          
-            return (img_tensor,)
-          
-        except Exception as e:
-            print(f"❌ WebROI Error: {e}")
-            empty_img = torch.zeros((1, 512, 512, 3), dtype=torch.float32)
-            return (empty_img,)
-
-# 节点映射名称，JS 必须用这个名字 "WebROICapture" 才能找到它
-NODE_CLASS_MAPPINGS = {
-    "WebROICapture": WebROICapture
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "WebROICapture": "🖥️ Web ROI Capture"
-}
-