Update app.py

app.py

@@ -1,97 +1,20 @@
-import gradio as gr
-import os
-import sys
-import logging
-from PIL import Image
-import numpy as np
-import time
-import random
-import warnings
-import json
-
-# 设置环境变量解决 OpenMP 问题
-os.environ['OMP_NUM_THREADS'] = '1'
-os.environ['MKL_NUM_THREADS'] = '1'
-
-# 抑制警告
-warnings.filterwarnings("ignore")
-
-# 设置日志
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# 检查模型管理器是否存在
-try:
-    from models.model_manager import ModelManager
-    MODELS_AVAILABLE = True
-    logger.info("模型管理器导入成功")
-except ImportError as e:
-    logger.warning(f"模型管理器导入失败: {e}")
-    logger.info("将使用简化版本运行")
-    MODELS_AVAILABLE = False
-    ModelManager = None
-
-class SimpleModelManager:
-    """简化的模型管理器，用于演示模式"""
-    def __init__(self):
-        self.device = "cpu"
-        logger.info("使用简化模型管理器")
-    
-    def generate_caption(self, image):
-        return "这是一件时尚的服装设计，具有现代感和优雅的风格。"
-    
-    def analyze_style(self, image):
-        return {"时尚潮流": 0.8, "休闲风": 0.6, "优雅风": 0.4}
-    
-    def generate_image(self, prompt, **kwargs):
-        # 创建占位图像
-        width, height = kwargs.get('width', 512), kwargs.get('height', 512)
-        color = (random.randint(100, 255), random.randint(100, 255), random.randint(100, 255))
-        img = Image.new('RGB', (width, height), color=color)
-        return img
-    
-    def cleanup(self):
-        pass
-
-# 全局状态管理
-class AppState:
-    def __init__(self):
-        self.current_image = None
-        self.current_caption = ""
-        self.current_analysis = {}
-        self.current_suggestions = {}
-        self.design_images = []
-        self.selected_suggestion = ""
-        self.selected_design = ""
-
-# 初始化
-if MODELS_AVAILABLE:
-    try:
-        model_manager = ModelManager()
-        logger.info("使用完整模型管理器")
-    except Exception as e:
-        logger.error(f"初始化完整模型管理器失败: {e}")
-        model_manager = SimpleModelManager()
-else:
-    model_manager = SimpleModelManager()
-
-app_state = AppState()
+# ...（保留之前的导入和初始化代码）
 
 def upload_and_analyze(image_path, progress=gr.Progress()):
-    """完整的图片上传和分析流程"""
+    """完整的图片上传和分析流程 - 增强关联性"""
     try:
+        # 重置应用状态
+        app_state = AppState()
+        
         if image_path is None:
             return {}, {}, gr.Radio(choices=[]), gr.Gallery(value=[])
         
         progress(0.1, desc="加载图片...")
-        
-        # 打开并保存图片
         image = Image.open(image_path).convert('RGB')
         app_state.current_image = image
         
+        # 步骤1: 生成图像描述并保存
         progress(0.2, desc="生成图像描述...")
-        
-        # 步骤1: 使用模型生成图像描述
         try:
             caption = model_manager.generate_caption(image)
             app_state.current_caption = caption
@@ -101,29 +24,23 @@ def upload_and_analyze(image_path, progress=gr.Progress()):
             caption = "时尚服装设计"
             app_state.current_caption = caption
         
-        progress(0.4, desc="分析服装风格...")
-        
         # 步骤2: 使用CLIP模型分析风格
+        progress(0.4, desc="分析服装风格...")
         try:
-            if hasattr(model_manager, 'analyze_style'):
-                style_scores = model_manager.analyze_style(image)
-            else:
-                # 回退到基于描述的分析
-                style_scores = analyze_style_from_caption(caption)
+            style_scores = model_manager.analyze_style(image)
             logger.info(f"风格分析结果: {style_scores}")
         except Exception as e:
             logger.error(f"风格分析失败: {e}")
-            style_scores = {"时尚潮流": 0.8, "休闲风": 0.6}
-        
-        progress(0.6, desc="提取颜色信息...")
+            # 使用描述回退分析
+            style_scores = analyze_style_from_caption(caption)
         
         # 步骤3: 提取颜色信息
+        progress(0.6, desc="提取颜色信息...")
         colors = extract_dominant_colors(image)
         
+        # 步骤4: 整合分析结果 - 保存所有关键信息
         progress(0.8, desc="生成完整分析...")
-        
-        # 步骤4: 整合分析结果
-        analysis_result = {
+        app_state.current_analysis = {
             "图像描述": caption,
             "主要风格": max(style_scores.keys(), key=style_scores.get),
             "风格评分": style_scores,
@@ -132,239 +49,76 @@ def upload_and_analyze(image_path, progress=gr.Progress()):
             "分析时间": time.strftime("%Y-%m-%d %H:%M:%S")
         }
         
-        # 步骤5: 基于模型分析结果生成个性化建议
-        suggestions = generate_personalized_suggestions_v2(
+        # 步骤5: 基于所有分析结果生成个性化建议
+        app_state.current_suggestions = generate_personalized_suggestions_v2(
             caption, style_scores, colors
         )
         
-        # 保存状态
-        app_state.current_analysis = analysis_result
-        app_state.current_suggestions = suggestions
-        
         # 创建建议选项
-        choices = list(suggestions.keys())
+        choices = list(app_state.current_suggestions.keys())
         
         progress(1.0, desc="分析完成")
         
         return (
-            analysis_result, 
-            suggestions, 
+            app_state.current_analysis, 
+            app_state.current_suggestions, 
             gr.Radio(choices=choices, value=choices[0] if choices else None),
             gr.Gallery(value=[])  # 清空之前的设计
         )
         
     except Exception as e:
-        error_result = {"错误": f"分析失败: {str(e)}"}
         logger.error(f"上传分析失败: {e}")
-        return error_result, {}, gr.Radio(choices=[]), gr.Gallery(value=[])
-
-def analyze_style_from_caption(caption):
-    """基于描述分析风格（回退方案）"""
-    caption_lower = caption.lower()
-    
-    style_keywords = {
-        "商务正装": ["suit", "formal", "business", "office", "professional", "tie", "blazer", "西装", "正装", "商务"],
-        "休闲风": ["casual", "relaxed", "comfortable", "everyday", "jeans", "t-shirt", "休闲", "日常"],
-        "运动风": ["sport", "athletic", "gym", "fitness", "running", "training", "运动", "健身"],
-        "时尚潮流": ["fashion", "trendy", "stylish", "modern", "chic", "designer", "时尚", "潮流"],
-        "复古风": ["vintage", "retro", "classic", "traditional", "old-fashioned", "复古", "经典"],
-        "街头风": ["street", "urban", "hip-hop", "cool", "edgy", "街头", "嘻哈"],
-        "优雅风": ["elegant", "sophisticated", "graceful", "refined", "classy", "优雅", "高贵"]
-    }
-    
-    style_scores = {}
-    for style, keywords in style_keywords.items():
-        score = sum(0.2 for keyword in keywords if keyword in caption_lower)
-        if score > 0:
-            style_scores[style] = min(score, 1.0)
-    
-    # 如果没有匹配，给默认评分
-    if not style_scores:
-        style_scores = {"休闲风": 0.7, "时尚潮流": 0.5}
-    
-    return style_scores
-
-def extract_dominant_colors(image):
-    """提取图像主要颜色"""
-    try:
-        from sklearn.cluster import KMeans
-        
-        # 调整图像大小以提高处理速度
-        image = image.resize((150, 150))
-        
-        # 转换为numpy数组
-        img_array = np.array(image)
-        pixels = img_array.reshape(-1, 3)
-        
-        # 使用KMeans聚类找到主要颜色
-        kmeans = KMeans(n_clusters=3, random_state=42, n_init=10)
-        kmeans.fit(pixels)
-        
-        # 将RGB值转换为颜色名称
-        colors = []
-        for color in kmeans.cluster_centers_:
-            color_name = rgb_to_color_name(color)
-            colors.append(color_name)
-        
-        return colors
-    except Exception as e:
-        logger.error(f"颜色提取失败: {e}")
-        return ["主色调", "辅助色", "点缀色"]
-
-def rgb_to_color_name(rgb):
-    """将RGB值转换为颜色名称"""
-    try:
-        r, g, b = rgb.astype(int)
-        
-        if r > 200 and g > 200 and b > 200:
-            return "白色系"
-        elif r < 50 and g < 50 and b < 50:
-            return "黑色系"
-        elif r > g and r > b:
-            return "红色系" if r > 150 else "深红色系"
-        elif g > r and g > b:
-            return "绿色系" if g > 150 else "深绿色系"
-        elif b > r and b > g:
-            return "蓝色系" if b > 150 else "深蓝色系"
-        elif r > 150 and g > 150:
-            return "黄色系"
-        elif r > 100 and b > 100:
-            return "紫色系"
-        elif g > 100 and b > 100:
-            return "青色系"
-        else:
-            return "灰色系"
-    except:
-        return "混合色调"
-
-def generate_personalized_suggestions_v2(caption, style_scores, colors):
-    """基于模型分析结果生成个性化建议"""
-    try:
-        # 获取主要风格
-        main_style = max(style_scores.keys(), key=style_scores.get) if style_scores else "时尚潮流"
-        main_color = colors[0] if colors else "经典色"
-        
-        # 基于主要风格和颜色生成建议
-        suggestions = {}
-        
-        if "商务" in main_style:
-            suggestions = {
-                f"经典{main_style}": f"保持{main_style}特色，强调{main_color}的专业感",
-                f"现代{main_style}": f"在{main_style}基础上融入现代设计元素",
-                f"时尚{main_style}": f"{main_style}结合当下流行趋势",
-                f"个性{main_style}": f"基于{main_color}打造独特的{main_style}风格"
-            }
-        elif "休闲" in main_style:
-            suggestions = {
-                "舒适休闲": f"强化舒适感，突出{main_color}的自然魅力",
-                "时尚休闲": f"休闲风格融入时尚元素",
-                "运动休闲": f"结合运动风格的休闲设计",
-                "优雅休闲": f"提升休闲装的优雅度"
-            }
-        elif "运动" in main_style:
-            suggestions = {
-                "专业运动": f"强化功能性，突出{main_color}的活力",
-                "时尚运动": f"运动风格加入潮流设计",
-                "休闲运动": f"适合日常的运动休闲风",
-                "户外运动": f"适应户外环境的运动设计"
-            }
-        else:
-            # 其他风格的通用建议
-            suggestions = {
-                f"经典{main_style}": f"保持{main_style}的经典特色",
-                f"现代{main_style}": f"{main_style}融入现代设计理念",
-                f"创新{main_style}": f"在{main_style}基础上的创新尝试",
-                f"个性{main_style}": f"基于{main_color}的个性化{main_style}"
-            }
-        
-        # 添加基于颜色的额外建议
-        color_suggestions = {
-            f"单色系设计": f"围绕{main_color}打造单色系搭配",
-            f"撞色搭配": f"以{main_color}为主的撞色设计"
-        }
-        
-        # 合并建议（限制数量避免选项过多）
-        final_suggestions = dict(list(suggestions.items())[:4] + list(color_suggestions.items())[:2])
-        
-        return final_suggestions
-        
-    except Exception as e:
-        logger.error(f"生成建议失败: {e}")
-        return {
-            "经典设计": "传统经典的设计风格",
-            "现代风格": "融入现代设计元素",
-            "时尚潮流": "跟随当下时尚趋势",
-            "个性化": "独特的个性化设计"
-        }
+        return {"错误": f"分析失败: {str(e)}"}, {}, gr.Radio(choices=[]), gr.Gallery(value=[])
 
 def generate_designs(selected_suggestion, progress=gr.Progress()):
-    """根据选择的建议使用SD模型生成设计"""
+    """根据选择的建议使用SD模型生成设计 - 增强关联性"""
     try:
-        if not selected_suggestion:
+        if not selected_suggestion or not app_state.current_analysis:
             return gr.Gallery(value=[]), gr.Radio(choices=[])
         
         progress(0.1, desc="准备设计生成...")
-        
-        # 保存选择的建议
         app_state.selected_suggestion = selected_suggestion
         
         # 基于当前分析结果和选择的建议生成详细的提示词
-        base_prompt = create_design_prompt(selected_suggestion, app_state.current_analysis)
+        base_prompt = create_design_prompt(
+            selected_suggestion, 
+            app_state.current_analysis
+        )
         
         # 生成设计图像
         design_images = []
         design_choices = []
         
-        # 检查模型是否可用
-        if not hasattr(model_manager, 'sd_pipeline') or model_manager.sd_pipeline is None:
-            logger.error("无法生成设计：Stable Diffusion 模型未加载")
-            # 创建占位图像
-            for i in range(3):
-                color = (random.randint(120, 200), random.randint(120, 200), random.randint(120, 200))
-                img = Image.new('RGB', (512, 512), color=color)
-                design_images.append(img)
-                design_choices.append(f"{selected_suggestion} - 方案 {i+1} (模型未加载)")
-            
-            return (
-                gr.Gallery(value=design_images), 
-                gr.Radio(choices=design_choices, value=design_choices[0] if design_choices else None)
-            )
-        
         for i in range(3):  # 生成3个设计方案
             try:
                 progress(0.2 + i*0.25, desc=f"生成设计方案 {i+1}/3...")
                 
-                # 为每个设计添加变化
-                variant_prompt = f"{base_prompt}, design variation {i+1}, unique style, high quality fashion design"
+                # 为每个设计添加变化，同时包含原始描述和风格信息
+                variant_prompt = (
+                    f"{base_prompt}, design variation {i+1}, "
+                    f"inspired by: '{app_state.current_caption}', "
+                    f"style: {app_state.current_analysis['主要风格']}, "
+                    f"colors: {', '.join(app_state.current_analysis['主要颜色'][:2])}"
+                )
                 
-                # 使用模型生成图像 - 添加错误处理
-                try:
-                    image = model_manager.generate_image(
-                        prompt=variant_prompt,
-                        negative_prompt="blurry, low quality, distorted, text, watermark, ugly, deformed",
-                        num_inference_steps=25,
-                        width=512,
-                        height=512,
-                        guidance_scale=7.5
-                    )
-                except Exception as gen_e:
-                    logger.error(f"生成设计 {i+1} 失败: {gen_e}")
-                    # 创建占位图像
-                    width, height = 512, 512
-                    color = (random.randint(120, 200), random.randint(120, 200), random.randint(120, 200))
-                    image = Image.new('RGB', (width, height), color=color)
+                # 使用模型生成图像
+                image = model_manager.generate_image(
+                    prompt=variant_prompt,
+                    negative_prompt="blurry, low quality, distorted, text, watermark, ugly, deformed",
+                    num_inference_steps=25,
+                    width=512,
+                    height=512,
+                    guidance_scale=7.5
+                )
                 
-                if image:
-                    design_images.append(image)
-                    design_choices.append(f"{selected_suggestion} - 方案 {i+1}")
-                    logger.info(f"成功生成设计方案 {i+1}")
+                design_images.append(image)
+                design_choices.append(f"{selected_suggestion} - 方案 {i+1}")
+                logger.info(f"成功生成设计方案 {i+1}")
                     
             except Exception as e:
                 logger.error(f"生成设计 {i+1} 失败: {e}")
                 # 创建占位图像
-                width, height = 512, 512
-                color = (random.randint(120, 200), random.randint(120, 200), random.randint(120, 200))
-                img = Image.new('RGB', (width, height), color=color)
+                img = create_placeholder_image(512, 512)
                 design_images.append(img)
                 design_choices.append(f"{selected_suggestion} - 方案 {i+1} (占位)")
         
@@ -382,76 +136,34 @@ def generate_designs(selected_suggestion, progress=gr.Progress()):
         logger.error(f"设计生成错误: {e}")
         return gr.Gallery(value=[]), gr.Radio(choices=[])
 
-def create_design_prompt(suggestion, analysis):
-    """基于建议和分析创建详细的设计提示词"""
-    try:
-        # 从分析中提取关键信息
-        style_info = analysis.get("主要风格", "时尚")
-        colors = analysis.get("主要颜色", ["现代色"])
-        description = analysis.get("图像描述", "")
-        
-        # 基础提示词映射
-        style_prompts = {
-            "商务正装": "professional business attire, formal suit, clean lines, sophisticated",
-            "休闲风": "casual clothing, comfortable style, everyday wear, relaxed fit",
-            "运动风": "sportswear, athletic clothing, functional design, activewear",
-            "时尚潮流": "trendy fashion, stylish clothing, contemporary design, fashionable",
-            "复古风": "vintage style, retro fashion, classic design, nostalgic elements",
-            "街头风": "streetwear, urban fashion, casual street style, modern youth",
-            "优雅风": "elegant clothing, sophisticated style, refined fashion, graceful design"
-        }
-        
-        # 获取风格对应的提示词
-        style_prompt = style_prompts.get(style_info, "stylish clothing, modern design")
-        
-        # 颜色相关的提示词
-        color_prompt = f"color palette inspired by {colors[0] if colors else 'modern colors'}"
-        
-        # 根据建议调整提示词
-        if "经典" in suggestion:
-            modifier = "timeless, classic design, traditional elements"
-        elif "现代" in suggestion:
-            modifier = "contemporary, modern aesthetic, innovative design"
-        elif "时尚" in suggestion:
-            modifier = "fashion-forward, trendy, runway-inspired"
-        elif "个性" in suggestion:
-            modifier = "unique, personalized, distinctive style"
-        else:
-            modifier = "high-quality, well-designed, stylish"
-        
-        # 组合完整的提示词
-        full_prompt = f"{style_prompt}, {color_prompt}, {modifier}, high detail, professional fashion photography, studio lighting"
-        
-        logger.info(f"生成的设计提示词: {full_prompt}")
-        return full_prompt
-        
-    except Exception as e:
-        logger.error(f"创建提示词失败: {e}")
-        return "stylish clothing design, high quality, professional fashion"
-
-def generate_3d_fitting(selected_design, progress=gr.Progress()):
-    """生成3D试穿效果"""
+def generate_3d_fitting(selected_design_index, progress=gr.Progress()):
+    """生成3D试穿效果 - 增强关联性"""
     try:
-        if not selected_design:
+        if not app_state.design_images or not app_state.current_image:
             return None
         
         progress(0.1, desc="准备3D试穿...")
         
-        # 保存选择的设计
-        app_state.selected_design = selected_design
+        # 获取选中的设计
+        selected_image = app_state.design_images[selected_design_index]
+        app_state.selected_design = selected_design_index
         
-        # 基于选择的设计和原始分析创��3D试穿提示词
-        fitting_prompt = create_3d_fitting_prompt(selected_design, app_state.current_analysis)
+        # 基于原始图像和选择的设计创建3D试穿提示词
+        fitting_prompt = create_3d_fitting_prompt(
+            selected_design_index, 
+            app_state.current_analysis
+        )
         
         progress(0.3, desc="生成3D模型...")
         
-        # 尝试使用ControlNet如果可用
+        # 尝试使用ControlNet
         if hasattr(model_manager, 'controlnet_pipeline') and model_manager.controlnet_pipeline:
             try:
-                # 使用ControlNet生成更精确的试穿效果
+                # 使用原始图像作为控制图，选择的设计作为风格参考
                 image = model_manager.generate_controlnet_image(
-                    image=app_state.current_image,  # 使用原始图像作为控制
+                    image=app_state.current_image,  # 姿势控制
                     prompt=fitting_prompt,
+                    reference_image=selected_image,  # 设计风格参考
                     negative_prompt="blurry, distorted, low quality, unrealistic, extra limbs, deformed",
                     num_inference_steps=30,
                     guidance_scale=8.0
@@ -459,7 +171,7 @@ def generate_3d_fitting(selected_design, progress=gr.Progress()):
                 progress(0.9, desc="完成3D渲染")
                 return image
             except Exception as e:
-                logger.warning(f"ControlNet生成失败，使用普通SD: {e}")
+                logger.warning(f"ControlNet生成失败: {e}")
         
         # 回退到普通SD模型
         progress(0.5, desc="使用标准模型生成...")
@@ -469,145 +181,110 @@ def generate_3d_fitting(selected_design, progress=gr.Progress()):
                 negative_prompt="blurry, distorted, low quality, unrealistic, extra limbs, deformed, bad anatomy",
                 num_inference_steps=30,
                 width=512,
-                height=768,  # 适合全身图像
+                height=768,
                 guidance_scale=7.5
             )
         except Exception as e:
             logger.error(f"3D试穿生成失败: {e}")
-            # 创建占位图像
-            image = Image.new('RGB', (512, 768), color=(180, 180, 180))
+            image = create_placeholder_image(512, 768)
         
         progress(0.9, desc="完成3D渲染")
         return image
         
     except Exception as e:
         logger.error(f"3D试穿生成错误: {e}")
-        # 创建占位图像
-        img = Image.new('RGB', (512, 768), color=(180, 180, 180))
-        return img
+        return create_placeholder_image(512, 768)
 
-def create_3d_fitting_prompt(design_info, analysis):
-    """创建3D试穿的提示词"""
+def create_design_prompt(suggestion, analysis):
+    """创建详细的设计提示词 - 整合所有分析结果"""
     try:
+        # 从分析中提取关键信息
         style_info = analysis.get("主要风格", "时尚")
         colors = analysis.get("主要颜色", ["现代色"])
+        caption = analysis.get("图像描述", "")
         
-        # 3D试穿基础提示词
-        base_prompt = "3D virtual try-on, realistic human model wearing"
+        # 获取风格描述
+        style_prompts = {
+            "商务正装": "专业商务装，正式西装，简洁线条，精致剪裁",
+            "休闲风": "休闲服装，舒适风格，日常穿着，宽松合身",
+            "运动风": "运动服装，功能性设计，运动休闲",
+            "时尚潮流": "时尚潮流，现代设计，高级时装",
+            "复古风": "复古风格，怀旧元素，经典设计",
+            "街头风": "街头服饰，都市风格，现代青年文化",
+            "优雅风": "优雅服装，精致风格，高贵设计"
+        }
         
-        # 根据设计信息调整
-        if "方案" in design_info:
-            design_type = design_info.split(" - ")[0] if " - " in design_info else design_info
-        else:
-            design_type = design_info
+        style_prompt = style_prompts.get(style_info, "时尚服装，现代设计")
         
-        # 添加风格和颜色信息
-        style_desc = f"{style_info} style clothing"
-        color_desc = f"in {colors[0] if colors else 'stylish colors'}"
+        # 颜色描述
+        color_prompt = f"主色调: {colors[0] if colors else '现代色调'}"
+        if len(colors) > 1:
+            color_prompt += f", 辅色: {colors[1]}"
         
-        # 完整的3D试穿提示词
-        full_prompt = f"{base_prompt} {style_desc} {color_desc}, full body shot, professional studio lighting, high quality 3D rendering, realistic fabric texture, well-fitted clothing"
+        # 根据建议调整提示词
+        suggestion_modifiers = {
+            "经典": "经典设计，永恒风格，传统元素",
+            "现代": "现代美学，创新设计，前沿时尚",
+            "时尚": "时尚前沿，T台风格，潮流趋势",
+            "个性": "独特设计，个性化元素，定制风格"
+        }
         
-        logger.info(f"3D试穿提示词: {full_prompt}")
+        modifier = "高品质，精心设计，时尚风格"
+        for key, value in suggestion_modifiers.items():
+            if key in suggestion:
+                modifier = value
+                break
+        
+        # 组合完整的提示词 - 整合所有分析元素
+        full_prompt = (
+            f"{style_prompt}，{color_prompt}，{modifier}。"
+            f"设计灵感来源：'{caption}'。"
+            f"高清细节，专业时尚摄影，工作室灯光"
+        )
+        
+        logger.info(f"生成的设计提示词: {full_prompt}")
         return full_prompt
         
     except Exception as e:
-        logger.error(f"创建3D提示词失败: {e}")
-        return "3D virtual fashion try-on, realistic human model, full body, studio lighting"
+        logger.error(f"创建提示词失败: {e}")
+        return "时尚服装设计，高品质，专业时尚"
 
-def create_gradio_interface():
-    """创建Gradio用户界面"""
-    
-    with gr.Blocks(title="AI时尚设计师", theme="soft") as demo:
-        gr.Markdown("# 🎨 AI时尚设计师")
-        gr.Markdown("上传服装图片，AI将分析风格并生成个性化设计方案和3D试穿效果")
-        
-        with gr.Row():
-            with gr.Column(scale=1):
-                image_input = gr.Image(type="filepath", label="上传参考图片", height=400)
-                analyze_btn = gr.Button("🔍 AI智能分析", variant="primary", size="lg")
-            
-            with gr.Column(scale=2):
-                analysis_output = gr.JSON(label="🎯 AI分析结果")
-        
-        with gr.Tab("💡 设计建议"):
-            suggestions_output = gr.JSON(label="个性化设计建议")
-            suggestion_choice = gr.Radio(label="选择设计方向", interactive=True)
-            generate_designs_btn = gr.Button("🎨 生成设计方案", variant="primary")
-        
-        with gr.Tab("👔 样衣设计"):
-            designs_gallery = gr.Gallery(label="AI生成的设计方案", columns=3, height=400)
-            design_choice = gr.Radio(label="选择设计方案", interactive=True)
-            generate_3d_btn = gr.Button("🎭 生成3D试穿效果", variant="primary")
-        
-        with gr.Tab("👤 3D试穿效果"):
-            fitting_result = gr.Image(label="3D试穿效果", height=600)
-            
-        # 系统状态和控制
-        with gr.Row():
-            with gr.Column():
-                gr.Markdown("### 🔧 系统控制")
-                cleanup_btn = gr.Button("🧹 清理内存", variant="secondary")
-                gr.Markdown("> **提示**: 如果遇到内存问题，请点击清理内存按钮")
-            
-        # 事件绑定 - 完整的流水线连接
-        analyze_btn.click(
-            fn=upload_and_analyze,
-            inputs=[image_input],
-            outputs=[analysis_output, suggestions_output, suggestion_choice, designs_gallery],
-            concurrency_limit=1
-        )
+def create_3d_fitting_prompt(design_index, analysis):
+    """创建3D试穿的提示词 - 整合所有分析结果"""
+    try:
+        style_info = analysis.get("主要风格", "时尚")
+        colors = analysis.get("主要颜色", ["现代色"])
+        caption = analysis.get("图像描述", "")
         
-        generate_designs_btn.click(
-            fn=generate_designs,
-            inputs=[suggestion_choice],
-            outputs=[designs_gallery, design_choice],
-            concurrency_limit=1
-        )
+        # 获取设计描述
+        design_desc = f"设计方案 {design_index+1}"
         
-        generate_3d_btn.click(
-            fn=generate_3d_fitting,
-            inputs=[design_choice],
-            outputs=[fitting_result],
-            concurrency_limit=1
-        )
+        # 3D试穿基础提示词
+        base_prompt = "3D虚拟试穿，真实人体模特穿着"
         
-        cleanup_btn.click(
-            fn=model_manager.cleanup,
-            inputs=[],
-            outputs=[]
+        # 添加风格和颜色信息
+        style_desc = f"{style_info}风格服装"
+        color_desc = f"主色调: {colors[0] if colors else '时尚色调'}"
+        
+        # 完整的3D试穿提示词
+        full_prompt = (
+            f"{base_prompt} {style_desc}，{color_desc}。"
+            f"全身展示，专业工作室灯光，高质量3D渲染，"
+            f"真实面料质感，合身剪裁。"
+            f"设计灵感：'{caption}'。"
+            f"具体设计：{design_desc}"
         )
         
-        # 添加使用说明
-        with gr.Row():
-            gr.Markdown("""
-            ### 📋 使用流程:
-            1. **上传图片** → 点击"AI智能分析"进行风格识别
-            2. **查看建议** → 在"设计建议"标签中选择心仪的设计方向
-            3. **生成设计** → 点击"生成设计方案"查看AI设计的服装
-            4. **3D试穿** → ���择喜欢的设计，点击"生成3D试穿效果"
-            
-            💡 **提示**: 
-            - 每一步都会调用相应的AI模型，请耐心等待生成完成
-            - 如果遇到模型加载问题，请检查网络连接或预下载模型
-            """)
-    
-    return demo
+        logger.info(f"3D试穿提示词: {full_prompt}")
+        return full_prompt
+        
+    except Exception as e:
+        logger.error(f"创建3D提示词失败: {e}")
+        return "3D虚拟时尚试穿，真实人体模特，全身展示，工作室灯光"
+
+def create_placeholder_image(width, height):
+    """创建占位图像"""
+    color = (random.randint(120, 200), random.randint(120, 200), random.randint(120, 200))
+    return Image.new('RGB', (width, height), color=color)
 
-if __name__ == "__main__":
-    # 检查环境
-    logger.info(f"Python版本: {sys.version}")
-    logger.info(f"当前工作目录: {os.getcwd()}")
-    logger.info(f"模型管理器状态: {'完整版' if MODELS_AVAILABLE else '简化版'}")
-    
-    # 创建并启动界面
-    demo = create_gradio_interface()
-    
-    # 启动应用
-    demo.launch(
-        server_name="0.0.0.0", 
-        server_port=7860,
-        share=False,
-        show_error=True,
-        max_threads=2
-    )
+# ...（保留后续的UI创建和启动代码）