save code

API.md

@@ -0,0 +1,108 @@
+# change_app.py API 文档
+
+## 1. GET /
+
+返回主页静态文件 `index.html`。
+
+---
+
+## 2. POST /change_cloth
+
+**推荐入口**，带 Redis 队列排队，避免并发冲突。
+
+### 请求参数（JSON）
+
+| 参数 | 类型 | 必选 | 说明 |
+|------|------|------|------|
+| human_url | string | 是 | 人物图片 URL |
+| cloth_url | string | 是 | 服装图片 URL |
+| output_format | string | 是 | 输出格式，包含 `"base64"` 则返回 base64，否则返回 URL |
+| no2 | bool | 否 | true=跳过第一步（脱衣/生成写真），直接换衣；默认 false |
+| tuodi | bool | 否 | true=使用拖地款工作流；默认 false |
+| kuzi | bool | 否 | 是否同时换裤子（配合 kuzi_url）；默认 false |
+| cloth_len | string | 否 | 手动指定服装长度（如"膝盖""拖地"等），不传则 AI 自动判断 |
+| suit | bool | 否 | true=使用 Gemini 模型换装（套装模式）；默认 false |
+
+### 响应
+
+```json
+// 成功（URL 模式）
+{
+  "ret": 0,
+  "state": 0,
+  "msg": "success",
+  "url": "https://xiangsilian.oss-cn-beijing.aliyuncs.com/xxx.jpg",
+  "second_url": "换衣前中间步骤图 URL",
+  "first_url": "第一步（脱衣/写真）图 URL",
+  "is_girl": true
+}
+
+// 成功（base64 模式）
+{
+  "ret": 0,
+  "state": 0,
+  "msg": "success",
+  "data": "data:image/jpeg;base64,...",
+  "second_step_data": "...",
+  "first_step_data": "...",
+  "is_girl": true
+}
+
+// 失败
+{ "ret": -1, "state": -1, "msg": "错误信息" }
+```
+
+---
+
+## 3. POST /change_cloth_base64
+
+与 `/change_cloth` 功能相同，图片以 Base64 格式传入。
+
+### 请求参数（JSON）
+
+| 参数 | 类型 | 必选 | 说明 |
+|------|------|------|------|
+| human_img | string | 是 | 人物图片 base64（带 data: 头，如 `data:image/jpeg;base64,...`） |
+| cloth_img | string | 是 | 服装图片 base64 |
+| output_format | string | 是 | 同上 |
+| kuzi_img | string | 否 | 裤子图片 base64 |
+| no2 | bool | 否 | 同上 |
+| tuodi | bool | 否 | 同上 |
+| suit | bool | 否 | 同上 |
+| cloth_len | string | 否 | 同上 |
+
+### 响应
+
+同 `/change_cloth`。
+
+---
+
+## 4. POST /do_change_cloth
+
+**直接调用**，无队列保护，通常由内部或 `/change_cloth_base64` 调用，不建议外部直接使用。
+
+### 请求参数（JSON）
+
+| 参数 | 类型 | 必选 | 说明 |
+|------|------|------|------|
+| human_url | string | 是 | 人物图片 URL |
+| cloth_url | string | 是 | 服装图片 URL |
+| output_format | string | 是 | 同上 |
+| no2 | bool | 否 | 同上 |
+| tuodi | bool | 否 | 同上 |
+| kuzi_url | string | 否 | 裤子图片 URL |
+| cloth_len | string | 否 | 同上 |
+| suit | bool | 否 | 同上 |
+
+### 响应
+
+同 `/change_cloth`。
+
+---
+
+## 备注
+
+- `cloth_len` 可选值：`胸、腰、跨、大腿、膝盖、小腿、脚踝、拖地、裤子、难以辨认`
+- 若服装图片中检测到人物，`cloth_len` 自动设为 `拖地`
+- 结果图片同时上传至阿里云 OSS（bucket: `xiangsilian`，region: 北京）
+- 服务默认监听端口由 `config.py` 中的 `base64_test_port` 决定

basic_api_example.py

@@ -1,42 +1,41 @@
-import json
+# -*- coding=utf-8
-from urllib import request
+from qcloud_cos import CosConfig
+from qcloud_cos import CosS3Client
+import sys
+import os
+import logging
 
-#This is the ComfyUI api prompt format.
+# 正常情况日志级别使用 INFO，需要定位时可以修改为 DEBUG，此时 SDK 会打印和服务端的通信信息
+logging.basicConfig(level=logging.INFO, stream=sys.stdout)
 
-#If you want it for a specific workflow you can "enable dev mode options"
+# 1. 设置用户属性, 包括 secret_id, secret_key, region等。Appid 已在 CosConfig 中移除，请在参数 Bucket 中带上 Appid。Bucket 由 BucketName-Appid 组成
-#in the settings of the UI (gear beside the "Queue Size: ") this will enable
+secret_id = 'AKIDDIBrNhoiOtBF5rcEdoBRUKwU2Rj2OgxA'     # 用户的 SecretId，建议使用子账号密钥，授权遵循最小权限指引，降低使用风险。子账号密钥获取可参见 https://cloud.tencent.com/document/product/598/37140
-#a button on the UI to save workflows in api format.
+secret_key = '5wkKhttgYQD2iEZgaInEVYVPCo2BJK9l'   # 用户的 SecretKey，建议使用子账号密钥，授权遵循最小权限指引，降低使用风险。子账号密钥获取可参见 https://cloud.tencent.com/document/product/598/37140
-
+region = 'ap-beijing' #'ap-guangzhou'      # 替换为用户的 region，已创建桶归属的 region 可以在控制台查看，https://console.cloud.tencent.com/cos5/bucket
-#keep in mind ComfyUI is pre alpha software so this format will change a bit.
+                           # COS 支持的所有 region 列表参见 https://cloud.tencent.com/document/product/436/6224
-
+token = None               # 如果使用永久密钥不需要填入 token，如果使用临时密钥需要填入，临时密钥生成和使用指引参见 https://cloud.tencent.com/document/product/436/14048
-#this is the one for the default workflow
+scheme = 'https'           # 指定使用 http/https 协议来访问 COS，默认为 https，可不填
-
-def queue_prompt(prompt):
-    p = {"prompt": prompt}
-
-    # If the workflow contains API nodes, you can add a Comfy API key to the `extra_data`` field of the payload.
-    # p["extra_data"] = {
-    #     "api_key_comfy_org": "comfyui-87d01e28d*******************************************************"  # replace with real key
-    # }
-    # See: https://docs.comfy.org/tutorials/api-nodes/overview
-    # Generate a key here: https://platform.comfy.org/login
-
-    data = json.dumps(p).encode('utf-8')
-    req =  request.Request("http://127.0.0.1:8188/prompt", data=data)
-    request.urlopen(req)
 
 
-with open('/home/szlc/code/ComfyUI/change_cloth/basic_api.json', 'r', encoding='utf-8') as file:
+config = CosConfig(Region=region, SecretId=secret_id, SecretKey=secret_key, Token=token, Scheme=scheme)
-    prompt_text = file.read()
+client = CosS3Client(config)
 
-prompt = json.loads(prompt_text)
+#### 文件流简单上传（不支持超过5G的文件，推荐使用下方高级上传接口）
-#set the text prompt for our positive CLIPTextEncode
+# 强烈建议您以二进制模式(binary mode)打开文件,否则可能会导致错误
-prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
+with open('out_image.png', 'rb') as fp:
-
+    response = client.put_object(
-#set the seed for our KSampler node
+        Bucket='b-1304254135',
-prompt["3"]["inputs"]["seed"] = 5
+        Body=fp,
-
+        Key='out_image.png',
-
+        StorageClass='STANDARD',
-queue_prompt(prompt)
+        EnableMD5=False
+    )
+print(response['ETag'])
 
 
+####  获取文件到本地
+response = client.get_object(
+    Bucket='b-1304254135',
+    Key='out_image.png'
+)
+response['Body'].get_stream_to_file('cos_girl.png')

change_app.py

@@ -1,7 +1,7 @@
 import os
 import uuid
 import requests
-from flask import Flask, request, jsonify
+from flask import Flask, request, jsonify, Response
 from urllib.parse import urlparse
 import json
 import base64
@@ -14,7 +14,11 @@ import oss2
 import redis
 # from check_img_body import is_thigh_visible
 import logging
-from config import QUEUE_NAME, DEFAULT_TIMEOUT, KEY_QUEUE_LOCK_NAME, acquire_lock
+from config import *
+import websockets
+import asyncio
+import traceback
+import re
 
 
 APP_ROOT = os.path.dirname(os.path.abspath(__file__))
@@ -28,7 +32,7 @@ logger.setLevel(logging.INFO)  # 设置 logger 的级别
 now = datetime.now()
 
 # 格式化为字符串（例如：2023-10-25 14:30:45）
-date_time_str = now.strftime("%Y-%m-%d_%H:%M:%S")
+date_time_str = now.strftime("%Y-%m-%d_%H-%M-%S")
 
 # 创建文件 handler
 file_handler = logging.FileHandler(f'/var/log/fuyan/change_app_{date_time_str}.log')
@@ -58,11 +62,19 @@ redis_pool = redis.ConnectionPool(
     max_connections=2000  # 根据实际情况调整
 )
 
+from datetime import datetime
+def log_message(msg):
+    """简单的日志输出函数"""
+    print(f"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] {msg}")
+    logger.info(msg)
+
 def get_redis_conn():
     """获取 Redis 连接"""
     return redis.Redis(connection_pool=redis_pool)
 
-app = Flask(__name__)
+app = Flask(__name__, static_folder='static', static_url_path='/static')
+from flask_cors import CORS
+CORS(app)
 
 client = Ark(
             # 此为默认路径，您可根据业务所在地域进行配置
@@ -97,6 +109,32 @@ def GetPicDesc(img_url):
         print(text)
         return text
 
+
+def GetPicHumanFace(img_url):
+        response = client.chat.completions.create(
+            # 指定您创建的方舟推理接入点 ID，此处已帮您修改为您的推理接入点 ID
+            model="doubao-1.5-vision-pro-250328",
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": img_url
+                            },
+                        },
+                        {"type": "text", "text": "图片是一件有服装的照片，帮忙分析一下，返回为json格式, 字段名是'face_state'， 图片是否有人脸或者人，有人或者人穿着衣服就返回'有人' 没有就返回'没人'"},
+                    ],
+                }
+            ],
+            
+        )
+
+        text = response.choices[0].message.content
+        print(text)
+        return text
+
 def GetHumanDesDesc(img_url):
         response = client.chat.completions.create(
             # 指定您创建的方舟推理接入点 ID，此处已帮您修改为您的推理接入点 ID
@@ -123,12 +161,12 @@ def GetHumanDesDesc(img_url):
         return text
 
 def takeoff_cloth_first(human_name, is_girl):
-    print('换泳装')
+    print(f'换泳装 {change_with_add_cloth}')
     queue = requests.get("http://localhost:8188/queue").json()
     if queue["queue_running"] or queue["queue_pending"]:
         return None, "cur gpu is busy"
 
-    with open('/home/szlc/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
+    with open(f'{APP_ROOT}/{change_with_add_cloth}', 'r', encoding='utf-8') as file:
         prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
@@ -140,9 +178,10 @@ def takeoff_cloth_first(human_name, is_girl):
 
     #input cloth img
     if is_girl:
-        prompt["22"]["inputs"]["image"] = 'girl_cloth.jpg'
+        prompt["22"]["inputs"]["image"] = 'girl_cloth_new_new.png'
     else:
-        prompt["22"]["inputs"]["image"] = 'man_cloth.jpg'
+        prompt["22"]["inputs"]["image"] = 'man_cloth_grey.jpg'
+        # prompt["22"]["inputs"]["image"] = 'man_cloth.jpg'
 
     #input human img
     prompt["61"]["inputs"]["image"] = human_name
@@ -181,12 +220,12 @@ def takeoff_cloth_first(human_name, is_girl):
     return None
 
 def generate_from_face(human_name, sex_girl):
-    print('生成写真')
+    print(f'生成写真 {xiezhen_name}')
     queue = requests.get("http://localhost:8188/queue").json()
     if queue["queue_running"] or queue["queue_pending"]:
         return None, "cur gpu is busy"
 
-    with open('/home/szlc/code/ComfyUI/change_cloth/xiezhen_girl.json', 'r', encoding='utf-8') as file:
+    with open(f'{APP_ROOT}/{xiezhen_name}', 'r', encoding='utf-8') as file:
         prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
@@ -194,10 +233,16 @@ def generate_from_face(human_name, sex_girl):
 
     prompt["93"]["inputs"]["image"] = human_name
 
+    # if sex_girl:
+    #     prompt["6"]["inputs"]["text"] = "asian girl,knee-length shot ,model pose,hands are at the sides of the body,smile,wearing black tube top and micro skirt,simple ,white background,32k,high detail,and face is illuminated by soft side light and natural light. The sunlight spills over the white wall behind."
+    # else:
+    #     prompt["6"]["inputs"]["text"] = "asian man,tall,knee-length shot,model pose,hands are at the sides of the body,smile,wearing black short pants,simple white background,The sunlight spills over the white wall behind,32k."
+
     if sex_girl:
-        prompt["6"]["inputs"]["text"] = "asian girl,full body shot(1.9),complete figure,front-facing,model pose,hands are at the sides of the body,smile,wearing black tube top and micro skirt,simple ,white background,32k,high detail,and face is illuminated by soft side light and natural light. The sunlight spills over the white wall behind."
+        prompt["6"]["inputs"]["text"] = "asian girl,knee-length shot,model pose,hands are at the sides of the body,smile,wearing black tube top and micro skirt,solid very dark gray background,32k,high detail,and face is illuminated by soft side light and natural light."
     else:
-        prompt["6"]["inputs"]["text"] = "asian man,full body shot(1.9),complete figure,front-facing,model pose,hands are at the sides of the body,smile,wearing black tight  shortst,simple white background,32k,high detail,and face is illuminated by soft side light and natural light. The sunlight spills over the white wall behind."
+        prompt["6"]["inputs"]["text"] = "asian man,tall,knee-length shot,model pose,hands are at the sides of the body,smile,shirtless,wearing black short pants,very dark gray background,solid dark gray background,32k,"
+
 
     #out put name
     out_img_name = str(uuid.uuid4())[:8]
@@ -232,7 +277,7 @@ def generate_from_face(human_name, sex_girl):
                         return out_img_file_name
     return None
 
-def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2):
+def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2, tuodi, cloth_len):
     human_json_str = GetHumanDesDesc(human_url)
     print(f"human_json_str {human_json_str}")
     human_json_data = json.loads(human_json_str)
@@ -243,29 +288,44 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
 
     sgwzd = human_json_data['身高完整度']
 
-    json_str = GetPicDesc(cloth_url)
-    json_data = json.loads(json_str)
-    cloth_len = json_data['服装长度']
     cloth_short = True
-    if '长袖' in json_data['衣袖']:
+    if cloth_len == None:
-        cloth_short = False
+        json_str = GetPicDesc(cloth_url)
-    if cloth_len == '难以辨认':
+        print(f"GetPicDesc:{json_str}")
-        return None, None, sex_girl, "get image type error"
+        json_data = json.loads(json_str)
+        cloth_len = json_data['服装长度']
+        if '长袖' in json_data['衣袖']:
+            cloth_short = False
+    else:
+        print(f'change 函数里面获取的 cloth_len')
+    
+    
+    cloth_json_str = GetPicHumanFace(cloth_url)
+    print(f"cloth_json_str:{cloth_json_str}")
+    cloth_json_data = json.loads(cloth_json_str)
+    if cloth_json_data['face_state'] == '有人':
+        cloth_len = '拖地'
+
+    print(f"tuodi:{tuodi}")
+
+
+    if tuodi == True or tuodi == "true":
+        cloth_len = '拖地'
 
     if no2 == True:
         print(f'不用第二部 no2{no2}')
     else:
         print(f'要第二部 no2{no2} 先搞第一步')
-        # thigh_visible = is_thigh_visible(f"/home/szlc/code/ComfyUI/input/{human_name}")
+        if sgwzd >= 0.70:
-        if sgwzd >= 0.5:
             #脱衣服
             takeoff_file_name = takeoff_cloth_first(human_name, sex_girl)
+            print(f"takeoff_file_name:{takeoff_file_name} human_name:{human_name} sex_girl:{sex_girl}")
             if takeoff_file_name == None:
                 return None, None, sex_girl, f"takeoff_cloth_first error {human_name}"
             else:
                 human_name = takeoff_file_name
-                takeoff_file_path_name = os.path.join('/home/szlc/code/ComfyUI/output', takeoff_file_name)
+                takeoff_file_path_name = os.path.join(f'{APP_ROOT}/../output', takeoff_file_name)
-                takeoff_file_path_name_input = os.path.join('/home/szlc/code/ComfyUI/input', takeoff_file_name)
+                takeoff_file_path_name_input = os.path.join(f'{APP_ROOT}/../input', takeoff_file_name)
                 shutil.copy(takeoff_file_path_name, takeoff_file_path_name_input)
         else:
             #生成写真
@@ -274,17 +334,22 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
                 return None, None, sex_girl, f"xiezhen error {human_name}"
             else:
                 human_name = generate_name
-                generate_name_file_path_name = os.path.join('/home/szlc/code/ComfyUI/output', generate_name)
+                generate_name_file_path_name = os.path.join(f'{APP_ROOT}/../output', generate_name)
-                generate_name_file_path_name_input = os.path.join('/home/szlc/code/ComfyUI/input', generate_name)
+                generate_name_file_path_name_input = os.path.join(f'{APP_ROOT}/../input', generate_name)
                 shutil.copy(generate_name_file_path_name, generate_name_file_path_name_input)
 
     queue = requests.get("http://localhost:8188/queue").json()
     if queue["queue_running"] or queue["queue_pending"]:
         return None, None, sex_girl, "cur gpu is busy, Shou not happen"
 
-    print('开始换衣服')
+    if tuodi:
-    with open('/home/szlc/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
+        print(f'开始换衣服 {change_tuodi_input} cloth_len:{cloth_len} cloth_short:{cloth_short}')
-        prompt_text = file.read()
+        with open(f'{APP_ROOT}/{change_tuodi_input}', 'r', encoding='utf-8') as file:
+            prompt_text = file.read()
+    else:
+        print(f'开始换衣服 {change_only_name} cloth_len:{cloth_len} cloth_short:{cloth_short}')
+        with open(f'{APP_ROOT}/{change_only_name}', 'r', encoding='utf-8') as file:
+            prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
 
@@ -310,9 +375,8 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
     response = requests.post("http://localhost:8188/prompt", data=data)
     prompt_id = response.json()["prompt_id"]
 
-
-    # 2. 轮询队列，直到任务完成
     while True:
+        # response = requests.post("http://localhost:8188/interrupt")
         queue = requests.get("http://localhost:8188/queue").json()
         # print(queue)
         if not queue["queue_running"] and not queue["queue_pending"]:
@@ -332,6 +396,61 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
                         return out_img_file_name, human_name, sex_girl,"success"
     return None, human_name, sex_girl, "can not find output image"
 
+
+def change_kuzi(human_name, kuzi_name):
+    queue = requests.get("http://localhost:8188/queue").json()
+    if queue["queue_running"] or queue["queue_pending"]:
+        return None, "cur gpu is busy, Shou not happen"
+
+    print(f'开始换裤子 {change_only_name}')
+    with open(f'{APP_ROOT}/{change_only_name}', 'r', encoding='utf-8') as file:
+        prompt_text = file.read()
+        
+    prompt = json.loads(prompt_text)
+
+    prompt["96"]["inputs"]["cloth_len"] = "裤子"
+    prompt["96"]["inputs"]["cloth_short"] = False
+
+    # prompt["99"]["inputs"]["width"] = int((c_width/c_height) * 1024)
+
+    #input cloth img
+    prompt["22"]["inputs"]["image"] = kuzi_name
+
+    #input human img
+    prompt["61"]["inputs"]["image"] = human_name
+
+    #out put name
+    out_img_name = str(uuid.uuid4())[:8]
+    prompt["102"]["inputs"]["filename_prefix"] = out_img_name
+
+    p = {"prompt": prompt}
+
+    data = json.dumps(p).encode('utf-8')
+
+    response = requests.post("http://localhost:8188/prompt", data=data)
+    prompt_id = response.json()["prompt_id"]
+
+    while True:
+        # response = requests.post("http://localhost:8188/interrupt")
+        queue = requests.get("http://localhost:8188/queue").json()
+        # print(queue)
+        if not queue["queue_running"] and not queue["queue_pending"]:
+            break  # 队列为空，任务已完成
+        time.sleep(0.5)  # 避免频繁请求
+
+    # 3. 从历史记录中获取结果
+    history = requests.get("http://localhost:8188/history").json()
+    # print("History:", history)
+    outputs = history[prompt_id]["outputs"]
+    for out in outputs:
+        if 'images' in outputs[out]:
+            for out_img in outputs[out]['images']:
+                if 'filename' in out_img:
+                    out_img_file_name = out_img['filename']
+                    if  out_img_name in out_img_file_name:
+                        return out_img_file_name,"success"
+    return None, "can not find output image"
+
 def save_base64_image(base64_str, prefix):
     """
     将base64字符串保存为图片文件
@@ -360,13 +479,13 @@ def save_base64_image(base64_str, prefix):
         timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
         unique_id = str(uuid.uuid4())[:8]
         filename = f"{prefix}_{timestamp}_{unique_id}{file_ext}"
-        filepath = os.path.join('/home/szlc/code/ComfyUI/change_cloth/static/imgs', filename)
+        filepath = os.path.join(f'{APP_ROOT}/static/imgs', filename)
         
         # 解码并保存图片
         with open(filepath, 'wb') as f:
             f.write(base64.b64decode(data))
 
-        input_filepath = os.path.join('/home/szlc/code/ComfyUI/input', filename)
+        input_filepath = os.path.join(f'{APP_ROOT}/../input', filename)
         # 解码并保存图片
         with open(input_filepath, 'wb') as f:
             f.write(base64.b64decode(data))
@@ -386,32 +505,32 @@ def get_image_dimensions(image_path):
         print(f"Error: {e}")
         return None
     
-def image_to_base64(file_path, mime_type=None):
+def image_to_base64(file_path, with_head = True):
-    if mime_type is None:
+    extension = file_path.split('.')[-1].lower()
-        extension = file_path.split('.')[-1].lower()
+    mime_types = {
-        mime_types = {
+        'jpg': 'image/jpeg',
-            'jpg': 'image/jpeg',
+        'jpeg': 'image/jpeg',
-            'jpeg': 'image/jpeg',
+        'png': 'image/png',
-            'png': 'image/png',
+        'gif': 'image/gif',
-            'gif': 'image/gif',
+        'webp': 'image/webp',
-            'webp': 'image/webp',
+        'bmp': 'image/bmp'
-            'bmp': 'image/bmp'
+    }
-        }
+    mime_type = mime_types.get(extension, 'application/octet-stream')
-        mime_type = mime_types.get(extension, 'application/octet-stream')
 
-    # 读取文件内容并编码为Base64
     with open(file_path, 'rb') as image_file:
         encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
     
-    # 组合成Data URI格式
+    if with_head:
-    return f"data:{mime_type};base64,{encoded_string}"
+        return f"data:{mime_type};base64,{encoded_string}"
+    else:
+        return encoded_string
 
 def upload_to_oss(image_path, object_name=None):
     # 配置信息（替换为你的实际信息）
-    access_key_id = 'LTAI5tB9t2RH6f1drSLvVLLZ'
+    access_key_id = 'LTAI5tGp1sLzedqxihcNC1eb'
-    access_key_secret = '91uzPI1RAFHN7n3Y6TJDGFP8w0dG1R'
+    access_key_secret = 'IFZE1b8YYreCP6zfA6GaZ9uBT678qO'
     endpoint = 'oss-cn-beijing.aliyuncs.com'  # 替换为你的Endpoint
-    bucket_name = 'llyz'
+    bucket_name = 'xiangsilian'
     
     # 创建Bucket实例
     auth = oss2.Auth(access_key_id, access_key_secret)
@@ -437,11 +556,159 @@ def upload_to_oss(image_path, object_name=None):
         print(f"上传失败: {str(e)}")
         return None
 
+def get_image_from_json(json_str):
+    try:
+        data = json.loads(json_str)
+        parts = data["candidates"][0]["content"]["parts"]
+        base64_data = None
+        for part in parts:
+            if "inlineData" in part and "data" in part["inlineData"]:
+                base64_data = part["inlineData"]["data"]
+                break
         
-def process_change_cloth(human_filename, cloth_filename, output_format, img_url, human_url, no2):
+        if base64_data is None:
-    w,h = get_image_dimensions(f'/home/szlc/code/ComfyUI/input/{human_filename}') 
+            print("未找到包含图片数据的部分")
+            return None
         
-    out_put_name, out_human_name, is_girl,  msg = change(human_filename, cloth_filename, w, h, img_url, human_url, no2)
+        base64_data = re.sub(r'\s+', '', base64_data)
+        image_data = base64.b64decode(base64_data)
+        return image_data
+    except Exception as e:
+        print(f"保存图片时发生错误: {e}")
+        return None
+    
+import http.client
+from io import BytesIO
+def process_change_banana(human_filename, cloth_filename, output_format):
+    human_filepath = os.path.join(f'{APP_ROOT}/../input', human_filename)
+    suit_filepath = os.path.join(f'{APP_ROOT}/../input', cloth_filename)
+
+    conn = http.client.HTTPSConnection("ai.juguang.chat")
+    payload = json.dumps({
+    "contents": [
+        {
+        "parts": [
+            {
+            "text": "这是一张有人的图片"
+            },
+            {
+            "inline_data": {
+                "mime_type": "image/jpeg",
+                "data": image_to_base64(human_filepath, False)
+            }
+            },
+            {
+            "text": "这是另外一张有衣服，裤子或者裙子，鞋子，手表，耳环和其他各种可以穿戴在身上物品的图片"
+            },
+            {
+            "inline_data": {
+                "mime_type": "image/jpeg",
+                "data": image_to_base64(suit_filepath, False)
+            }
+            },
+            {
+            "text": "给第一张图片的人物，穿戴上第二张图片的衣服和配饰"
+            }
+        ]
+        }
+    ]
+    })
+    headers = {
+    'Content-Type': 'application/json',
+    'Authorization': 'Bearer sk-zLFhpbBQKWV4qohV4vD0AFR6Gaa7JwL0Q8zphh1CYFl2EqDM'
+    }
+    conn.request("POST", "/v1beta/models/gemini-2.5-flash-image-preview:generateContent", payload, headers)
+    res = conn.getresponse()
+    data = res.read()
+    decode_str = data.decode("utf-8")
+
+    img_data = get_image_from_json(decode_str)
+    image_stream = BytesIO(img_data)
+    image = Image.open(image_stream)
+    jpg_name = f"{uuid.uuid4()}.png"
+    jpg_path_name = f'{APP_ROOT}/static/imgs/{jpg_name}'
+    image.save(jpg_path_name, quality=90)
+    upload_to_oss(jpg_path_name, jpg_name)
+    https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{jpg_name}'
+
+    if img_data:
+        if 'base64' in output_format:
+            return jsonify({
+                "ret":0,
+                "state": 0,
+                "msg":"success",
+                "data":image_to_base64(jpg_path_name)
+            })
+        else:
+            return jsonify({
+                "ret":0,
+                "state": 0,
+                "msg":"success",
+                "url":https_url
+            })
+    else:
+        return jsonify({
+                "ret":-1,
+                "state": -1,
+                "msg":"failure"
+            })
+
+def process_change_cloth(human_filename, cloth_filename, output_format, img_url, human_url, no2, tuodi, kuzi_url, cloth_len, kuzi_img=None):
+    w,h = get_image_dimensions(f'{APP_ROOT}/../input/{human_filename}') 
+
+    if kuzi_url:
+        print(f'换裤子 kuzi_url:{kuzi_url}')
+
+        human_json_str = GetHumanDesDesc(human_url)
+        print(f"human_json_str {human_json_str}")
+        human_json_data = json.loads(human_json_str)
+        sex_type = human_json_data['性别']
+        sex_girl = True
+        if '男' in sex_type:
+            sex_girl = False
+
+        new_data = {
+            "model_image": image_to_base64(f'{APP_ROOT}/../input/{human_filename}', False),
+            "shirt_image": image_to_base64(f'{APP_ROOT}/../input/{cloth_filename}', False),
+            "pants_image": kuzi_img if kuzi_img else image_to_base64(save_image_from_url(kuzi_url), False),
+        }
+        response = requests.post(f'http://117.50.44.174:47698/try-on', json=new_data)
+        result_image_data = response.json().get("result_image", "")
+        if result_image_data:
+            print(f"result_image_data: {result_image_data[:30]}...")  # 打印前30个字符以验证数据格式
+            if 'base64' in output_format:
+                return jsonify({
+                    "ret":0,
+                    "state": 0,
+                    "msg":"success",
+                    "is_girl":sex_girl,
+                    "second_step_data":new_data["model_image"],
+                    "first_step_data":new_data["model_image"],
+                    "data":result_image_data
+                })
+            else:
+                result_image_bytes = base64.b64decode(result_image_data.split(',')[1])
+                result_image_stream = BytesIO(result_image_bytes)
+                image = Image.open(result_image_stream)
+                jpg_name = f"{uuid.uuid4()}.png"
+                jpg_path_name = f'{APP_ROOT}/static/imgs/{jpg_name}'
+                image.save(jpg_path_name, quality=90)
+                upload_to_oss(jpg_path_name, jpg_name)
+                https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{jpg_name}'
+
+                return jsonify({
+                    "ret":0,
+                    "state": 0,
+                    "msg":"success",
+                    "second_url":https_url,
+                    "first_url":https_url,
+                    "is_girl":sex_girl,
+                    "url":https_url
+                })
+                    
+                    
+
+    out_put_name, out_human_name, is_girl, msg = change(human_filename, cloth_filename, w, h, img_url, human_url, no2, tuodi, cloth_len)
     if out_put_name == None:
         print(f'Failed to change cloth {msg}')
         return jsonify({"ret":-1, 'msg': f'Failed to change cloth {msg}'}), 200
@@ -449,30 +716,53 @@ def process_change_cloth(human_filename, cloth_filename, output_format, img_url,
     if no2:
         out_human_https_url = human_url
     else:
-        out_human_image = Image.open(f'/home/szlc/code/ComfyUI/output/{out_human_name}')
+        if os.path.exists(f'{APP_ROOT}/../output/{out_human_name}'):
+            out_human_image = Image.open(f'{APP_ROOT}/../output/{out_human_name}')
+        else:
+            out_human_image = Image.open(f'{APP_ROOT}/../input/{out_human_name}')
         out_human_jpg_name = out_human_name.replace(".png", ".jpg")
-        out_human_jpg_path_name = f'/home/szlc/code/ComfyUI/change_cloth/static/imgs/{out_human_jpg_name}'
+        out_human_jpg_path_name = f'{APP_ROOT}/static/imgs/{out_human_jpg_name}'
-        out_human_image.save(out_human_jpg_path_name, quality=95)
+        out_human_image.save(out_human_jpg_path_name, quality=90)
         upload_to_oss(out_human_jpg_path_name, out_human_jpg_name)  # 第二个参数可选，指定OSS上的路径
-        out_human_https_url = f'https://llyz.oss-cn-beijing.aliyuncs.com/{out_human_jpg_name}'
+        out_human_https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{out_human_jpg_name}'
         print(f"生成的第一步图片 HTTPS URL: {out_human_https_url}")
 
-    
+    image = Image.open(f'{APP_ROOT}/../output/{out_put_name}')
-    image = Image.open(f'/home/szlc/code/ComfyUI/output/{out_put_name}')
     jpg_name = out_put_name.replace(".png", ".jpg")
-    jpg_path_name = f'/home/szlc/code/ComfyUI/change_cloth/static/imgs/{jpg_name}'
+    jpg_path_name = f'{APP_ROOT}/static/imgs/{jpg_name}'
-    image.save(jpg_path_name, quality=95)
+    image.save(jpg_path_name, quality=90)
 
 
     upload_to_oss(jpg_path_name, jpg_name)  # 第二个参数可选，指定OSS上的路径
-    https_url = f'https://llyz.oss-cn-beijing.aliyuncs.com/{jpg_name}'
+    https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{jpg_name}'
     print(f"生成的HTTPS URL: {https_url}")
 
+    out_befor_kuzi_url = https_url
+    if kuzi_url:
+        output_path_name = os.path.join(f'{APP_ROOT}/../output', out_put_name)
+        output_path_name_input = os.path.join(f'{APP_ROOT}/../input', out_put_name)
+        shutil.copy(output_path_name, output_path_name_input)
+
+
+        kuzi_filename = save_image_from_url(kuzi_url)
+        kuzi_out_put_name, msg = change_kuzi(out_put_name, kuzi_filename)
+        image = Image.open(f'{APP_ROOT}/../output/{kuzi_out_put_name}')
+        jpg_name = kuzi_out_put_name.replace(".png", ".jpg")
+        jpg_path_name = f'{APP_ROOT}/static/imgs/{jpg_name}'
+        image.save(jpg_path_name, quality=90)
+
+        upload_to_oss(jpg_path_name, jpg_name)  # 第二个参数可选，指定OSS上的路径
+        https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{jpg_name}'
+        print(f"生成的加上换裤子的 HTTPS URL: {https_url}")
+
+    
+
     if 'base64' in output_format:
         return jsonify({
             "ret":0,
             "state": 0,
             "msg":"success",
+            "second_step_data":image_to_base64(out_befor_kuzi_url),
             "first_step_data":image_to_base64(out_human_jpg_path_name),
             "is_girl":is_girl,
             "data":image_to_base64(jpg_path_name)
@@ -482,6 +772,7 @@ def process_change_cloth(human_filename, cloth_filename, output_format, img_url,
             "ret":0,
             "state": 0,
             "msg":"success",
+            "second_url":out_befor_kuzi_url,
             "first_url":out_human_https_url,
             "is_girl":is_girl,
             "url":https_url
@@ -510,13 +801,13 @@ def save_image_from_url(image_url):
         # 获取原始图片格式
         ext = get_file_extension(image_url)
         filename = f"{uuid.uuid4()}{ext}"
-        filepath = os.path.join('/home/szlc/code/ComfyUI/change_cloth/static/imgs', filename)
+        filepath = os.path.join(f'{APP_ROOT}/static/imgs', filename)
 
         with open(filepath, "wb") as f:
             for chunk in response.iter_content(1024):
                 f.write(chunk)
 
-        input_filepath = os.path.join('/home/szlc/code/ComfyUI/input', filename)
+        input_filepath = os.path.join(f'{APP_ROOT}/../input', filename)
         shutil.copy(filepath, input_filepath)
 
         return filename
@@ -525,11 +816,20 @@ def save_image_from_url(image_url):
         return None
 
 
+@app.route('/')
+def index():
+    """返回主页"""
+    from flask import send_from_directory
+    return send_from_directory('static', 'index.html')
+
 @app.route('/do_change_cloth', methods=['POST'])
 def do_change_cloth():
+    log_message("do_change_cloth called")
     """从 URL 下载图片"""
     data = request.json
 
+    print(f"do_change_cloth input data:{data}") 
+
     human_url = data.get("human_url")
 
     human_filename = save_image_from_url(human_url)
@@ -543,6 +843,10 @@ def do_change_cloth():
     
     output_format = data.get('output_format')
 
+    if 'suit' in data:
+        if data['suit']:
+            return process_change_banana(human_filename, cloth_filename, output_format)
+
     def check_type(var):
         if isinstance(var, bool):
             print(f"{var} 是布尔值no2")
@@ -551,12 +855,29 @@ def do_change_cloth():
         else:
             print(f"既不是字符串也不是布尔值no2，实际类型: {type(var)}")
 
-    no2 = data['no2']
+    no2 = False
-    check_type(no2)
+    if 'no2' in data:
+        no2 = data['no2']
+        check_type(no2)
 
+    tuodi = False
+    if 'tuodi' in data:
+        tuodi = data['tuodi']
+    print(f"tuodi:{tuodi}")
+
+    kuzi_url = None
+    if 'kuzi_url' in data:
+        kuzi_url = data.get("kuzi_url")
+        print(f"要弄裤子 kuzi:{kuzi_url}")
+
+    cloth_len = None
+    if 'cloth_len' in data:
+        cloth_len = data['cloth_len']
     try:
-        return process_change_cloth(human_filename, cloth_filename, output_format, cloth_url, human_url, no2)
+        return process_change_cloth(human_filename, cloth_filename, output_format, cloth_url, human_url, no2, tuodi, kuzi_url, cloth_len, data.get("kuzi_img") )
-    except:
+    except Exception as e:
+        traceback.print_exc()
+        print(f"错误详情：{e}")
         return jsonify({
             "ret":-1,
             "state": -1,
@@ -611,6 +932,7 @@ def queueCall(data):
 
 @app.route('/change_cloth', methods=['POST'])
 def change_cloth():
+    log_message("change_cloth_base64 called")
     """从 URL 下载图片"""
     data = request.json
 
@@ -630,14 +952,25 @@ def change_cloth():
     if not no2:
         data['no2'] = False
 
+    tuodi = data.get('tuodi')
+    if not tuodi:
+        data['tuodi'] = False
+
+    kuzi = data.get('kuzi')
+    if not kuzi:
+        data['kuzi'] = False
+
     print(f"change_cloth input data:{data}")
 
     return queueCall(data)
 
 @app.route('/change_cloth_base64', methods=['POST'])
 def change_cloth_base64():
+    log_message("change_cloth_base64 called")
+
     # 获取参数
     data = request.get_json()
+    print(f"change_cloth_base64 input data:{data}")
     if not data:
         return jsonify({"ret":-1, "state":-1, 'msg': 'No JSON data provided'}), 400
 
@@ -655,7 +988,7 @@ def change_cloth_base64():
         return jsonify({"ret":-1, 'msg': 'Failed to save human image'}), 500
     data['human_img'] = None
     
-    human_url = f"http://112.126.94.241:18888/static/imgs/{human_filename}"
+    human_url = f"http://117.50.44.174:{base64_test_port}/static/imgs/{human_filename}"
 
     # 保存服装图片
     cloth_filename = save_base64_image(cloth_img, 'cloth')
@@ -663,17 +996,51 @@ def change_cloth_base64():
         return jsonify({"ret":-1, 'msg': 'Failed to save cloth image'}), 500
     data['cloth_img'] = None
     
-    cloth_url = f"http://112.126.94.241:18888/static/imgs/{cloth_filename}"
+    cloth_url = f"http://117.50.44.174:{base64_test_port}/static/imgs/{cloth_filename}"
 
     data["human_url"] = human_url
     data["cloth_url"] = cloth_url
 
+    kuzi_img = data.get('kuzi_img')
+    if kuzi_img:
+        kuzi_filename = save_base64_image(kuzi_img, 'kuzi')
+        # data['kuzi_img'] = None
+        kuzi_url = f"http://117.50.44.174:{base64_test_port}/static/imgs/{kuzi_filename}"
+        data['kuzi_url'] = kuzi_url
+        
     no2 = data.get('no2')
     if not no2:
         data['no2'] = False
 
-    return queueCall(data)
+    tuodi = data.get('tuodi')
+    if not tuodi:
+        data['tuodi'] = False
+
+
+    if not data.get('suit'):
+        data['suit'] = False
+
+    if data.get('cloth_len'):
+        print(f'客户端传入了衣服长度: {data['cloth_len']}')
+    else:
+        print('客户端传入了衣服长度，需要ai 判断')
+
+
+    # 在内部调用第二个HTTP请求
+    try:
+        # 调用第二个API（可以是外部服务或自己的另一个端点）
+        response = requests.post(f'http://117.50.44.174:{base64_test_port}/do_change_cloth', json=data)
+        
+        return Response(
+            response=response.content,
+            status=response.status_code,
+            headers=dict(response.headers)
+    )
+    except requests.exceptions.RequestException as e:
+        data['second_api_error'] = str(e)
+    
+    return jsonify("error"), 500
 
 
 if __name__ == '__main__':
-    app.run(host="0.0.0.0", port=8888, debug=True)
+    app.run(host="0.0.0.0", port=base64_test_port, debug=False)

change_new.json

@@ -1,7 +1,7 @@
 {
   "3": {
     "inputs": {
-      "seed": 154943414582783,
+      "seed": 940724765309123,
       "steps": 20,
       "cfg": 1,
       "sampler_name": "euler",
@@ -73,7 +73,7 @@
   },
   "10": {
     "inputs": {
-      "strength": 1,
+      "strength": 1.0000000000000002,
       "strength_type": "multiply",
       "conditioning": [
         "11",
@@ -196,7 +196,7 @@
   },
   "22": {
     "inputs": {
-      "image": "cloth_20250715_232138_50414b8f.jpg"
+      "image": "0b0a7d75-3241-49b5-be98-5dc87838322c.jpg"
     },
     "class_type": "LoadImage",
     "_meta": {
@@ -254,7 +254,7 @@
   "27": {
     "inputs": {
       "context_expand_pixels": 20,
-      "context_expand_factor": 1,
+      "context_expand_factor": 1.0000000000000002,
       "fill_mask_holes": true,
       "blur_mask_pixels": 10,
       "invert_mask": false,
@@ -263,7 +263,7 @@
       "mode": "ranged size",
       "force_width": 1024,
       "force_height": 1024,
-      "rescale_factor": 1,
+      "rescale_factor": 1.0000000000000002,
       "min_width": 512,
       "min_height": 512,
       "max_width": 1800,
@@ -467,9 +467,9 @@
   "59": {
     "inputs": {
       "brightness": -1,
-      "contrast": 1,
+      "contrast": 1.0000000000000002,
-      "saturation": 1,
+      "saturation": 1.0000000000000002,
-      "sharpness": 1,
+      "sharpness": 1.0000000000000002,
       "blur": 0,
       "gaussian_blur": 48.1,
       "edge_enhance": 0,
@@ -486,7 +486,7 @@
   },
   "61": {
     "inputs": {
-      "image": "75857233_00001_.png"
+      "image": "c599a298-2992-487d-95f0-be5e6c08e8c8.png"
     },
     "class_type": "LoadImage",
     "_meta": {
@@ -495,7 +495,7 @@
   },
   "75": {
     "inputs": {
-      "model_path": "svdq-int4-flux.1-fill-dev",
+      "model_path": "svdq-fp4_r32-flux.1-fill-dev.safetensors",
       "cache_threshold": 0,
       "attention": "nunchaku-fp16",
       "cpu_offload": "auto",
@@ -639,7 +639,7 @@
   },
   "94": {
     "inputs": {
-      "value": 1024
+      "value": 2048
     },
     "class_type": "PrimitiveInt",
     "_meta": {
@@ -668,7 +668,7 @@
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@@ -819,7 +819,7 @@
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@@ -832,7 +832,7 @@
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@@ -975,7 +975,7 @@
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+}

change_new_3090_api.json

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+}

change_new_debug.json

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+    "_meta": {
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+}

change_new_debug_api.json

@@ -0,0 +1,970 @@
+{
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+}

change_new_only_3090.json

@@ -0,0 +1,913 @@
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+}

change_new_only_change.json

@@ -0,0 +1,913 @@
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+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "17": {
+    "inputs": {
+      "noise_mask": false,
+      "positive": [
+        "10",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "vae": [
+        "16",
+        0
+      ],
+      "pixels": [
+        "27",
+        1
+      ],
+      "mask": [
+        "27",
+        2
+      ]
+    },
+    "class_type": "InpaintModelConditioning",
+    "_meta": {
+      "title": "InpaintModelConditioning"
+    }
+  },
+  "20": {
+    "inputs": {
+      "crop": "center",
+      "clip_vision": [
+        "21",
+        0
+      ],
+      "image": [
+        "25",
+        0
+      ]
+    },
+    "class_type": "CLIPVisionEncode",
+    "_meta": {
+      "title": "CLIP Vision Encode"
+    }
+  },
+  "21": {
+    "inputs": {
+      "clip_name": "sigclip_vision_patch14_384.safetensors"
+    },
+    "class_type": "CLIPVisionLoader",
+    "_meta": {
+      "title": "Load CLIP Vision"
+    }
+  },
+  "22": {
+    "inputs": {
+      "image": "微信图片_20250810123345_95.jpg"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  },
+  "25": {
+    "inputs": {
+      "width": [
+        "94",
+        0
+      ],
+      "height": [
+        "94",
+        0
+      ],
+      "interpolation": "bicubic",
+      "method": "keep proportion",
+      "condition": "always",
+      "multiple_of": 0,
+      "image": [
+        "22",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "🔧 Image Resize"
+    }
+  },
+  "26": {
+    "inputs": {
+      "width": [
+        "94",
+        0
+      ],
+      "height": [
+        "94",
+        0
+      ],
+      "interpolation": "bicubic",
+      "method": "keep proportion",
+      "condition": "always",
+      "multiple_of": 0,
+      "image": [
+        "61",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "🔧 Image Resize"
+    }
+  },
+  "27": {
+    "inputs": {
+      "context_expand_pixels": 20,
+      "context_expand_factor": 1.0000000000000002,
+      "fill_mask_holes": true,
+      "blur_mask_pixels": 10,
+      "invert_mask": false,
+      "blend_pixels": 16,
+      "rescale_algorithm": "bicubic",
+      "mode": "ranged size",
+      "force_width": 1024,
+      "force_height": 1024,
+      "rescale_factor": 1.0000000000000002,
+      "min_width": 512,
+      "min_height": 512,
+      "max_width": 1800,
+      "max_height": 1800,
+      "padding": 32,
+      "image": [
+        "42",
+        0
+      ],
+      "mask": [
+        "30",
+        0
+      ],
+      "optional_context_mask": [
+        "40",
+        0
+      ]
+    },
+    "class_type": "InpaintCrop",
+    "_meta": {
+      "title": "(OLD 💀, use the new ✂️ Inpaint Crop node)"
+    }
+  },
+  "28": {
+    "inputs": {
+      "mask": [
+        "96",
+        0
+      ]
+    },
+    "class_type": "MaskToImage",
+    "_meta": {
+      "title": "Convert Mask to Image"
+    }
+  },
+  "29": {
+    "inputs": {
+      "width": [
+        "94",
+        0
+      ],
+      "height": [
+        "94",
+        0
+      ],
+      "interpolation": "bicubic",
+      "method": "keep proportion",
+      "condition": "always",
+      "multiple_of": 0,
+      "image": [
+        "28",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "🔧 Image Resize"
+    }
+  },
+  "30": {
+    "inputs": {
+      "channel": "red",
+      "image": [
+        "43",
+        0
+      ]
+    },
+    "class_type": "ImageToMask",
+    "_meta": {
+      "title": "Convert Image to Mask"
+    }
+  },
+  "34": {
+    "inputs": {
+      "rescale_algorithm": "bislerp",
+      "stitch": [
+        "27",
+        0
+      ],
+      "inpainted_image": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "InpaintStitch",
+    "_meta": {
+      "title": "(OLD 💀, use the new ✂️ Inpaint Stitch node)"
+    }
+  },
+  "37": {
+    "inputs": {
+      "direction": "right",
+      "match_image_size": true,
+      "image1": [
+        "38",
+        0
+      ],
+      "image2": [
+        "57",
+        0
+      ]
+    },
+    "class_type": "ImageConcanate",
+    "_meta": {
+      "title": "Image Concatenate"
+    }
+  },
+  "38": {
+    "inputs": {
+      "mask": [
+        "71:2",
+        1
+      ]
+    },
+    "class_type": "MaskToImage",
+    "_meta": {
+      "title": "Convert Mask to Image"
+    }
+  },
+  "40": {
+    "inputs": {
+      "channel": "red",
+      "image": [
+        "37",
+        0
+      ]
+    },
+    "class_type": "ImageToMask",
+    "_meta": {
+      "title": "Convert Image to Mask"
+    }
+  },
+  "42": {
+    "inputs": {
+      "direction": "right",
+      "match_image_size": true,
+      "image1": [
+        "25",
+        0
+      ],
+      "image2": [
+        "26",
+        0
+      ]
+    },
+    "class_type": "ImageConcanate",
+    "_meta": {
+      "title": "Image Concatenate"
+    }
+  },
+  "43": {
+    "inputs": {
+      "direction": "right",
+      "match_image_size": true,
+      "image1": [
+        "59",
+        0
+      ],
+      "image2": [
+        "29",
+        0
+      ]
+    },
+    "class_type": "ImageConcanate",
+    "_meta": {
+      "title": "Image Concatenate"
+    }
+  },
+  "45": {
+    "inputs": {
+      "images": [
+        "42",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "57": {
+    "inputs": {
+      "brightness": -1,
+      "contrast": 0,
+      "saturation": 0,
+      "sharpness": 0,
+      "blur": 0,
+      "gaussian_blur": 0,
+      "edge_enhance": 0,
+      "detail_enhance": "false",
+      "image": [
+        "26",
+        0
+      ]
+    },
+    "class_type": "Image Filter Adjustments",
+    "_meta": {
+      "title": "Image Filter Adjustments"
+    }
+  },
+  "59": {
+    "inputs": {
+      "brightness": -1,
+      "contrast": 1.0000000000000002,
+      "saturation": 1.0000000000000002,
+      "sharpness": 1.0000000000000002,
+      "blur": 0,
+      "gaussian_blur": 48.1,
+      "edge_enhance": 0,
+      "detail_enhance": "false",
+      "image": [
+        "25",
+        0
+      ]
+    },
+    "class_type": "Image Filter Adjustments",
+    "_meta": {
+      "title": "Image Filter Adjustments"
+    }
+  },
+  "61": {
+    "inputs": {
+      "image": "微信图片_20250809133614_84.jpg"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  },
+  "75": {
+    "inputs": {
+      "model_path": "svdq-fp4_r32-flux.1-fill-dev.safetensors",
+      "cache_threshold": 0,
+      "attention": "nunchaku-fp16",
+      "cpu_offload": "auto",
+      "device_id": 0,
+      "data_type": "bfloat16",
+      "i2f_mode": "enabled"
+    },
+    "class_type": "NunchakuFluxDiTLoader",
+    "_meta": {
+      "title": "Nunchaku FLUX DiT Loader"
+    }
+  },
+  "79": {
+    "inputs": {
+      "style_model_name": "flux1-redux-dev.safetensors"
+    },
+    "class_type": "StyleModelLoader",
+    "_meta": {
+      "title": "Load Style Model"
+    }
+  },
+  "83": {
+    "inputs": {
+      "images": [
+        "29",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "84": {
+    "inputs": {
+      "images": [
+        "43",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "85": {
+    "inputs": {
+      "mask": [
+        "30",
+        0
+      ]
+    },
+    "class_type": "MaskPreview",
+    "_meta": {
+      "title": "MaskPreview"
+    }
+  },
+  "86": {
+    "inputs": {
+      "mask": [
+        "71:2",
+        1
+      ]
+    },
+    "class_type": "MaskPreview+",
+    "_meta": {
+      "title": "🔧 Mask Preview"
+    }
+  },
+  "87": {
+    "inputs": {
+      "images": [
+        "38",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "88": {
+    "inputs": {
+      "images": [
+        "37",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "89": {
+    "inputs": {
+      "images": [
+        "57",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "90": {
+    "inputs": {
+      "images": [
+        "59",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "91": {
+    "inputs": {
+      "images": [
+        "27",
+        1
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "93": {
+    "inputs": {
+      "mask": [
+        "27",
+        2
+      ]
+    },
+    "class_type": "MaskPreview",
+    "_meta": {
+      "title": "MaskPreview"
+    }
+  },
+  "94": {
+    "inputs": {
+      "value": 2048
+    },
+    "class_type": "PrimitiveInt",
+    "_meta": {
+      "title": "Int"
+    }
+  },
+  "95": {
+    "inputs": {
+      "detect_hand": "disable",
+      "detect_body": "enable",
+      "detect_face": "disable",
+      "resolution": 512,
+      "bbox_detector": "yolo_nas_m_fp16.onnx",
+      "pose_estimator": "dw-ll_ucoco_384.onnx",
+      "scale_stick_for_xinsr_cn": "disable",
+      "image": [
+        "61",
+        0
+      ]
+    },
+    "class_type": "DWPreprocessor",
+    "_meta": {
+      "title": "DWPose Estimator"
+    }
+  },
+  "96": {
+    "inputs": {
+      "cloth_len": "腰",
+      "line_len": 0.4000000000000001,
+      "cloth_short": true,
+      "width": 0,
+      "height": 0,
+      "left_right_line_width": 1,
+      "human_head2_yao_times": 2.5,
+      "more_clip": 0.1,
+      "kps": [
+        "95",
+        1
+      ]
+    },
+    "class_type": "RenderPeopleKpsMask",
+    "_meta": {
+      "title": "My RenderPeopleKps Mask"
+    }
+  },
+  "98": {
+    "inputs": {
+      "mask": [
+        "96",
+        0
+      ]
+    },
+    "class_type": "MaskPreview",
+    "_meta": {
+      "title": "MaskPreview"
+    }
+  },
+  "99": {
+    "inputs": {
+      "width": [
+        "108",
+        0
+      ],
+      "height": [
+        "107",
+        1
+      ],
+      "x": [
+        "109",
+        0
+      ],
+      "y": 0,
+      "image": [
+        "34",
+        0
+      ]
+    },
+    "class_type": "ImageCrop",
+    "_meta": {
+      "title": "Image Crop"
+    }
+  },
+  "102": {
+    "inputs": {
+      "filename_prefix": "my_test_out",
+      "images": [
+        "99",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "104": {
+    "inputs": {
+      "image": [
+        "61",
+        0
+      ]
+    },
+    "class_type": "GetImageSize",
+    "_meta": {
+      "title": "Get Image Size"
+    }
+  },
+  "106": {
+    "inputs": {
+      "op": "Mul",
+      "a": [
+        "107",
+        1
+      ],
+      "b": [
+        "104",
+        0
+      ]
+    },
+    "class_type": "CM_IntBinaryOperation",
+    "_meta": {
+      "title": "IntBinaryOperation"
+    }
+  },
+  "107": {
+    "inputs": {
+      "image": [
+        "34",
+        0
+      ]
+    },
+    "class_type": "GetImageSize",
+    "_meta": {
+      "title": "Get Image Size"
+    }
+  },
+  "108": {
+    "inputs": {
+      "op": "Div",
+      "a": [
+        "106",
+        0
+      ],
+      "b": [
+        "104",
+        1
+      ]
+    },
+    "class_type": "CM_IntBinaryOperation",
+    "_meta": {
+      "title": "IntBinaryOperation"
+    }
+  },
+  "109": {
+    "inputs": {
+      "op": "Sub",
+      "a": [
+        "107",
+        0
+      ],
+      "b": [
+        "108",
+        0
+      ]
+    },
+    "class_type": "CM_IntBinaryOperation",
+    "_meta": {
+      "title": "IntBinaryOperation"
+    }
+  },
+  "119": {
+    "inputs": {
+      "anything": [
+        "10",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "120": {
+    "inputs": {
+      "anything": [
+        "10",
+        0
+      ]
+    },
+    "class_type": "easy clearCacheAll",
+    "_meta": {
+      "title": "Clear Cache All"
+    }
+  },
+  "124": {
+    "inputs": {
+      "images": [
+        "95",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "128": {
+    "inputs": {
+      "mask": [
+        "96",
+        0
+      ]
+    },
+    "class_type": "MaskPreview",
+    "_meta": {
+      "title": "MaskPreview"
+    }
+  },
+  "71:1": {
+    "inputs": {
+      "model_name": "GroundingDINO_SwinT_OGC (694MB)"
+    },
+    "class_type": "GroundingDinoModelLoader (segment anything)",
+    "_meta": {
+      "title": "GroundingDinoModelLoader (segment anything)"
+    }
+  },
+  "71:0": {
+    "inputs": {
+      "model_name": "sam_vit_h (2.56GB)"
+    },
+    "class_type": "SAMModelLoader (segment anything)",
+    "_meta": {
+      "title": "SAMModelLoader (segment anything)"
+    }
+  },
+  "71:2": {
+    "inputs": {
+      "prompt": "cloth",
+      "threshold": 0.30000000000000004,
+      "sam_model": [
+        "71:0",
+        0
+      ],
+      "grounding_dino_model": [
+        "71:1",
+        0
+      ],
+      "image": [
+        "25",
+        0
+      ]
+    },
+    "class_type": "GroundingDinoSAMSegment (segment anything)",
+    "_meta": {
+      "title": "GroundingDinoSAMSegment (segment anything)"
+    }
+  },
+  "71:3": {
+    "inputs": {
+      "images": [
+        "71:2",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  }
+}

change_openai.py

@@ -0,0 +1,119 @@
+import base64
+#from openai import OpenAI
+
+# client = OpenAI(
+#     #api_key="sk-6Fr1OWm8SJXseEtWjArObksjTr39P08HSNydgNFgsOewI0xp",
+#     api_key="sk-zLFhpbBQKWV4qohV4vD0AFR6Gaa7JwL0Q8zphh1CYFl2EqDM",
+#     base_url="https://www.chataiapi.com/v1",
+# )
+#https://ai.juguang.chat/console/topup
+import requests
+import json
+import http.client
+import json
+import base64
+import re
+
+def save_base64_image_from_json(json_str, output_filename):
+    """
+    从JSON字符串中提取base64图片数据并保存为文件
+    """
+    try:
+        # 解析JSON
+        data = json.loads(json_str)
+        
+        parts = data["candidates"][0]["content"]["parts"]
+        
+        # 遍历parts找到包含inlineData的那个
+        base64_data = None
+        for part in parts:
+            if "inlineData" in part and "data" in part["inlineData"]:
+                base64_data = part["inlineData"]["data"]
+                break
+        
+        if base64_data is None:
+            print("未找到包含图片数据的部分")
+            return False
+        
+        # 清理可能的换行符和空格
+        base64_data = re.sub(r'\s+', '', base64_data)
+        
+        # 解码base64数据
+        image_data = base64.b64decode(base64_data)
+        
+        # 保存为文件
+        with open(output_filename, 'wb') as f:
+            f.write(image_data)
+        
+        print(f"图片已成功保存为: {output_filename}")
+        return True
+        
+    except Exception as e:
+        print(f"保存图片时发生错误: {e}")
+        return False
+
+def image_to_base64(file_path, mime_type=None):
+    if mime_type is None:
+        extension = file_path.split('.')[-1].lower()
+        mime_types = {
+            'jpg': 'image/jpeg',
+            'jpeg': 'image/jpeg',
+            'png': 'image/png',
+            'gif': 'image/gif',
+            'webp': 'image/webp',
+            'bmp': 'image/bmp'
+        }
+        mime_type = mime_types.get(extension, 'application/octet-stream')
+    
+    # 读取文件内容并编码为Base64
+    with open(file_path, 'rb') as image_file:
+        encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
+    
+    # 组合成Data URI格式
+    #return f"data:{mime_type};base64,{encoded_string}"
+    return encoded_string 
+
+conn = http.client.HTTPSConnection("ai.juguang.chat")
+payload = json.dumps({
+  "contents": [
+    {
+      "parts": [
+        {
+          "text": "这是一张有人的图片"
+        },
+        {
+          "inline_data": {
+            "mime_type": "image/jpeg",
+            "data": image_to_base64("/home/xsl/code/ComfyUI/change_cloth/static/imgs/0b9014f9-14dc-4a97-9c99-642441b8c122.jpg")
+          }
+        },
+        {
+          "text": "这是另外一张有衣服，裤子或者裙子，和其他各种可以穿戴在身上物品的图片"
+        },
+        {
+          "inline_data": {
+            "mime_type": "image/jpeg",
+            "data": image_to_base64("/home/xsl/code/ComfyUI/change_cloth/cloth_suit.jpg")
+          }
+        },
+        {
+          "text": "给第一张图片的人物，换上第二张图片的衣服和配饰"
+        }
+      ]
+    }
+  ]
+})
+headers = {
+  'Content-Type': 'application/json',
+  'Authorization': 'Bearer sk-zLFhpbBQKWV4qohV4vD0AFR6Gaa7JwL0Q8zphh1CYFl2EqDM'
+}
+conn.request("POST", "/v1beta/models/gemini-2.5-flash-image-preview:generateContent", payload, headers)
+res = conn.getresponse()
+data = res.read()
+decode_str = data.decode("utf-8")
+
+
+# 调用函数保存图片
+save_base64_image_from_json(decode_str, "out_image.png")
+
+print(decode_str)

change_proxy/change_cloth_proxy.py

@@ -0,0 +1,258 @@
+import os
+import requests
+from flask import Flask, request, jsonify, send_from_directory
+from flask_cors import CORS
+import logging
+from datetime import datetime
+import threading
+import queue
+import uuid
+import time
+
+APP_ROOT = os.path.dirname(os.path.abspath(__file__))
+STATIC_FOLDER = os.path.join(APP_ROOT, 'static')
+
+app = Flask(__name__, static_folder=STATIC_FOLDER, static_url_path='/static')
+CORS(app)
+
+CHANGE_APP_BASE_URL = "http://127.0.0.1:28889"
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+
+def log_message(msg):
+    print(f"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] {msg}")
+    logger.info(msg)
+
+
+class DualQueueProcessor:
+    def __init__(self):
+        self.normal_lock = threading.Lock()
+        self.kuzi_lock = threading.Lock()
+        self.normal_queue = queue.Queue()
+        self.kuzi_queue = queue.Queue()
+        self.normal_processing = 0
+        self.kuzi_processing = 0
+        self.normal_total = 0
+        self.kuzi_total = 0
+        self.stats_lock = threading.Lock()
+        self._start_workers()
+
+    def _start_workers(self):
+        normal_worker = threading.Thread(target=self._process_normal_queue, daemon=True)
+        normal_worker.start()
+        
+        kuzi_worker = threading.Thread(target=self._process_kuzi_queue, daemon=True)
+        kuzi_worker.start()
+        
+        log_message("Dual queue workers started: normal_queue and kuzi_queue")
+
+    def _process_normal_queue(self):
+        while True:
+            task_id, data, result_event, result_container = self.normal_queue.get()
+            log_message(f"[Normal Queue] Processing task {task_id}, queue_size={self.normal_queue.qsize()}")
+            
+            try:
+                response = requests.post(
+                    f"{CHANGE_APP_BASE_URL}/change_cloth_base64",
+                    json=data,
+                    timeout=600
+                )
+                result_container['status_code'] = response.status_code
+                result_container['json'] = response.json()
+                result_container['success'] = True
+                log_message(f"[Normal Queue] Task {task_id} completed with status {response.status_code}")
+            except requests.exceptions.Timeout:
+                result_container['success'] = False
+                result_container['error'] = "Request timeout"
+                log_message(f"[Normal Queue] Task {task_id} timeout")
+            except requests.exceptions.RequestException as e:
+                result_container['success'] = False
+                result_container['error'] = str(e)
+                log_message(f"[Normal Queue] Task {task_id} error: {str(e)}")
+            finally:
+                result_event.set()
+                self.normal_queue.task_done()
+
+    def _process_kuzi_queue(self):
+        while True:
+            task_id, data, result_event, result_container = self.kuzi_queue.get()
+            log_message(f"[Kuzi Queue] Processing task {task_id}, queue_size={self.kuzi_queue.qsize()}")
+            
+            try:
+                response = requests.post(
+                    f"{CHANGE_APP_BASE_URL}/change_cloth_base64",
+                    json=data,
+                    timeout=600
+                )
+                result_container['status_code'] = response.status_code
+                result_container['json'] = response.json()
+                result_container['success'] = True
+                log_message(f"[Kuzi Queue] Task {task_id} completed with status {response.status_code}")
+            except requests.exceptions.Timeout:
+                result_container['success'] = False
+                result_container['error'] = "Request timeout"
+                log_message(f"[Kuzi Queue] Task {task_id} timeout")
+            except requests.exceptions.RequestException as e:
+                result_container['success'] = False
+                result_container['error'] = str(e)
+                log_message(f"[Kuzi Queue] Task {task_id} error: {str(e)}")
+            finally:
+                result_event.set()
+                self.kuzi_queue.task_done()
+
+    def submit_request(self, data):
+        has_kuzi = data.get('kuzi_img') is not None and data.get('kuzi_img') != ''
+        task_id = str(uuid.uuid4())[:8]
+        result_event = threading.Event()
+        result_container = {'success': False}
+        
+        if has_kuzi:
+            with self.stats_lock:
+                self.kuzi_total += 1
+                queue_position = self.kuzi_queue.qsize() + 1
+            self.kuzi_queue.put((task_id, data, result_event, result_container))
+            log_message(f"[Kuzi Queue] Task {task_id} submitted, position={queue_position}")
+            queue_name = "kuzi"
+        else:
+            with self.stats_lock:
+                self.normal_total += 1
+                queue_position = self.normal_queue.qsize() + 1
+            self.normal_queue.put((task_id, data, result_event, result_container))
+            log_message(f"[Normal Queue] Task {task_id} submitted, position={queue_position}")
+            queue_name = "normal"
+        
+        return task_id, result_event, result_container, queue_name, queue_position
+
+    def get_stats(self):
+        with self.stats_lock:
+            return {
+                "normal_queue_size": self.normal_queue.qsize(),
+                "kuzi_queue_size": self.kuzi_queue.qsize(),
+                "normal_total": self.normal_total,
+                "kuzi_total": self.kuzi_total
+            }
+
+
+dual_queue = DualQueueProcessor()
+
+
+@app.route('/')
+def index():
+    return send_from_directory(STATIC_FOLDER, 'index.html')
+
+
+@app.route('/health', methods=['GET'])
+def health():
+    return jsonify({"status": "ok", "service": "change_cloth_proxy"})
+
+
+@app.route('/queue_stats', methods=['GET'])
+def queue_stats():
+    stats = dual_queue.get_stats()
+    return jsonify({
+        "ret": 0,
+        "msg": "success",
+        "data": stats
+    })
+
+
+@app.route('/change_cloth', methods=['POST'])
+def change_cloth():
+    log_message("change_cloth called")
+    data = request.get_json()
+    if not data:
+        return jsonify({"ret": -1, "state": -1, "msg": "No JSON data provided"}), 400
+
+    required_fields = ["human_url", "cloth_url", "output_format"]
+    for field in required_fields:
+        if field not in data:
+            return jsonify({"ret": -1, "state": -1, "msg": f"Missing required field: {field}"}), 400
+
+    log_message(f"Forwarding change_cloth request: human_url={data.get('human_url')}, cloth_url={data.get('cloth_url')}")
+
+    try:
+        response = requests.post(
+            f"{CHANGE_APP_BASE_URL}/change_cloth",
+            json=data,
+            timeout=600
+        )
+        log_message(f"change_cloth response status: {response.status_code}")
+        return jsonify(response.json()), response.status_code
+    except requests.exceptions.Timeout:
+        log_message("change_cloth request timeout")
+        return jsonify({"ret": -1, "state": -1, "msg": "Request timeout"}), 504
+    except requests.exceptions.RequestException as e:
+        log_message(f"change_cloth request error: {str(e)}")
+        return jsonify({"ret": -1, "state": -1, "msg": f"Request failed: {str(e)}"}), 500
+
+
+@app.route('/change_cloth_base64', methods=['POST'])
+def change_cloth_base64():
+    log_message("change_cloth_base64 called")
+    data = request.get_json()
+    if not data:
+        return jsonify({"ret": -1, "state": -1, "msg": "No JSON data provided"}), 400
+
+    required_fields = ["human_img", "cloth_img", "output_format"]
+    for field in required_fields:
+        if field not in data:
+            return jsonify({"ret": -1, "state": -1, "msg": f"Missing required field: {field}"}), 400
+
+    has_kuzi = data.get('kuzi_img') is not None and data.get('kuzi_img') != ''
+    queue_type = "kuzi" if has_kuzi else "normal"
+    
+    task_id, result_event, result_container, queue_name, queue_position = dual_queue.submit_request(data)
+    
+    log_message(f"Task {task_id} queued in {queue_name} queue, position={queue_position}, waiting for result...")
+    
+    if result_event.wait(timeout=610):
+        if result_container.get('success'):
+            log_message(f"Task {task_id} returned successfully")
+            return jsonify(result_container['json']), result_container['status_code']
+        else:
+            error_msg = result_container.get('error', 'Unknown error')
+            log_message(f"Task {task_id} failed: {error_msg}")
+            return jsonify({"ret": -1, "state": -1, "msg": error_msg}), 500
+    else:
+        log_message(f"Task {task_id} timed out waiting in queue")
+        return jsonify({"ret": -1, "state": -1, "msg": "Queue timeout"}), 504
+
+
+@app.route('/do_change_cloth', methods=['POST'])
+def do_change_cloth():
+    log_message("do_change_cloth called")
+    data = request.get_json()
+    if not data:
+        return jsonify({"ret": -1, "state": -1, "msg": "No JSON data provided"}), 400
+
+    required_fields = ["human_url", "cloth_url", "output_format"]
+    for field in required_fields:
+        if field not in data:
+            return jsonify({"ret": -1, "state": -1, "msg": f"Missing required field: {field}"}), 400
+
+    log_message(f"Forwarding do_change_cloth request: human_url={data.get('human_url')}, cloth_url={data.get('cloth_url')}")
+
+    try:
+        response = requests.post(
+            f"{CHANGE_APP_BASE_URL}/do_change_cloth",
+            json=data,
+            timeout=600
+        )
+        log_message(f"do_change_cloth response status: {response.status_code}")
+        return jsonify(response.json()), response.status_code
+    except requests.exceptions.Timeout:
+        log_message("do_change_cloth request timeout")
+        return jsonify({"ret": -1, "state": -1, "msg": "Request timeout"}), 504
+    except requests.exceptions.RequestException as e:
+        log_message(f"do_change_cloth request error: {str(e)}")
+        return jsonify({"ret": -1, "state": -1, "msg": f"Request failed: {str(e)}"}), 500
+
+
+if __name__ == '__main__':
+    log_message(f"Starting change_cloth_proxy service on port 28888, forwarding to {CHANGE_APP_BASE_URL}")
+    app.run(host="0.0.0.0", port=28888, debug=False, threaded=True)

change_proxy/static/index.html

@@ -0,0 +1,313 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>服装更换工具</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 800px;
+            margin: 0 auto;
+            padding: 20px;
+            line-height: 1.6;
+        }
+        h1 {
+            text-align: center;
+            color: #333;
+        }
+        .image-upload-container {
+            display: flex;
+            justify-content: space-between;
+            margin-bottom: 20px;
+        }
+        .image-upload-box {
+            width: 48%;
+            border: 2px dashed #ccc;
+            padding: 15px;
+            text-align: center;
+            border-radius: 5px;
+        }
+        .image-upload-box h3 {
+            margin-top: 0;
+        }
+        .image-preview {
+            max-width: 100%;
+            max-height: 300px;
+            margin-top: 10px;
+            display: none;
+        }
+        button {
+            background-color: #4CAF50;
+            color: white;
+            padding: 10px 15px;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+            font-size: 16px;
+            display: block;
+            margin: 20px auto;
+        }
+        button:hover {
+            background-color: #45a049;
+        }
+        #result {
+            margin-top: 20px;
+            padding: 15px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            display: none;
+        }
+        #loading {
+            text-align: center;
+            display: none;
+            margin: 20px 0;
+        }
+        .spinner {
+            border: 5px solid #f3f3f3;
+            border-top: 5px solid #3498db;
+            border-radius: 50%;
+            width: 50px;
+            height: 50px;
+            animation: spin 2s linear infinite;
+            margin: 0 auto;
+        }
+        @keyframes spin {
+            0% { transform: rotate(0deg); }
+            100% { transform: rotate(360deg); }
+        }
+        .error {
+            color: red;
+        }
+        .option-box {
+            margin: 15px 0;
+            padding: 15px;
+            border: 1px solid #ddd;
+            border-radius: 5px;
+        }
+        .option-box label {
+            display: block;
+            margin-bottom: 10px;
+        }
+        .cloth-len-select {
+            margin: 15px 0;
+        }
+        .cloth-len-select label {
+            display: block;
+            margin-bottom: 5px;
+            font-weight: bold;
+        }
+        .cloth-len-select select {
+            width: 100%;
+            padding: 8px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+        }
+    </style>
+</head>
+<body>
+    <h1>服装更换工具</h1>
+    
+    <div class="image-upload-container">
+        <div class="image-upload-box">
+            <h3>人体图片</h3>
+            <input type="file" id="humanInput" accept="image/*">
+            <img id="humanPreview" class="image-preview" alt="人体图片预览">
+        </div>
+        
+        <div class="image-upload-box">
+            <h3>衣服图片</h3>
+            <input type="file" id="clothInput" accept="image/*">
+            <img id="clothPreview" class="image-preview" alt="衣服图片预览">
+        </div>
+    </div>
+
+    <div class="image-upload-container">
+        <div class="image-upload-box">
+            <h3>裤子图片</h3>
+            <input type="file" id="kuziInput" accept="image/*">
+            <img id="kuziPreview" class="image-preview" alt="裤子图片预览">
+        </div>
+        
+        <div class="cloth-len-select">
+            <label for="clothLenSelect">选择服装长度：</label>
+            <select id="clothLenSelect">
+                <option value="胸">胸</option>
+                <option value="腰">腰</option>
+                <option value="跨">跨</option>
+                <option value="大腿">大腿</option>
+                <option value="膝盖">膝盖</option>
+                <option value="小腿">小腿</option>
+                <option value="脚踝">脚踝</option>
+                <option value="拖地">拖地</option>
+            </select>
+        </div>
+    </div>
+    
+    <div class="option-box">
+        <label>
+            <input type="checkbox" id="no2Checkbox"> 设置 no2 不要两步(一步完成)
+        </label>
+        <br>
+        <label>
+            <input type="checkbox" id="tuodiCheckbox"> 设置 tuodi(拖地)
+        </label>
+        <br>
+        <label>
+            <input type="checkbox" id="suitCheckbox"> 设置 suit(套装)
+        </label>
+    </div>
+    
+    <button id="submitBtn">提交处理</button>
+    
+    <div id="loading">
+        <div class="spinner"></div>
+        <p>正在处理中，请稍候...</p>
+    </div>
+    
+    <div id="result"></div>
+    
+    <script>
+        document.getElementById('humanInput').addEventListener('change', function(e) {
+            const file = e.target.files[0];
+            if (file) {
+                const reader = new FileReader();
+                reader.onload = function(event) {
+                    const img = document.getElementById('humanPreview');
+                    img.src = event.target.result;
+                    img.style.display = 'block';
+                };
+                reader.readAsDataURL(file);
+            }
+        });
+        
+        document.getElementById('clothInput').addEventListener('change', function(e) {
+            const file = e.target.files[0];
+            if (file) {
+                const reader = new FileReader();
+                reader.onload = function(event) {
+                    const img = document.getElementById('clothPreview');
+                    img.src = event.target.result;
+                    img.style.display = 'block';
+                };
+                reader.readAsDataURL(file);
+            }
+        });
+
+        document.getElementById('kuziInput').addEventListener('change', function(e) {
+            const file = e.target.files[0];
+            if (file) {
+                const reader = new FileReader();
+                reader.onload = function(event) {
+                    const img = document.getElementById('kuziPreview');
+                    img.src = event.target.result;
+                    img.style.display = 'block';
+                };
+                reader.readAsDataURL(file);
+            }
+        });
+        
+        document.getElementById('submitBtn').addEventListener('click', function() {
+            const humanFile = document.getElementById('humanInput').files[0];
+            const clothFile = document.getElementById('clothInput').files[0];
+            const kuziFile = document.getElementById('kuziInput').files[0];
+            const no2 = document.getElementById("no2Checkbox").checked;
+            const tuodi = document.getElementById("tuodiCheckbox").checked;
+            const suit = document.getElementById("suitCheckbox").checked;
+            const clothLen = document.getElementById("clothLenSelect").value;
+
+            
+            if (!humanFile || !clothFile) {
+                alert('请同时选择人体图片和衣服图片！');
+                return;
+            }
+            
+            document.getElementById('loading').style.display = 'block';
+            document.getElementById('result').style.display = 'none';
+            
+            Promise.all([
+                readFileAsDataURL(humanFile),
+                readFileAsDataURL(clothFile),
+                kuziFile ? readFileAsDataURL(kuziFile) : Promise.resolve(null)
+            ]).then(([humanDataURL, clothDataURL, kuziDataURL]) => {
+
+                const data = {
+                    human_img: humanDataURL,
+                    cloth_img: clothDataURL,
+                    output_format: "url",
+                    no2: no2,
+                    tuodi: tuodi,
+                    suit: suit,
+                    cloth_len: clothLen
+                };
+
+                if(kuziDataURL)
+                {
+                    data.kuzi_img = kuziDataURL;
+                }
+
+                console.log("准备发送的数据:", data);
+                
+                fetch('/change_cloth_base64', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify(data)
+                })
+                .then(response => {
+                    if (!response.ok) {
+                        throw new Error(`HTTP错误! 状态: ${response.status}`);
+                    }
+                    return response.json();
+                })
+                .then(data => {
+                    document.getElementById('loading').style.display = 'none';
+                    
+                    const resultDiv = document.getElementById('result');
+                    if (data.url) {
+                        resultDiv.innerHTML = `
+                            <h3>处理结果</h3>
+                            <p>处理成功！点击查看结果：</p>
+                            <a href="${data.url}" target="_blank">${data.url}</a>
+                            <p><img src="${data.url}" style="max-width: 100%; margin-top: 10px;"></p>
+                            <a href="${data.first_url}" target="_blank">${data.url}</a>
+                            <p><img src="${data.first_url}" style="max-width: 100%; margin-top: 10px;"></p>
+                            <a href="${data.second_url}" target="_blank">${data.url}</a>
+                            <p><img src="${data.second_url}" style="max-width: 100%; margin-top: 10px;"></p>
+                        `;
+                    } else {
+                        resultDiv.innerHTML = `
+                            <h3>处理结果</h3>
+                            <p class="error">处理完成，但未返回预期的URL</p>
+                            <p>返回数据：</p>
+                            <pre>${JSON.stringify(data, null, 2)}</pre>
+                        `;
+                    }
+                    resultDiv.style.display = 'block';
+                })
+                .catch(error => {
+                    console.error('Error:', error);
+                    document.getElementById('loading').style.display = 'none';
+                    document.getElementById('result').innerHTML = `
+                        <h3 class="error">错误</h3>
+                        <p>处理过程中出现错误：${error.message}</p>
+                        <p>请检查控制台获取更多信息</p>
+                    `;
+                    document.getElementById('result').style.display = 'block';
+                });
+            });
+        });
+        
+        function readFileAsDataURL(file) {
+            return new Promise((resolve, reject) => {
+                const reader = new FileReader();
+                reader.onload = () => resolve(reader.result);
+                reader.onerror = (error) => reject(error);
+                reader.readAsDataURL(file);
+            });
+        }
+    </script>
+</body>
+</html>

check_img_body.py

@@ -1,6 +1,73 @@
 import cv2
 import mediapipe as mp
 
+async def listen_node_output(prompt_id, target_node_id):
+    uri = "ws://localhost:8188/ws"
+    async with websockets.connect(uri) as websocket:
+        await websocket.send(json.dumps({"prompt_id": prompt_id}))
+        
+        while True:
+            message = await websocket.recv()
+            
+            # 1. 处理二进制数据
+            if isinstance(message, bytes):
+                try:
+                    message = message.decode("utf-8")
+                except UnicodeDecodeError:
+                    print(f"[{datetime.now().strftime('%H:%M:%S')}] 收到二进制数据 (长度: {len(message)} bytes)")
+                    continue
+            
+            # 2. 解析JSON
+            try:
+                data = json.loads(message)
+                print(f"cur data {data}")
+            except json.JSONDecodeError:
+                print(f"[{datetime.now().strftime('%H:%M:%S')}] 非JSON数据: {message[:100]}...")
+                continue
+
+            if data.get("type") == "progress":
+                pdata = data.get('data', {})
+                print(f"cur progress {pdata}")
+                # if value >= max:
+                #     return f"finished value:{value} max:{max}"
+
+            if data.get("type") == "progress_state":
+                nodes = data.get('data', {}).get('nodes', {})
+                for node in nodes:
+                    if node.get("state", None) != 'finished':
+                        print(f"progress_state node:{node}")
+            
+            # 3. 输出运行状态
+            if data.get("type") == "status":
+                print(f"[{datetime.now().strftime('%H:%M:%S')}] 系统状态: {data.get('data', {}).get('status', {})}")
+                status = data.get('data', {}).get('status', None)
+                print(f"statue:{status}")
+                if status:
+                    exec_info = status.get('exec_info', None)
+                    print(f"exec_info:{exec_info}")
+                    if exec_info:
+                        queue_remaining = exec_info.get('queue_remaining', None)
+                        print(f"queue_remaining:{queue_remaining}")
+                        if queue_remaining == 0:
+                            return "process end"
+                continue
+                
+            if data.get("type") == "executing":
+                node_id = data.get("data", {}).get("node")
+                progress = data.get("data", {}).get("progress", 0)
+                print(f"[{datetime.now().strftime('%H:%M:%S')}] 正在执行节点 {node_id} (进度: {progress:.0%})")
+            
+            # 4. 目标节点完成
+            if data.get("type") == "executed" and data.get("data", {}).get("node") == target_node_id:
+                output = data.get("data", {}).get("output")
+                print(f"[{datetime.now().strftime('%H:%M:%S')}] 节点 {target_node_id} 完成!")
+                return output
+
+
+
+    # output = asyncio.run(listen_node_output(prompt_id, "104"))
+    # print("最终输出:", output)
+
 # def is_thigh_visible(image_path):
 #     # 初始化MediaPipe Pose模型
 #     mp_pose = mp.solutions.pose
@@ -36,4 +103,4 @@ import mediapipe as mp
     
 #     return left_thigh_visible and right_thigh_visible
 
-# print(is_thigh_visible("/home/szlc/code/ComfyUI/change_cloth/static/imgs/fc74eded_00001_.jpg"))
+# print(is_thigh_visible("/home/xsl/code/ComfyUI/change_cloth/static/imgs/fc74eded_00001_.jpg"))

config.py

@@ -4,7 +4,7 @@ import logging
 
 QUEUE_NAME = 'task_queue'
 # 配置
-REDIS_HOST = '127.0.0.1'
+REDIS_HOST = '127.0.0.1'#'192.168.101.118'
 REDIS_PORT = 6379
 REDIS_DB = 0
 DEFAULT_TIMEOUT = (60*20)
@@ -37,6 +37,23 @@ console_handler.setFormatter(console_formatter)
 logger.addHandler(file_handler)
 logger.addHandler(console_handler)
 
+selfComputer = "5090"
+
+if selfComputer == "5090":
+    change_tuodi_input = 'change_tuodi_input_api.json'
+    change_only_name = "change_new_only_change.json"
+    change_with_add_cloth = "change_new_debug_api.json"
+    xiezhen_name = "xiezhen-0812-40s_api.json"
+    base64_test_port = 28889
+else:
+    change_tuodi_input = 'change_tuodi_input_3090_api.json'
+    change_only_name = "change_new_only_3090.json"
+    change_with_add_cloth = "change_new_3090_api.json"
+    xiezhen_name = "xiezhen-0812-40s_api.json"
+    base64_test_port = 18888
+
+
+
 def acquire_lock(redis_client, lock_name):
     lock = Lock(
         redis_client,

flux_kontext_dev_basic_xz.json

@@ -0,0 +1,212 @@
+{
+  "6": {
+    "inputs": {
+      "text": "Using this elegant style, create a portrait of a swan wearing a pearl tiara and lace collar, maintaining the same refined quality and soft color tones.",
+      "clip": [
+        "38",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Positive Prompt)"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "31",
+        0
+      ],
+      "vae": [
+        "39",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "31": {
+    "inputs": {
+      "seed": 331754788447825,
+      "steps": 20,
+      "cfg": 1,
+      "sampler_name": "euler",
+      "scheduler": "simple",
+      "denoise": 1,
+      "model": [
+        "37",
+        0
+      ],
+      "positive": [
+        "35",
+        0
+      ],
+      "negative": [
+        "135",
+        0
+      ],
+      "latent_image": [
+        "124",
+        0
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "KSampler"
+    }
+  },
+  "35": {
+    "inputs": {
+      "guidance": 2.5,
+      "conditioning": [
+        "177",
+        0
+      ]
+    },
+    "class_type": "FluxGuidance",
+    "_meta": {
+      "title": "FluxGuidance"
+    }
+  },
+  "37": {
+    "inputs": {
+      "unet_name": "flux1-dev-kontext_fp8_scaled.safetensors",
+      "weight_dtype": "default"
+    },
+    "class_type": "UNETLoader",
+    "_meta": {
+      "title": "Load Diffusion Model"
+    }
+  },
+  "38": {
+    "inputs": {
+      "clip_name1": "clip_l.safetensors",
+      "clip_name2": "t5xxl_fp8_e4m3fn_scaled.safetensors",
+      "type": "flux",
+      "device": "default"
+    },
+    "class_type": "DualCLIPLoader",
+    "_meta": {
+      "title": "DualCLIPLoader"
+    }
+  },
+  "39": {
+    "inputs": {
+      "vae_name": "ae.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "42": {
+    "inputs": {
+      "image": [
+        "146",
+        0
+      ]
+    },
+    "class_type": "FluxKontextImageScale",
+    "_meta": {
+      "title": "FluxKontextImageScale"
+    }
+  },
+  "124": {
+    "inputs": {
+      "pixels": [
+        "42",
+        0
+      ],
+      "vae": [
+        "39",
+        0
+      ]
+    },
+    "class_type": "VAEEncode",
+    "_meta": {
+      "title": "VAE Encode"
+    }
+  },
+  "135": {
+    "inputs": {
+      "conditioning": [
+        "6",
+        0
+      ]
+    },
+    "class_type": "ConditioningZeroOut",
+    "_meta": {
+      "title": "ConditioningZeroOut"
+    }
+  },
+  "136": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "142": {
+    "inputs": {
+      "image": "ComfyUI_00441_.png [output]",
+      "refresh": "refresh"
+    },
+    "class_type": "LoadImageOutput",
+    "_meta": {
+      "title": "Load Image (from Outputs)"
+    }
+  },
+  "146": {
+    "inputs": {
+      "direction": "right",
+      "match_image_size": true,
+      "spacing_width": 0,
+      "spacing_color": "white",
+      "image1": [
+        "142",
+        0
+      ]
+    },
+    "class_type": "ImageStitch",
+    "_meta": {
+      "title": "Image Stitch"
+    }
+  },
+  "173": {
+    "inputs": {
+      "images": [
+        "42",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "177": {
+    "inputs": {
+      "conditioning": [
+        "6",
+        0
+      ],
+      "latent": [
+        "124",
+        0
+      ]
+    },
+    "class_type": "ReferenceLatent",
+    "_meta": {
+      "title": "ReferenceLatent"
+    }
+  }
+}

http_app.py

@@ -56,7 +56,7 @@ def takeoff_cloth_first(human_name):
     if queue["queue_running"] or queue["queue_pending"]:
         return None, "cur gpu is busy"
 
-    with open('/home/szlc/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
+    with open('/home/xsl/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
         prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
@@ -122,15 +122,15 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, is_generated):
                 return None, f"takeoff_cloth_first error {human_name}"
             else:
                 human_name = takeoff_file_name
-                takeoff_file_path_name = os.path.join('/home/szlc/code/ComfyUI/output', takeoff_file_name)
+                takeoff_file_path_name = os.path.join('/home/xsl/code/ComfyUI/output', takeoff_file_name)
-                takeoff_file_path_name_input = os.path.join('/home/szlc/code/ComfyUI/input', takeoff_file_name)
+                takeoff_file_path_name_input = os.path.join('/home/xsl/code/ComfyUI/input', takeoff_file_name)
                 shutil.copy(takeoff_file_path_name, takeoff_file_path_name_input)
     
     queue = requests.get("http://localhost:8188/queue").json()
     if queue["queue_running"] or queue["queue_pending"]:
         return None, "cur gpu is busy"
 
-    with open('/home/szlc/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
+    with open('/home/xsl/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
         prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
@@ -207,13 +207,13 @@ def save_base64_image(base64_str, prefix):
         timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
         unique_id = str(uuid.uuid4())[:8]
         filename = f"{prefix}_{timestamp}_{unique_id}{file_ext}"
-        filepath = os.path.join('/home/szlc/code/ComfyUI/change_cloth/static/imgs', filename)
+        filepath = os.path.join('/home/xsl/code/ComfyUI/change_cloth/static/imgs', filename)
         
         # 解码并保存图片
         with open(filepath, 'wb') as f:
             f.write(base64.b64decode(data))
 
-        input_filepath = os.path.join('/home/szlc/code/ComfyUI/input', filename)
+        input_filepath = os.path.join('/home/xsl/code/ComfyUI/input', filename)
         # 解码并保存图片
         with open(input_filepath, 'wb') as f:
             f.write(base64.b64decode(data))
@@ -255,10 +255,10 @@ def image_to_base64(file_path, mime_type=None):
 
 def upload_to_oss(image_path, object_name=None):
     # 配置信息（替换为你的实际信息）
-    access_key_id = 'LTAI5tB9t2RH6f1drSLvVLLZ'
+    access_key_id = 'LTAI5tGp1sLzedqxihcNC1eb'
-    access_key_secret = '91uzPI1RAFHN7n3Y6TJDGFP8w0dG1R'
+    access_key_secret = 'IFZE1b8YYreCP6zfA6GaZ9uBT678qO'
     endpoint = 'oss-cn-beijing.aliyuncs.com'  # 替换为你的Endpoint
-    bucket_name = 'llyz'
+    bucket_name = 'xiangsilian'
     
     # 创建Bucket实例
     auth = oss2.Auth(access_key_id, access_key_secret)
@@ -286,21 +286,21 @@ def upload_to_oss(image_path, object_name=None):
 
 
 def process_change_cloth(human_filename, cloth_filename, output_format, img_url, is_generated):
-    w,h = get_image_dimensions(f'/home/szlc/code/ComfyUI/input/{human_filename}') 
+    w,h = get_image_dimensions(f'/home/xsl/code/ComfyUI/input/{human_filename}') 
 
     out_put_name, msg = change(human_filename, cloth_filename, w, h, img_url, is_generated)
     if out_put_name == None:
         print(f'Failed to change cloth {msg}')
         return jsonify({"ret":-1, 'msg': f'Failed to change cloth {msg}'}), 200
     
-    image = Image.open(f'/home/szlc/code/ComfyUI/output/{out_put_name}')
+    image = Image.open(f'/home/xsl/code/ComfyUI/output/{out_put_name}')
     jpg_name = out_put_name.replace(".png", ".jpg")
-    jpg_path_name = f'/home/szlc/code/ComfyUI/change_cloth/static/imgs/{jpg_name}'
+    jpg_path_name = f'/home/xsl/code/ComfyUI/change_cloth/static/imgs/{jpg_name}'
     image.save(jpg_path_name, quality=95)
 
 
     upload_to_oss(jpg_path_name, jpg_name)  # 第二个参数可选，指定OSS上的路径
-    https_url = f'https://llyz.oss-cn-beijing.aliyuncs.com/{jpg_name}'
+    https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/{jpg_name}'
     print(f"生成的HTTPS URL: {https_url}")
 
     if 'base64' in output_format:
@@ -347,7 +347,7 @@ def change_cloth_base64():
         if not cloth_filename:
             return jsonify({"ret":-1, 'msg': 'Failed to save cloth image'}), 500
         
-        img_url = f"http://112.126.94.241:18888/static/imgs/{cloth_filename}"
+        img_url = f"http://117.50.44.174:18888/static/imgs/{cloth_filename}"
 
         return process_change_cloth(human_filename, cloth_filename, output_format, img_url, is_generated)
         
@@ -376,13 +376,13 @@ def save_image_from_url(image_url):
         # 获取原始图片格式
         ext = get_file_extension(image_url)
         filename = f"{uuid.uuid4()}{ext}"
-        filepath = os.path.join('/home/szlc/code/ComfyUI/change_cloth/static/imgs', filename)
+        filepath = os.path.join('/home/xsl/code/ComfyUI/change_cloth/static/imgs', filename)
 
         with open(filepath, "wb") as f:
             for chunk in response.iter_content(1024):
                 f.write(chunk)
 
-        input_filepath = os.path.join('/home/szlc/code/ComfyUI/input', filename)
+        input_filepath = os.path.join('/home/xsl/code/ComfyUI/input', filename)
         shutil.copy(filepath, input_filepath)
 
         return filename
@@ -394,6 +394,7 @@ def save_image_from_url(image_url):
 def change_cloth():
     """从 URL 下载图片"""
     data = request.json
+    print(f"change_cloth data: {data}")
 
     is_generated = data.get("is_generated")
     # if not is_generated:
@@ -406,6 +407,7 @@ def change_cloth():
     if not human_url:
         return jsonify({"error": "Missing 'human_url' parameter"}), 400
 
+    
     human_filename = save_image_from_url(human_url)
     if not human_filename:
         return jsonify({"error": "Failed to download or save human image"}), 500

oss_test.py

@@ -2,10 +2,10 @@ import oss2
 
 def upload_to_oss(image_path, object_name=None):
     # 配置信息（替换为你的实际信息）
-    access_key_id = 'LTAI5tB9t2RH6f1drSLvVLLZ'
+    access_key_id = 'LTAI5tGp1sLzedqxihcNC1eb'
-    access_key_secret = '91uzPI1RAFHN7n3Y6TJDGFP8w0dG1R'
+    access_key_secret = 'IFZE1b8YYreCP6zfA6GaZ9uBT678qO'
     endpoint = 'oss-cn-beijing.aliyuncs.com'  # 替换为你的Endpoint
-    bucket_name = 'llyz'
+    bucket_name = 'xiangsilian'
     
     # 创建Bucket实例
     auth = oss2.Auth(access_key_id, access_key_secret)
@@ -32,7 +32,7 @@ def upload_to_oss(image_path, object_name=None):
         return None
 
 # 使用示例
-image_path = '/home/szlc/code/ComfyUI/change_cloth/girl8010.jpg'  # 本地图片路径
+image_path = '/home/xsl/code/ComfyUI/change_cloth/girl8010.jpg'  # 本地图片路径
 upload_to_oss(image_path, 'girl8011.jpg')  # 第二个参数可选，指定OSS上的路径
-https_url = f'https://llyz.oss-cn-beijing.aliyuncs.com/girl8011.jpg'
+https_url = f'https://xiangsilian.oss-cn-beijing.aliyuncs.com/girl8011.jpg'
 print(f"生成的HTTPS URL: {https_url}")

static/img.html

@@ -0,0 +1,186 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>图片处理工具</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 600px;
+            margin: 0 auto;
+            padding: 20px;
+            line-height: 1.6;
+        }
+        .container {
+            display: flex;
+            flex-direction: column;
+            gap: 20px;
+        }
+        .form-group {
+            display: flex;
+            flex-direction: column;
+            gap: 8px;
+        }
+        label {
+            font-weight: bold;
+        }
+        input[type="file"], input[type="text"] {
+            padding: 8px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+        }
+        button {
+            padding: 10px 15px;
+            background-color: #4CAF50;
+            color: white;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+            font-size: 16px;
+        }
+        button:hover {
+            background-color: #45a049;
+        }
+        .preview {
+            margin-top: 20px;
+            display: flex;
+            flex-wrap: wrap;
+            gap: 20px;
+        }
+        .preview-item {
+            display: flex;
+            flex-direction: column;
+            align-items: center;
+        }
+        .preview-item img {
+            max-width: 200px;
+            max-height: 200px;
+            border: 1px solid #ddd;
+            margin-top: 10px;
+        }
+        #status {
+            margin-top: 20px;
+            padding: 10px;
+            border-radius: 4px;
+        }
+        .success {
+            background-color: #dff0d8;
+            color: #3c763d;
+        }
+        .error {
+            background-color: #f2dede;
+            color: #a94442;
+        }
+    </style>
+</head>
+<body>
+    <h1>图片处理工具</h1>
+    <div class="container">
+        <form id="imageForm">
+            <div class="form-group">
+                <label for="fileUpload">上传图片:</label>
+                <input type="file" id="fileUpload" name="file" accept="image/*" required>
+                <div class="preview">
+                    <div class="preview-item">
+                        <span>上传的图片预览:</span>
+                        <img id="uploadPreview" src="#" alt="上传的图片预览" style="display: none;">
+                    </div>
+                </div>
+            </div>
+            
+            <div class="form-group">
+                <label for="clothImgUrl">服装图片URL:</label>
+                <input type="text" id="clothImgUrl" name="cloth_img" 
+                       value="http://117.50.44.174:18888/static/imgs/cloth_20250713_092536_279335d2.jpg" 
+                       placeholder="输入服装图片的URL" required>
+                <div class="preview">
+                    <div class="preview-item">
+                        <span>URL图片预览:</span>
+                        <img id="urlPreview" src="http://117.50.44.174:18888/static/imgs/cloth_20250713_092536_279335d2.jpg" 
+                             alt="URL图片预览" onerror="this.style.display='none'">
+                    </div>
+                </div>
+            </div>
+            
+            <button type="submit">提交处理</button>
+        </form>
+        
+        <div id="status"></div>
+    </div>
+
+    <script>
+        // 上传图片预览
+        document.getElementById('fileUpload').addEventListener('change', function(e) {
+            const file = e.target.files[0];
+            if (file) {
+                const reader = new FileReader();
+                reader.onload = function(event) {
+                    const preview = document.getElementById('uploadPreview');
+                    preview.src = event.target.result;
+                    preview.style.display = 'block';
+                };
+                reader.readAsDataURL(file);
+            }
+        });
+
+        // URL图片预览
+        document.getElementById('clothImgUrl').addEventListener('input', function(e) {
+            const url = e.target.value;
+            if (url) {
+                const preview = document.getElementById('urlPreview');
+                preview.src = url;
+                preview.style.display = 'block';
+                
+                // 检查图片是否能加载
+                preview.onerror = function() {
+                    preview.alt = "无法加载图片";
+                    preview.src = "";
+                };
+            }
+        });
+
+        // 表单提交
+        document.getElementById('imageForm').addEventListener('submit', function(e) {
+            e.preventDefault();
+            
+            const statusDiv = document.getElementById('status');
+            statusDiv.textContent = "正在提交...";
+            statusDiv.className = "";
+            
+            const formData = new FormData(this);
+            const apiUrl = "http://117.50.44.174:19001/process-image";
+            
+            fetch(apiUrl, {
+                method: 'POST',
+                body: formData
+            })
+            .then(response => {
+                if (!response.ok) {
+                    throw new Error('网络响应不正常');
+                }
+                return response.json();
+            })
+            .then(data => {
+                statusDiv.textContent = "提交成功！";
+                statusDiv.className = "success";
+                console.log("成功:", data);
+            })
+            .catch(error => {
+                statusDiv.textContent = "提交失败: " + error.message;
+                statusDiv.className = "error";
+                console.error("错误:", error);
+            });
+        });
+
+        // 初始加载时检查默认URL图片
+        window.addEventListener('load', function() {
+            const preview = document.getElementById('urlPreview');
+            preview.onerror = function() {
+                preview.alt = "无法加载默认图片";
+                preview.src = "";
+            };
+        });
+    </script>
+</body>
+</html>

static/index.html

@@ -79,6 +79,31 @@
         .error {
             color: red;
         }
+        .option-box {
+            margin: 15px 0;
+            padding: 15px;
+            border: 1px solid #ddd;
+            border-radius: 5px;
+        }
+        .option-box label {
+            display: block;
+            margin-bottom: 10px;
+        }
+        .cloth-len-select {
+            margin: 15px 0;
+        }
+        .cloth-len-select label {
+            display: block;
+            margin-bottom: 5px;
+            font-weight: bold;
+        }
+        .cloth-len-select select {
+            width: 100%;
+            padding: 8px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            font-size: 14px;
+        }
     </style>
 </head>
 <body>
@@ -96,11 +121,42 @@
             <input type="file" id="clothInput" accept="image/*">
             <img id="clothPreview" class="image-preview" alt="衣服图片预览">
         </div>
-        <div class="option-box">
+    </div>
+
+    <div class="image-upload-container">
+        <div class="image-upload-box">
+            <h3>裤子图片</h3>
+            <input type="file" id="kuziInput" accept="image/*">
+            <img id="kuziPreview" class="image-preview" alt="裤子图片预览">
+        </div>
+        
+        <div class="cloth-len-select">
+            <label for="clothLenSelect">选择服装长度：</label>
+            <select id="clothLenSelect">
+                <option value="胸">胸</option>
+                <option value="腰">腰</option>
+                <option value="跨">跨</option>
+                <option value="大腿">大腿</option>
+                <option value="膝盖">膝盖</option>
+                <option value="小腿">小腿</option>
+                <option value="脚踝">脚踝</option>
+                <option value="拖地">拖地</option>
+            </select>
+        </div>
+    </div>
+    
+    <div class="option-box">
         <label>
             <input type="checkbox" id="no2Checkbox"> 设置 no2 不要两步(一步完成)
         </label>
-    </div>
+        <br>
+        <label>
+            <input type="checkbox" id="tuodiCheckbox"> 设置 tuodi(拖地)
+        </label>
+        <br>
+        <label>
+            <input type="checkbox" id="suitCheckbox"> 设置 suit(套装)
+        </label>
     </div>
     
     <button id="submitBtn">提交处理</button>
@@ -140,11 +196,29 @@
             }
         });
 
+        document.getElementById('kuziInput').addEventListener('change', function(e) {
+            const file = e.target.files[0];
+            if (file) {
+                const reader = new FileReader();
+                reader.onload = function(event) {
+                    const img = document.getElementById('kuziPreview');
+                    img.src = event.target.result;
+                    img.style.display = 'block';
+                };
+                reader.readAsDataURL(file);
+            }
+        });
+        
         // 提交处理
         document.getElementById('submitBtn').addEventListener('click', function() {
             const humanFile = document.getElementById('humanInput').files[0];
             const clothFile = document.getElementById('clothInput').files[0];
+            const kuziFile = document.getElementById('kuziInput').files[0];
             const no2 = document.getElementById("no2Checkbox").checked;
+            const tuodi = document.getElementById("tuodiCheckbox").checked;
+            const suit = document.getElementById("suitCheckbox").checked;
+            const clothLen = document.getElementById("clothLenSelect").value;
+
             
             if (!humanFile || !clothFile) {
                 alert('请同时选择人体图片和衣服图片！');
@@ -158,20 +232,32 @@
             // 读取图片并转换为Base64（包含完整前缀）
             Promise.all([
                 readFileAsDataURL(humanFile),
-                readFileAsDataURL(clothFile)
+                readFileAsDataURL(clothFile),
-            ]).then(([humanDataURL, clothDataURL]) => {
+                kuziFile ? readFileAsDataURL(kuziFile) : Promise.resolve(null)
+            ]).then(([humanDataURL, clothDataURL, kuziDataURL]) => {
+
+
                 // 准备请求数据
                 const data = {
                     human_img: humanDataURL, // 包含完整前缀的Base64
                     cloth_img: clothDataURL, // 包含完整前缀的Base64
                     output_format: "url",
                     no2: no2,
+                    tuodi: tuodi,
+                    suit: suit,
+                    cloth_len: clothLen  // 新增的服装长度字段
                 };
 
+                if(kuziDataURL)
+                {
+                    data.kuzi_img = kuziDataURL;
+                }
+
+                
                 console.log("准备发送的数据:", data); // 调试用
                 
                 // 调用API
-                fetch('http://112.126.94.241:18888/change_cloth_base64', {
+                fetch('http://117.50.44.174:28888/change_cloth_base64', {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json'
@@ -198,6 +284,8 @@
                             <p><img src="${data.url}" style="max-width: 100%; margin-top: 10px;"></p>
                             <a href="${data.first_url}" target="_blank">${data.url}</a>
                             <p><img src="${data.first_url}" style="max-width: 100%; margin-top: 10px;"></p>
+                            <a href="${data.second_url}" target="_blank">${data.url}</a>
+                            <p><img src="${data.second_url}" style="max-width: 100%; margin-top: 10px;"></p>
                         `;
                     } else {
                         resultDiv.innerHTML = `

static/index_url.html

@@ -94,12 +94,12 @@
         
         <div class="input-group">
             <label for="human-url">人体图片URL:</label>
-            <input type="text" id="human-url" value="http://112.126.94.241:18888/static/imgs/human_20250713_091718_fb1f8a05.jpg">
+            <input type="text" id="human-url" value="http://117.50.44.174:18888/static/imgs/human_20250713_091718_fb1f8a05.jpg">
         </div>
         
         <div class="input-group">
             <label for="cloth-url">衣服图片URL:</label>
-            <input type="text" id="cloth-url" value="http://112.126.94.241:18888/static/imgs/cloth_20250713_092536_279335d2.jpg">
+            <input type="text" id="cloth-url" value="http://117.50.44.174:18888/static/imgs/cloth_20250713_092536_279335d2.jpg">
         </div>
         
         <button id="submit-btn">提交处理</button>
@@ -136,7 +136,7 @@
             
             try {
                 // 发送POST请求
-                const response = await fetch('http://112.126.94.241:18888/change_cloth', {
+                const response = await fetch('http://117.50.44.174:18888/change_cloth', {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json',

static/monitor.html

@@ -246,7 +246,7 @@
         // 获取服务器状态数据
         async function fetchServerStatus() {
             try {
-                const response = await fetch('http://112.126.94.241:18018/get_server_state');
+                const response = await fetch('http://117.50.44.174:18018/get_server_state');
                 if (!response.ok) throw new Error('网络响应不正常');
                 return await response.json();
             } catch (error) {

task_test.py

@@ -4,7 +4,7 @@ import json
 
 # 1. 提交任务
 
-with open('/home/szlc/code/ComfyUI/change_cloth/basic_api.json', 'r', encoding='utf-8') as file:
+with open('/home/xsl/code/ComfyUI/change_cloth/basic_api.json', 'r', encoding='utf-8') as file:
     prompt_text = file.read()
 
 prompt = json.loads(prompt_text)

test_change_cloth_http.py

@@ -27,13 +27,13 @@ def image_to_base64(file_path, mime_type=None):
     return f"data:{mime_type};base64,{encoded_string}"
 
 if __name__ == '__main__':
-    url = 'http://112.126.94.241:18018/change_cloth_base64'
+    url = 'http://117.50.44.174:18018/change_cloth_base64'
     headers = {'Content-Type': 'application/json'}
-    img64_human_str = image_to_base64("/home/szlc/code/ComfyUI/input/girl_full.jpg")
+    img64_human_str = image_to_base64("/home/xsl/code/ComfyUI/input/girl_full.jpg")
     data = {}
     data['human_img'] = img64_human_str
 
-    img64_cloth_str = image_to_base64("/home/szlc/code/ComfyUI/input/cloth_short.jpg")
+    img64_cloth_str = image_to_base64("/home/xsl/code/ComfyUI/input/cloth_short.jpg")
     data['cloth_img'] = img64_cloth_str
 
     data['output_format'] = "url"

worker.py

@@ -183,6 +183,8 @@ def call_remote_gpu_server(task_data_str, server=None):
                 "human_url": task_data['request']['human_url'],
                 "cloth_url": task_data['request']["cloth_url"],
                 "no2":task_data['request']['no2'],
+                "tuodi":task_data['request']['tuodi'],
+                "kuzi":task_data['request']['kuzi'],
                 "output_format":task_data['request']['output_format']
             }
         
@@ -307,7 +309,7 @@ def main_worker():
 serverindex = 0
 def regServer(instance, ip):
     global serverindex
-    registerGpuServer(f"s{serverindex}_1_{instance}", f"http://{ip}:8888", True)
+    registerGpuServer(f"s{serverindex}_1_{instance}", f"http://{ip}", True)
     serverindex += 1
 
 
@@ -316,7 +318,8 @@ if __name__ == '__main__':
     print(f"[Worker] Starting with PID: {os.getpid()}")
     redis_conn.set(GPU_SERVER_LIST, "[]")
 
-    regServer("一号", "192.168.101.118")
+    regServer("5090", "112.126.94.241:28888")
-    regServer("二号", "192.168.101.221")
+    # regServer("一号", "192.168.101.118:8888")
+    # regServer("二号", "192.168.101.221:8888")
 
     main_worker()

xiezhen-0811_bak_api.json

@@ -0,0 +1,345 @@
+{
+  "6": {
+    "inputs": {
+      "text": "asian girl,knee-length shot ,model pose,hands are at the sides of the body,smile,wearing black tube top and micro skirt,simple ,white background,32k,high detail,and face is illuminated by soft side light and natural light. The sunlight spills over the white wall behind.",
+      "clip": [
+        "68",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "10": {
+    "inputs": {
+      "vae_name": "ae.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "16": {
+    "inputs": {
+      "sampler_name": "dpmpp_2m"
+    },
+    "class_type": "KSamplerSelect",
+    "_meta": {
+      "title": "KSamplerSelect"
+    }
+  },
+  "17": {
+    "inputs": {
+      "scheduler": "sgm_uniform",
+      "steps": 30,
+      "denoise": 1,
+      "model": [
+        "63",
+        0
+      ]
+    },
+    "class_type": "BasicScheduler",
+    "_meta": {
+      "title": "BasicScheduler"
+    }
+  },
+  "25": {
+    "inputs": {
+      "noise_seed": 817211431292667
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "RandomNoise"
+    }
+  },
+  "26": {
+    "inputs": {
+      "guidance": 10,
+      "conditioning": [
+        "6",
+        0
+      ]
+    },
+    "class_type": "FluxGuidance",
+    "_meta": {
+      "title": "FluxGuidance"
+    }
+  },
+  "27": {
+    "inputs": {
+      "width": 768,
+      "height": 1024,
+      "batch_size": 1
+    },
+    "class_type": "EmptySD3LatentImage",
+    "_meta": {
+      "title": "EmptySD3LatentImage"
+    }
+  },
+  "45": {
+    "inputs": {
+      "pulid_file": "pulid_flux_v0.9.1.safetensors"
+    },
+    "class_type": "PulidFluxModelLoader",
+    "_meta": {
+      "title": "Load PuLID Flux Model"
+    }
+  },
+  "47": {
+    "inputs": {
+      "model": [
+        "62",
+        0
+      ],
+      "conditioning": [
+        "26",
+        0
+      ]
+    },
+    "class_type": "BasicGuider",
+    "_meta": {
+      "title": "BasicGuider"
+    }
+  },
+  "48": {
+    "inputs": {
+      "noise": [
+        "25",
+        0
+      ],
+      "guider": [
+        "47",
+        0
+      ],
+      "sampler": [
+        "16",
+        0
+      ],
+      "sigmas": [
+        "17",
+        0
+      ],
+      "latent_image": [
+        "27",
+        0
+      ]
+    },
+    "class_type": "SamplerCustomAdvanced",
+    "_meta": {
+      "title": "SamplerCustomAdvanced"
+    }
+  },
+  "49": {
+    "inputs": {
+      "samples": [
+        "48",
+        0
+      ],
+      "vae": [
+        "10",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "51": {
+    "inputs": {},
+    "class_type": "PulidFluxEvaClipLoader",
+    "_meta": {
+      "title": "Load Eva Clip (PuLID Flux)"
+    }
+  },
+  "53": {
+    "inputs": {
+      "provider": "CUDA"
+    },
+    "class_type": "PulidFluxInsightFaceLoader",
+    "_meta": {
+      "title": "Load InsightFace (PuLID Flux)"
+    }
+  },
+  "62": {
+    "inputs": {
+      "weight": 1.0000000000000002,
+      "start_at": 0,
+      "end_at": 1,
+      "model": [
+        "68",
+        0
+      ],
+      "pulid_flux": [
+        "45",
+        0
+      ],
+      "eva_clip": [
+        "51",
+        0
+      ],
+      "face_analysis": [
+        "53",
+        0
+      ],
+      "image": [
+        "93",
+        0
+      ]
+    },
+    "class_type": "ApplyPulidFlux",
+    "_meta": {
+      "title": "Apply PuLID Flux"
+    }
+  },
+  "63": {
+    "inputs": {
+      "unet_name": "flux1-dev-fp8.safetensors",
+      "weight_dtype": "fp8_e4m3fn"
+    },
+    "class_type": "UNETLoader",
+    "_meta": {
+      "title": "Load Diffusion Model"
+    }
+  },
+  "64": {
+    "inputs": {
+      "clip_name1": "flux/t5xxl_fp16.safetensors",
+      "clip_name2": "ViT-L-14-TEXT-detail-improved-hiT-GmP-HF.safetensors",
+      "type": "flux",
+      "device": "default"
+    },
+    "class_type": "DualCLIPLoader",
+    "_meta": {
+      "title": "DualCLIPLoader"
+    }
+  },
+  "65": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "68": {
+    "inputs": {
+      "PowerLoraLoaderHeaderWidget": {
+        "type": "PowerLoraLoaderHeaderWidget"
+      },
+      "➕ Add Lora": "",
+      "model": [
+        "63",
+        0
+      ],
+      "clip": [
+        "64",
+        0
+      ]
+    },
+    "class_type": "Power Lora Loader (rgthree)",
+    "_meta": {
+      "title": "Power Lora Loader (rgthree)"
+    }
+  },
+  "86": {
+    "inputs": {
+      "anything": [
+        "17",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "87": {
+    "inputs": {
+      "anything": [
+        "68",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "88": {
+    "inputs": {
+      "anything": [
+        "62",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "89": {
+    "inputs": {
+      "anything": [
+        "47",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "90": {
+    "inputs": {
+      "anything": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "91": {
+    "inputs": {
+      "anything": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "92": {
+    "inputs": {
+      "anything": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "easy clearCacheAll",
+    "_meta": {
+      "title": "Clear Cache All"
+    }
+  },
+  "93": {
+    "inputs": {
+      "image": "qwerqwe.jpg"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  }
+}

xiezhen-0812-40s_api.json

@@ -0,0 +1,354 @@
+{
+  "6": {
+    "inputs": {
+      "text": "asian man,tall,knee-length shot,model pose,hands are at the sides of the body,smile,wearing black short pants,simple white background,The sunlight spills over the white wall behind,32k,",
+      "clip": [
+        "68",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "10": {
+    "inputs": {
+      "vae_name": "ae.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "16": {
+    "inputs": {
+      "sampler_name": "dpmpp_2m"
+    },
+    "class_type": "KSamplerSelect",
+    "_meta": {
+      "title": "KSamplerSelect"
+    }
+  },
+  "17": {
+    "inputs": {
+      "scheduler": "sgm_uniform",
+      "steps": 30,
+      "denoise": 1,
+      "model": [
+        "63",
+        0
+      ]
+    },
+    "class_type": "BasicScheduler",
+    "_meta": {
+      "title": "BasicScheduler"
+    }
+  },
+  "25": {
+    "inputs": {
+      "noise_seed": 307959081040868
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "RandomNoise"
+    }
+  },
+  "26": {
+    "inputs": {
+      "guidance": 10,
+      "conditioning": [
+        "6",
+        0
+      ]
+    },
+    "class_type": "FluxGuidance",
+    "_meta": {
+      "title": "FluxGuidance"
+    }
+  },
+  "27": {
+    "inputs": {
+      "width": 768,
+      "height": 1024,
+      "batch_size": 1
+    },
+    "class_type": "EmptySD3LatentImage",
+    "_meta": {
+      "title": "EmptySD3LatentImage"
+    }
+  },
+  "45": {
+    "inputs": {
+      "pulid_file": "pulid_flux_v0.9.1.safetensors"
+    },
+    "class_type": "PulidFluxModelLoader",
+    "_meta": {
+      "title": "Load PuLID Flux Model"
+    }
+  },
+  "47": {
+    "inputs": {
+      "model": [
+        "62",
+        0
+      ],
+      "conditioning": [
+        "26",
+        0
+      ]
+    },
+    "class_type": "BasicGuider",
+    "_meta": {
+      "title": "BasicGuider"
+    }
+  },
+  "48": {
+    "inputs": {
+      "noise": [
+        "25",
+        0
+      ],
+      "guider": [
+        "47",
+        0
+      ],
+      "sampler": [
+        "16",
+        0
+      ],
+      "sigmas": [
+        "17",
+        0
+      ],
+      "latent_image": [
+        "27",
+        0
+      ]
+    },
+    "class_type": "SamplerCustomAdvanced",
+    "_meta": {
+      "title": "SamplerCustomAdvanced"
+    }
+  },
+  "49": {
+    "inputs": {
+      "samples": [
+        "48",
+        0
+      ],
+      "vae": [
+        "10",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "51": {
+    "inputs": {},
+    "class_type": "PulidFluxEvaClipLoader",
+    "_meta": {
+      "title": "Load Eva Clip (PuLID Flux)"
+    }
+  },
+  "53": {
+    "inputs": {
+      "provider": "CUDA"
+    },
+    "class_type": "PulidFluxInsightFaceLoader",
+    "_meta": {
+      "title": "Load InsightFace (PuLID Flux)"
+    }
+  },
+  "62": {
+    "inputs": {
+      "weight": 1.0000000000000002,
+      "start_at": 0,
+      "end_at": 1,
+      "model": [
+        "68",
+        0
+      ],
+      "pulid_flux": [
+        "45",
+        0
+      ],
+      "eva_clip": [
+        "51",
+        0
+      ],
+      "face_analysis": [
+        "53",
+        0
+      ],
+      "image": [
+        "93",
+        0
+      ]
+    },
+    "class_type": "ApplyPulidFlux",
+    "_meta": {
+      "title": "Apply PuLID Flux"
+    }
+  },
+  "63": {
+    "inputs": {
+      "unet_name": "flux1-dev-fp8.safetensors",
+      "weight_dtype": "fp8_e4m3fn"
+    },
+    "class_type": "UNETLoader",
+    "_meta": {
+      "title": "Load Diffusion Model"
+    }
+  },
+  "64": {
+    "inputs": {
+      "clip_name1": "flux/t5xxl_fp16.safetensors",
+      "clip_name2": "ViT-L-14-TEXT-detail-improved-hiT-GmP-HF.safetensors",
+      "type": "flux",
+      "device": "default"
+    },
+    "class_type": "DualCLIPLoader",
+    "_meta": {
+      "title": "DualCLIPLoader"
+    }
+  },
+  "65": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "68": {
+    "inputs": {
+      "PowerLoraLoaderHeaderWidget": {
+        "type": "PowerLoraLoaderHeaderWidget"
+      },
+      "➕ Add Lora": "",
+      "model": [
+        "63",
+        0
+      ],
+      "clip": [
+        "64",
+        0
+      ]
+    },
+    "class_type": "Power Lora Loader (rgthree)",
+    "_meta": {
+      "title": "Power Lora Loader (rgthree)"
+    }
+  },
+  "86": {
+    "inputs": {
+      "anything": [
+        "17",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "87": {
+    "inputs": {
+      "anything": [
+        "68",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "88": {
+    "inputs": {
+      "anything": [
+        "62",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "89": {
+    "inputs": {
+      "anything": [
+        "47",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "90": {
+    "inputs": {
+      "anything": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "91": {
+    "inputs": {
+      "anything": [
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+        0
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+    },
+    "class_type": "easy cleanGpuUsed",
+    "_meta": {
+      "title": "Clean VRAM Used"
+    }
+  },
+  "92": {
+    "inputs": {
+      "anything": [
+        "49",
+        0
+      ]
+    },
+    "class_type": "easy clearCacheAll",
+    "_meta": {
+      "title": "Clear Cache All"
+    }
+  },
+  "93": {
+    "inputs": {
+      "image": "微信图片_20250813204256_128.jpg"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
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+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  }
+}