修改名称

.gitignore

@@ -0,0 +1 @@
+AssetKey.json

CXH_ALY_Seg_Cloth.py → ALY_Seg_Cloth.py

@@ -4,38 +4,21 @@
 from typing import List
 
 from .AlyVision import imagese
-from alibabacloud_imageseg20191230.client import Client
 from alibabacloud_imageseg20191230.models import SegmentClothAdvanceRequest
-from alibabacloud_tea_openapi.models import Config
 from alibabacloud_tea_util.models import RuntimeOptions
 
 
 import os
-import io
-import sys
-import re
-import json
-import time
-import torch
-import psutil
-import random
 import datetime
-import comfy.sd
-import comfy.utils
 import numpy as np
 import folder_paths
-import comfy.samplers
-import latent_preview
 import comfy.model_base
 from pathlib import Path
-import comfy.model_management
 from urllib.request import urlopen
 from collections import defaultdict
 from PIL.PngImagePlugin import PngInfo
 from PIL import Image, ImageDraw, ImageFont
-from typing import Dict, List, Optional, Tuple, Union, Any
 import nodes
-from PIL import Image,ImageOps
 
 from .utils import *
 
@@ -44,7 +27,7 @@
 
 
 
-class CXH_ALY_Seg_Cloth:
+class ALY_Seg_Cloth:
 
     def __init__(self):
         pass
@@ -54,26 +37,30 @@ def INPUT_TYPES(cls):
         return {"required":
                 {
                 "cloth_type":   (["None","tops", "coat","skirt","pants","bag","shoes","hat"],{"default":"None"}  ),     
-                "image_path": ("STRING",{"default": "","multiline": False}), 
+                "image":("IMAGE", {"default": "","multiline": False}),
                 "return_form":   (["whiteBK", "mask"],{"default":"mask"} ),     
                 }
         }
 
     RETURN_TYPES = ("IMAGE","IMAGE")
-    RETURN_NAMES = ("source","class")
+    RETURN_NAMES = ("cloth","part")
     OUTPUT_NODE = True
     FUNCTION = "sample"
     CATEGORY = "CXH"
 
-    def sample(self,cloth_type,image_path,return_form):
-
-        if not os.path.exists(image_path):
-            print("文件不存在:" + image_path)
-            return
-        im = open(image_path, 'rb')
+    def sample(self,cloth_type,image,return_form):
+
+        now = datetime.datetime.now()
+        date_str = now.strftime("%Y-%m-%d")
+        folder_path = os.path.join(custom_nodes_path,"Comfyui_ALY","cache",f"{date_str}.jpg")
 
+        # 零时缓存转换成阿里io.buff
+        save_tensor_image(image,folder_path)
+
+        imp1 = open(folder_path, 'rb')
+
         segment_cloth_request = SegmentClothAdvanceRequest()
-        segment_cloth_request.image_urlobject =im
+        segment_cloth_request.image_urlobject =imp1
         #设置子类
         if cloth_type != "None":
             segment_cloth_request.cloth_class = [cloth_type]

ALY_Seg_Obj.py

@@ -0,0 +1,77 @@
+
+MAX_RESOLUTION=8192
+
+from typing import List
+
+from .AlyVision import imagese
+from alibabacloud_imageseg20191230.models import SegmentCommodityRequest
+from alibabacloud_tea_util.models import RuntimeOptions
+
+import os
+import datetime
+import numpy as np
+import folder_paths
+import comfy.model_base
+from pathlib import Path
+from urllib.request import urlopen
+from collections import defaultdict
+from PIL.PngImagePlugin import PngInfo
+from PIL import Image, ImageDraw, ImageFont
+import nodes
+
+from .utils import *
+
+comfy_path = os.path.dirname(folder_paths.__file__)
+custom_nodes_path = os.path.join(comfy_path, "custom_nodes")
+
+
+
+class ALY_Seg_Obj:
+
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {"required":
+                {   
+                    "image":("IMAGE", {"default": "","multiline": False}),   
+                }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("obj",)
+    OUTPUT_NODE = True
+    FUNCTION = "sample"
+    CATEGORY = "CXH"
+
+    def sample(self,image):
+
+        now = datetime.datetime.now()
+        date_str = now.strftime("%Y-%m-%d")
+        folder_path = os.path.join(custom_nodes_path,"Comfyui_ALY","cache",f"{date_str}.jpg")
+
+        # 零时缓存转换成阿里io.buff
+        save_tensor_image(image,folder_path)
+
+        imp1 = open(folder_path, 'rb')
+
+        segment_commodity_request = SegmentCommodityRequest()
+        segment_commodity_request.image_urlobject =imp1
+
+        runtime = RuntimeOptions()
+        try:
+            # 初始化Client
+            client = imagese.create_client_json()
+            response = client.segment_commodity_with_options_async(segment_commodity_request, runtime)
+            print(response)
+            image_url = response.body.data.image_url
+            print(image_url)
+        except Exception as error:
+            # 获取整体报错信息
+            print(error)
+            # 获取单个字段
+            print(error.code)
+
+        source_img = img_from_url(image_url)
+        return (source_img)

AlyVision.py

@@ -11,7 +11,7 @@
 
 comfy_path = os.path.dirname(folder_paths.__file__)
 custom_nodes_path = os.path.join(comfy_path, "custom_nodes")
-mine_path =  os.path.join(custom_nodes_path, "Comfyui-Mine")
+mine_path =  os.path.join(custom_nodes_path, "Comfyui_ALY")
 key_json = os.path.join(mine_path, "AssetKey.json")
 
 class AlyVision_imageseg:

README.md

@@ -4,7 +4,7 @@
 
 1.CXH_GPT 节点 安装参考：https://www.bilibili.com/video/BV1A94y1A7Mr/
 
-报错：ModuleNotFoundError: No module named 'gptcpp_node' 注意需要看视频结尾其实是需要comfyui_nodes节点，如果不需要GPT节点可以删除CXH_GPT.py，也到__init__.py把CXH_GPT删除
+报错：ModuleNotFoundError: No module named 'gptcpp_node' 注意需要看视频结尾其实是需要 comfyui_nodes 节点，如果不需要 GPT 节点可以删除 CXH_GPT.py，也到**init**.py 把 CXH_GPT 删除
 
 2.CXH_IMAGE 节点 接受一个图片路径输出图片
 
@@ -13,11 +13,11 @@
 获取 key 填写到 AssetKey.json
 
 (2).需要安装依赖：requirements.txt
-python_embeded\python.exe pip  install -r requirements.txt
+python_embeded\python.exe pip install -r requirements.txt
 
 如果阿里的库安装不上可以到群里获取库直接解压。
 
-链接：https://pan.baidu.com/s/1Wt7fLMktnlwuDCrGeV7DqQ 
+链接：https://pan.baidu.com/s/1Wt7fLMktnlwuDCrGeV7DqQ
 提取码：9c0f
 
 ![2da457a1d6d40ca81435c71f7f9a13f](https://github.com/StartHua/Comfyui-Mine/assets/22284244/39173f9d-629c-4766-a852-efb358c45d48)

__init__.py

@@ -1,16 +1,16 @@
 # from .mine_nodes import *
-from .CXH_ALY_Seg_Cloth import *
-from .CXH_IMAGE import *
+from .ALY_Seg_Cloth import *
+from .ALY_Seg_Obj import * 
 
 # A dictionary that contains all nodes you want to export with their names
 # NOTE: names should be globally unique
 NODE_CLASS_MAPPINGS = {
-    "CXH_ALY_Seg_Cloth":CXH_ALY_Seg_Cloth,
-    "CXH_IMAGE":CXH_IMAGE
+    "ALY_Seg_Cloth":ALY_Seg_Cloth,
+    "ALY_Seg_Obj":ALY_Seg_Obj
 }
 
 # A dictionary that contains the friendly/humanly readable titles for the nodes
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "CXH_ALY_Seg_Cloth":"CXH_ALY_Seg_Cloth",
-    "CXH_IMAGE":"CXH_IMAGE"
+    "ALY_Seg_Cloth":"ALY_Seg_Cloth",
+    "ALY_Seg_Obj":ALY_Seg_Obj
 }

utils.py

@@ -1,8 +1,43 @@
 import torch
 import numpy as np
 import io
-from PIL import Image,ImageOps
+from PIL import Image,ImageOps, ImageFilter
 from urllib.request import urlopen
+import datetime
+import os
+import cv2
+import requests
+from io import BytesIO
+
+#comfyui自己的图像就是tensor
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# Convert PIL to Tensor
+def pil2tensor(image):
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+
+# PIL to Mask
+def pil2mask(image):
+    image_np = np.array(image.convert("L")).astype(np.float32) / 255.0
+    mask = torch.from_numpy(image_np)
+    return 1.0 - mask
+
+# 保存tensor图片
+def save_tensor_image(img,path):
+    pil_image = tensor2pil(img)
+    pil_image.save(path)
+
+# Flutter ImageFilter 所使用的模糊算法高斯模糊
+def gaussian_region(image, radius=5.0):
+            image = ImageOps.invert(image.convert("L"))
+            image = image.filter(ImageFilter.GaussianBlur(radius=int(radius)))
+            return image.convert("RGB")
+
+# 网络下载图片
+def download_image(url):
+    response = requests.get(url)
+    return Image.open(BytesIO(response.content)).convert("RGB")
 
 def img_from_path(path):
     img = Image.open(path)
@@ -14,4 +49,43 @@ def img_from_path(path):
 
 def img_from_url(url):
     img = io.BytesIO(urlopen(url).read())
-    return img_from_path(img)
+    return img_from_path(img)
+
+def save_images(img_list, folder):
+    if not os.path.exists(folder):
+        os.makedirs(folder)
+    now = datetime.datetime.now()
+    date_str = now.strftime("%Y-%m-%d")
+    folder_path = os.path.join(folder, date_str)
+    if not os.path.exists(folder_path):
+        os.makedirs(folder_path)
+    time_str = now.strftime("%H_%M_%S")
+    for idx, img in enumerate(img_list):
+        image_number = idx + 1
+        filename = f"{time_str}_{image_number}.jpg"
+        save_path = os.path.join(folder_path, filename)
+        cv2.imwrite(save_path, img[..., ::-1])
+
+
+def check_channels(image):
+    channels = image.shape[2] if len(image.shape) == 3 else 1
+    if channels == 1:
+        image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+    elif channels > 3:
+        image = image[:, :, :3]
+    return image
+
+
+def resize_image(img, max_length=768):
+    height, width = img.shape[:2]
+    max_dimension = max(height, width)
+
+    if max_dimension > max_length:
+        scale_factor = max_length / max_dimension
+        new_width = int(round(width * scale_factor))
+        new_height = int(round(height * scale_factor))
+        new_size = (new_width, new_height)
+        img = cv2.resize(img, new_size)
+    height, width = img.shape[:2]
+    img = cv2.resize(img, (width-(width % 64), height-(height % 64)))
+    return img