save code

basic_api_example.py

@@ -26,7 +26,7 @@ def queue_prompt(prompt):
     request.urlopen(req)
 
 
-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)

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 +14,10 @@ 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
 
 
 APP_ROOT = os.path.dirname(os.path.abspath(__file__))
@@ -123,12 +126,12 @@ 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 +143,10 @@ 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.jpg'
     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 +185,12 @@ 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)
@@ -195,9 +199,9 @@ def generate_from_face(human_name, sex_girl):
     prompt["93"]["inputs"]["image"] = human_name
 
     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,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,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,wearing black short pants,simple white background,The sunlight spills over the white wall behind,32k."
 
     #out put name
     out_img_name = str(uuid.uuid4())[:8]
@@ -256,16 +260,16 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
         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 >= 0.55:
-        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
@@ -274,16 +278,16 @@ 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')
+    print(f'开始换衣服 {change_only_name}')
-    with open('/home/szlc/code/ComfyUI/change_cloth/change_new.json', 'r', encoding='utf-8') as file:
+    with open(f'{APP_ROOT}/{change_only_name}', 'r', encoding='utf-8') as file:
         prompt_text = file.read()
 
     prompt = json.loads(prompt_text)
@@ -311,8 +315,75 @@ def change(human_name, cloth_name, c_width, c_height, cloth_url, human_url, no2)
     prompt_id = response.json()["prompt_id"]
 
 
-    # 2. 轮询队列，直到任务完成
+    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)
+
     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"]:
@@ -360,13 +431,13 @@ 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))
@@ -439,7 +510,7 @@ def upload_to_oss(image_path, object_name=None):
 
 
 def process_change_cloth(human_filename, cloth_filename, output_format, img_url, human_url, no2):
-    w,h = get_image_dimensions(f'/home/szlc/code/ComfyUI/input/{human_filename}') 
+    w,h = get_image_dimensions(f'{APP_ROOT}/../input/{human_filename}') 
 
     out_put_name, out_human_name, is_girl,  msg = change(human_filename, cloth_filename, w, h, img_url, human_url, no2)
     if out_put_name == None:
@@ -449,19 +520,19 @@ 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}')
+        out_human_image = Image.open(f'{APP_ROOT}/../output/{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}'
         print(f"生成的第一步图片 HTTPS URL: {out_human_https_url}")
 
     
-    image = Image.open(f'/home/szlc/code/ComfyUI/output/{out_put_name}')
+    image = Image.open(f'{APP_ROOT}/../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
@@ -510,13 +581,13 @@ 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
@@ -556,7 +627,9 @@ def do_change_cloth():
 
     try:
         return process_change_cloth(human_filename, cloth_filename, output_format, cloth_url, human_url, no2)
-    except:
+    except Exception as e:
+        traceback.print_exc()
+        print(f"错误详情：{e}")
         return jsonify({
             "ret":-1,
             "state": -1,
@@ -655,7 +728,7 @@ 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://112.126.94.241:{base64_test_port}/static/imgs/{human_filename}"
 
     # 保存服装图片
     cloth_filename = save_base64_image(cloth_img, 'cloth')
@@ -663,7 +736,7 @@ 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://112.126.94.241:{base64_test_port}/static/imgs/{cloth_filename}"
 
     data["human_url"] = human_url
     data["cloth_url"] = cloth_url
@@ -672,7 +745,20 @@ def change_cloth_base64():
     if not no2:
         data['no2'] = False
 
-    return queueCall(data)
+    # 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://112.126.94.241:{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__':

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 @@
   "96": {
     "inputs": {
       "cloth_len": "小腿",
-      "line_len": 0.6000000000000001,
+      "line_len": 0.4,
       "cloth_short": true,
       "kps": [
         "95",
@@ -819,7 +819,7 @@
   },
   "110": {
     "inputs": {
-      "preview": "1180672",
+      "preview": "855040",
       "source": [
         "106",
         0
@@ -832,7 +832,7 @@
   },
   "111": {
     "inputs": {
-      "preview": "768",
+      "preview": "522",
       "source": [
         "108",
         0
@@ -858,7 +858,7 @@
   },
   "113": {
     "inputs": {
-      "preview": "1793",
+      "preview": "1547",
       "source": [
         "107",
         0
@@ -975,7 +975,7 @@
   "71:2": {
     "inputs": {
       "prompt": "cloth",
-      "threshold": 0.3,
+      "threshold": 0.30000000000000004,
       "sam_model": [
         "71:0",
         0

change_new_3090.json

@@ -0,0 +1,961 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 133974548609577,
+      "steps": 20,
+      "cfg": 1,
+      "sampler_name": "euler",
+      "scheduler": "simple",
+      "denoise": 1,
+      "model": [
+        "13",
+        0
+      ],
+      "positive": [
+        "17",
+        0
+      ],
+      "negative": [
+        "17",
+        1
+      ],
+      "latent_image": [
+        "17",
+        2
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "KSampler"
+    }
+  },
+  "6": {
+    "inputs": {
+      "text": "",
+      "clip": [
+        "12",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": "",
+      "clip": [
+        "12",
+        0
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "3",
+        0
+      ],
+      "vae": [
+        "16",
+        0
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE Decode"
+    }
+  },
+  "10": {
+    "inputs": {
+      "strength": 1.0000000000000002,
+      "strength_type": "multiply",
+      "conditioning": [
+        "11",
+        0
+      ],
+      "style_model": [
+        "79",
+        0
+      ],
+      "clip_vision_output": [
+        "20",
+        0
+      ]
+    },
+    "class_type": "StyleModelApply",
+    "_meta": {
+      "title": "Apply Style Model"
+    }
+  },
+  "11": {
+    "inputs": {
+      "guidance": 30,
+      "conditioning": [
+        "6",
+        0
+      ]
+    },
+    "class_type": "FluxGuidance",
+    "_meta": {
+      "title": "FluxGuidance"
+    }
+  },
+  "12": {
+    "inputs": {
+      "clip_name1": "flux/t5xxl_fp16.safetensors",
+      "clip_name2": "clip_l.safetensors",
+      "type": "flux",
+      "device": "default"
+    },
+    "class_type": "DualCLIPLoader",
+    "_meta": {
+      "title": "DualCLIPLoader"
+    }
+  },
+  "13": {
+    "inputs": {
+      "model": [
+        "75",
+        0
+      ]
+    },
+    "class_type": "DifferentialDiffusion",
+    "_meta": {
+      "title": "Differential Diffusion"
+    }
+  },
+  "16": {
+    "inputs": {
+      "vae_name": "ae.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "Load VAE"
+    }
+  },
+  "17": {
+    "inputs": {
+      "noise_mask": false,
+      "positive": [
+        "10",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "vae": [
+        "16",
+        0
+      ],
+      "pixels": [
+        "27",
+        1
+      ],
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+}

change_new_debug.json

@@ -0,0 +1,961 @@
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+}

change_new_only_change.json

@@ -0,0 +1,908 @@
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+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "🔧 Image Resize"
+    }
+  },
+  "26": {
+    "inputs": {
+      "width": [
+        "94",
+        0
+      ],
+      "height": [
+        "94",
+        0
+      ],
+      "interpolation": "nearest",
+      "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": "nearest",
+      "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,
+      "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"
+    }
+  }
+}

check_img_body.py

@@ -36,4 +36,4 @@ 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 = '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_only_name = "change_new_only_change.json"
+    # change_with_add_cloth = "change_new_debug.json"
+    change_with_add_cloth = change_only_name
+    xiezhen_name = "xiezhen-0812-40s_api.json"
+    base64_test_port = 28888
+else:
+    change_only_name = "change_new_only_3090.json"
+    # change_with_add_cloth = "change_new_3090.json"
+    change_with_add_cloth = change_only_name
+    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))
@@ -286,16 +286,16 @@ 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)
 
 
@@ -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

oss_test.py

@@ -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'
 print(f"生成的HTTPS URL: {https_url}")

static/index.html

@@ -171,7 +171,7 @@
                 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://112.126.94.241:28888/change_cloth_base64', {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json'

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

@@ -29,11 +29,11 @@ def image_to_base64(file_path, mime_type=None):
 if __name__ == '__main__':
     url = 'http://112.126.94.241:18018/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

@@ -307,7 +307,7 @@ 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 +316,8 @@ 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": [
+        "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": "微信图片_20250813204256_128.jpg"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  },
+  "94": {
+    "inputs": {
+      "text": "sian 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."
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  }
+}