大家好，我是超哥。今天给大家分享 Qwen-Image-2.1 图片 AI 模型的本地部署教程。它集文生图和图像编辑于一体，除了高质量图片生成，还支持多图编辑、涂抹编辑、圈选编辑、Mask 编辑、透明 PNG 生成以及主体提取等功能。接下来我会带大家一步步完成模型的本地部署，并搭建网页操作界面，让我们可以直接在浏览器中使用 Qwen-Image-2.1。下面我们开始教程。

提示：官方版就是无审查版，经过测试，可以生成任何图片（包括老司机图片），完全无审查、无限制！

博主电脑环境

显卡：NVIDIA RTX 4080 SUPER（16GB）

CPU：AMD R9 7900X 12-Core Processor（12核）

内存：64GB（3600 MHz）

Qwen-Image-2.1官方介绍：https://qwen.ai/blog?id=qwen-image-2.1

Qwen-Image-2.1 Hugging Face：https://huggingface.co/Qwen/Qwen-Image-2.1

Qwen-Image-2.1 ModelScope：https://modelscope.cn/models/Qwen/Qwen-Image-2.1

一、安装基础环境

1. 安装python

下载地址：https://www.python.org/downloads/release/python-3120/

直达下载：https://www.python.org/ftp/python/3.12.0/python-3.12.0-amd64.exe

验证python是否安装成功，cmd里执行下面代码：

python --version

2. 安装git

下载地址：https://git-scm.com/install/windows

直达下载：https://github.com/git-for-windows/git/releases/download/v2.55.0.windows.5/Git-2.55.0.5-64-bit.exe

验证git是否安装成功，cmd里执行下面代码：

git --version

二、安装虚拟环境

1. 创建模型目录

在D盘创建目录：ImageAI，创建后路径 D:\ImageAI

2. 创建虚拟空间

cmd进入 D:\ImageAI，执行下面命令，创建虚拟空间：

python -m venv qwen-env

输入下面命令，激活虚拟空间：

qwen-env\Scripts\activate

3. 升级 pip

升级 pip 命令：

python -m pip install --upgrade pip

4. 安装 CUDA 版 PyTorch

安装命令：

python -m pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128

检测命令：

python -c "import torch; print('CUDA:', torch.cuda.is_available()); print('CUDA版本:', torch.version.cuda); print('GPU:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else '未检测到GPU')"

检测需要出现类似下面文字（一个人一个样）：

CUDA: True

CUDA版本: 12.8

GPU: NVIDIA GeForce RTX 4080 SUPER

5. 安装DiffSynth-Studio

下载DiffSynth-Studio命令：

git clone https://github.com/modelscope/DiffSynth-Studio.git

进入DiffSynth-Studio命令：

cd DiffSynth-Studio

安装DiffSynth-Studio命令：

python -m pip install -e .

三、下载 Qwen-Image-2.1 模型

方法一、网盘下载地址

夸克网盘下载地址：https://pan.quark.cn/s/511153d60404?pwd=NrHP

迅雷网盘下载地址：https://pan.xunlei.com/s/VP22MdTbK3yTp1EiNLs1ewUrA1?pwd=n4uv

方法二、命令下载

1. cmd 进入 D:\ImageAI 目录

2. 执行激活虚拟空间命令

qwen-env\Scripts\activate

3. 创建模型目录

执行命令：

mkdir Qwen-Image-2.1

4. 安装 Hugging Face

安装命令：

python -m pip install -U huggingface_hub

5. Qwen-Image-2.1 模型下载

下载命令：

hf download Qwen/Qwen-Image-2.1 --local-dir D:\ImageAI\Qwen-Image-2.1

6. 安装 Windows 版 Triton

安装命令：

python -m pip install -U "triton-windows<3.7"

四、DiffSynth-Studio 根目录配置启动文件

方法1. 网盘下载文件

夸克网盘下载地址：https://pan.quark.cn/s/098a8d060590?pwd=AtEw

迅雷网盘下载地址：https://pan.xunlei.com/s/VP22CF0F-8hO8njvl5JJExAZA1?pwd=d9wt

方法2. 手动创建文件

1. DiffSynth-Studio 目录创建模型启动文件：web_ui.py

import os
import glob
import json
import random
import threading
import webbrowser
import base64
import io

from PIL import Image
from datetime import datetime
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from urllib.parse import urlparse

import torch

os.environ["DIFFSYNTH_SKIP_DOWNLOAD"] = "True"

from diffsynth.pipelines.qwen_image_21 import QwenImage21Pipeline, ModelConfig


# ========================================
# 基本设置
# ========================================

MODEL_PATH = r"..\Qwen-Image-2.1"
OUTPUT_DIR = os.path.join(MODEL_PATH, "output")

HOST = "127.0.0.1"
PORT = 7860

os.makedirs(OUTPUT_DIR, exist_ok=True)


# ========================================
# 网页进度状态
# ========================================

last_generated_filename = ""

progress_state = {
    "active": False,
    "step": 0,
    "total": 0,
    "status": "等待生成",
    "error": ""
}


def web_progress_bar(iterable):
    total = len(iterable)
    progress_state["active"] = True
    progress_state["step"] = 0
    progress_state["total"] = total
    progress_state["status"] = "正在生成图片……"
    progress_state["error"] = ""

    for index, item in enumerate(iterable, 1):
        progress_state["step"] = index
        yield item


# ========================================
# 加载模型
# ========================================

vram_config = {
    "offload_dtype": "disk",
    "offload_device": "disk",
    "onload_dtype": "disk",
    "onload_device": "disk",
    "preparing_dtype": torch.bfloat16,
    "preparing_device": "cuda",
    "computation_dtype": torch.bfloat16,
    "computation_device": "cuda",
}


print()
print("========================================")
print("      Qwen-Image-2.1 Web UI")
print("========================================")
print()
print("正在加载 Qwen-Image-2.1，请稍候...")
print()


pipe = QwenImage21Pipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",

    model_configs=[
        ModelConfig(
            path=glob.glob(
                os.path.join(
                    MODEL_PATH,
                    "transformer",
                    "diffusion_pytorch_model*.safetensors"
                )
            ),
            **vram_config
        ),

        ModelConfig(
            path=glob.glob(
                os.path.join(
                    MODEL_PATH,
                    "text_encoder",
                    "model*.safetensors"
                )
            ),
            **vram_config
        ),

        ModelConfig(
            path=glob.glob(
                os.path.join(
                    MODEL_PATH,
                    "vae",
                    "diffusion_pytorch_model*.safetensors"
                )
            ),
            **vram_config
        ),
    ],

    processor_config=ModelConfig(
        path=os.path.join(MODEL_PATH, "processor")
    ),

    vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)


print()
print("Qwen-Image-2.1 加载完成！")
print()


# 如果服务器重启，自动把最近一次 PNG 作为“继续创作”的上一张图片
try:
    _existing_outputs = sorted(
        [x for x in os.listdir(OUTPUT_DIR) if x.lower().endswith(".png")],
        reverse=True
    )
    if _existing_outputs:
        last_generated_filename = _existing_outputs[0]
except Exception:
    pass


# ========================================
# HTML 页面
# ========================================

HTML = r"""

""" # ======================================== # HTTP Server # ======================================== class WebHandler(BaseHTTPRequestHandler): def send_text(self, content, status=200, content_type="text/html; charset=utf-8"): data = content.encode("utf-8") self.send_response(status) self.send_header( "Content-Type", content_type ) self.send_header( "Content-Length", str(len(data)) ) self.end_headers() self.wfile.write(data) def do_GET(self): path = urlparse(self.path).path if path == "/": self.send_text(HTML) return if path == "/progress": self.send_text( json.dumps( progress_state, ensure_ascii=False ), 200, "application/json; charset=utf-8" ) return if path == "/history": files = [] try: files = sorted( [x for x in os.listdir(OUTPUT_DIR) if x.lower().endswith(".png")], reverse=True )[:24] except Exception: files = [] self.send_text( json.dumps({"items": files}, ensure_ascii=False), 200, "application/json; charset=utf-8" ) return if path.startswith("/output/"): filename = os.path.basename(path) filepath = os.path.join( OUTPUT_DIR, filename ) if not os.path.isfile(filepath): self.send_response(404) self.end_headers() return with open(filepath, "rb") as f: data = f.read() self.send_response(200) self.send_header( "Content-Type", "image/png" ) self.send_header( "Content-Length", str(len(data)) ) self.end_headers() self.wfile.write(data) return self.send_response(404) self.end_headers() def do_POST(self): global last_generated_filename path = urlparse(self.path).path if path == "/open_folder": try: length = int(self.headers.get("Content-Length", 0)) body = self.rfile.read(length) data = json.loads(body.decode("utf-8")) filename = os.path.basename( str(data.get("filename", "")) ) if not filename: raise ValueError("图片文件名不能为空") filepath = os.path.join( OUTPUT_DIR, filename ) if not os.path.isfile(filepath): raise FileNotFoundError("图片文件不存在") os.startfile(os.path.dirname(filepath)) self.send_text( json.dumps( {"success": True}, ensure_ascii=False ), 200, "application/json; charset=utf-8" ) except Exception as e: self.send_text( json.dumps( { "success": False, "error": str(e) }, ensure_ascii=False ), 500, "application/json; charset=utf-8" ) return if path != "/generate": self.send_response(404) self.end_headers() return try: length = int(self.headers.get("Content-Length", 0)) body = self.rfile.read(length) data = json.loads(body.decode("utf-8")) # 每次新的生成请求到达后，立即重置服务器端进度状态。 # 这样第二次、第三次生成时，前端轮询不会先显示上一张的 100%。 progress_state["active"] = True progress_state["step"] = 0 progress_state["total"] = max(1, int(data.get("steps", 40))) progress_state["status"] = "正在准备模型……" progress_state["error"] = "" prompt = str(data.get("prompt", "")).strip() negative_prompt = str(data.get("negativePrompt", "")).strip() cfg_scale = float(data.get("cfgScale", 1.0)) tiled_vae = bool(data.get("tiledVae", False)) width = int(data.get("width", 1024)) height = int(data.get("height", 1024)) steps = int(data.get("steps", 40)) seed = int(data.get("seed", -1)) mode = str(data.get("mode", "text")) edit_type = str(data.get("editType", "multi")) task_type = str(data.get("taskType", "normal")) image_data = data.get("images", []) continue_from_last = bool(data.get("continueFromLast", False)) output_transparent = bool(data.get("outputTransparent", False)) if not isinstance(image_data, list): image_data = [] if not prompt: raise ValueError("提示词不能为空") if mode == "text" and task_type == "extract" and len(image_data) != 1: raise ValueError("抠图模式需要 1 张原图") if mode == "text" and task_type == "fidelity" and not 1 <= len(image_data) <= 10: raise ValueError("高保真模式需要 1～10 张参考图片") if mode == "edit" and edit_type == "multi" and not 1 <= len(image_data) <= 10: raise ValueError("多图编辑需要 1～10 张参考图片") if mode == "edit" and edit_type in ("paint", "mask") and len(image_data) != 2: raise ValueError("局部编辑需要原图和 Mask 两张图片") if mode == "edit" and edit_type == "circle" and len(image_data) != 1: raise ValueError("圈选编辑需要 1 张标注图片") if mode == "edit" and edit_type == "alpha" and len(image_data) != 1: raise ValueError("透明图编辑需要 1 张 RGBA 图片") edit_images = [] for item in image_data: if not isinstance(item, str) or "," not in item: raise ValueError("参考图片数据无效") encoded = item.split(",", 1)[1] try: image_bytes = base64.b64decode(encoded) image = Image.open(io.BytesIO(image_bytes)) image.load() edit_images.append(image.convert("RGBA")) except Exception as e: raise ValueError("参考图片无法读取") from e if mode == "text" and task_type == "continue": if not last_generated_filename or not os.path.isfile(os.path.join(OUTPUT_DIR, last_generated_filename)): raise ValueError("没有可继续创作的上一张图片") previous = Image.open(os.path.join(OUTPUT_DIR, last_generated_filename)).convert("RGBA") edit_images = [previous] if mode == "edit" and edit_type == "mask": if edit_images[0].size != edit_images[1].size: edit_images[1] = edit_images[1].resize(edit_images[0].size, Image.Resampling.NEAREST) mask_gray = edit_images[1].convert("L") mask_gray = mask_gray.point(lambda p: 255 if p >= 128 else 0) edit_images[1] = Image.merge("RGBA", (mask_gray, mask_gray, mask_gray, Image.new("L", mask_gray.size, 255))) if mode == "edit" and edit_type in ("paint", "mask") and output_transparent: transparent_alpha = edit_images[1].getchannel("R") else: transparent_alpha = None original_alpha = edit_images[0].getchannel("A") if mode == "edit" and edit_type == "alpha" else None if seed < 0: seed = random.randint(0, 2147483647) width = max(256, round(width / 32) * 32) height = max(256, round(height / 32) * 32) print() print("========================================") print("开始生成图片") print(f"提示词：{prompt}") print(f"尺寸：{width} × {height}") print(f"Steps：{steps}") print(f"Seed：{seed}") print(f"模式：{'图像编辑' if mode == 'edit' else '文生图'}") if mode == "edit": print(f"编辑方式：{edit_type}") print(f"参考图片：{len(edit_images)} 张") print("========================================") final_prompt = prompt if mode == "text": task_prefix = { "transparent": "这是一个需要原生 Alpha 通道的透明 PNG 素材。请直接生成 RGBA 图像，背景必须是真正透明，不要生成棋盘格、白色背景或纯色背景。", "extract": "请从输入照片中提取指定主体，生成真正带 Alpha 通道的 RGBA 透明图层。删除背景，不要用白色或棋盘格代替透明。", "panorama": "请以宽幅全景构图生成，保证左右空间连续、透视自然、细节完整。", "infographic": "请按照信息图/海报设计进行构图，重视信息层级、排版、图形和中文文字清晰度。", "storyboard": "请按照故事板/连续分镜方式组织画面，保持角色、服装和视觉风格连续。", "fidelity": "请高度保持参考图中人物或产品的身份特征、外观、材质和关键细节。", "continue": "请基于上一张图片继续创作，只按照下面的新要求修改，尽可能保持未要求修改的内容一致。" } if task_type in task_prefix: final_prompt = task_prefix[task_type] + "\n" + prompt if mode == "edit": image = pipe(prompt=final_prompt, negative_prompt=negative_prompt, cfg_scale=cfg_scale, edit_image=edit_images, width=width, height=height, seed=seed, num_inference_steps=steps, tiled=tiled_vae, progress_bar_cmd=web_progress_bar) elif task_type in ("extract", "fidelity", "continue"): image = pipe(prompt=final_prompt, negative_prompt=negative_prompt, cfg_scale=cfg_scale, edit_image=edit_images, width=width, height=height, seed=seed, num_inference_steps=steps, tiled=tiled_vae, progress_bar_cmd=web_progress_bar) else: image = pipe(prompt=final_prompt, negative_prompt=negative_prompt, cfg_scale=cfg_scale, width=width, height=height, seed=seed, num_inference_steps=steps, tiled=tiled_vae, progress_bar_cmd=web_progress_bar) image = image.convert("RGBA") if mode == "edit" and edit_type == "mask" and transparent_alpha is not None: alpha = transparent_alpha.resize(image.size, Image.Resampling.NEAREST) image.putalpha(alpha) filename = datetime.now().strftime("%Y%m%d_%H%M%S_%f") + ".png" filepath = os.path.join(OUTPUT_DIR, filename) image.save(filepath, "PNG") print(f"生成完成：{filepath}") last_generated_filename = filename progress_state["active"] = False progress_state["step"] = progress_state["total"] progress_state["status"] = "生成完成" progress_state["error"] = "" note = "生成完成！" if task_type == "transparent": note = "生成完成：已按原生 RGBA Alpha 通道保存透明 PNG。" if task_type == "extract": note = "生成完成：已从原图提取主体并保存为透明 RGBA PNG。" if task_type == "continue": note = "生成完成：已基于上一张图片继续创作。" if mode == "edit" and edit_type == "alpha": note = "生成完成：已使用透明 PNG 作为原生编辑输入，并保留 RGBA 输出。" if transparent_alpha is not None: note = "生成完成，已按 Mask 输出透明 PNG。" result = {"success":True,"image":"/output/" + filename,"width":width,"height":height,"steps":steps,"seed":seed,"note":note} self.send_text( json.dumps( result, ensure_ascii=False ), 200, "application/json; charset=utf-8" ) except Exception as e: progress_state["active"] = False progress_state["status"] = "生成失败" progress_state["error"] = str(e) print() print("生成失败：") print(e) result = { "success": False, "error": str(e) } self.send_text( json.dumps( result, ensure_ascii=False ), 500, "application/json; charset=utf-8" ) def log_message(self, format, *args): return # ======================================== # 启动服务器 # ======================================== def open_browser(): webbrowser.open( f"http://{HOST}:{PORT}" ) server = ThreadingHTTPServer( (HOST, PORT), WebHandler ) print() print("========================================") print("Web UI 已启动") print() print(f"http://{HOST}:{PORT}") print("========================================") print() print("按 Ctrl+C 可以停止服务器") print() threading.Timer( 1.5, open_browser ).start() try: server.serve_forever() except KeyboardInterrupt: print() print("正在关闭服务器……") server.shutdown()

2. DiffSynth-Studio 目录创建一键启动脚本：启动.bat

@echo off
title Qwen-Image-2.1 XCHAOGE
cd /d "%~dp0"
call ..\qwen-env\Scripts\activate.bat
python web_ui.py
pause