Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py - 完整连接版本
 import gradio as gr
 import os
 import sys
@@ -316,6 +315,21 @@ def generate_designs(selected_suggestion, progress=gr.Progress()):
         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...")
@@ -323,15 +337,22 @@ def generate_designs(selected_suggestion, progress=gr.Progress()):
                 # 为每个设计添加变化
                 variant_prompt = f"{base_prompt}, design variation {i+1}, unique style, high quality fashion design"
                 
-                # 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
-                )
+                # 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)
                 
                 if image:
                     design_images.append(image)
@@ -442,14 +463,19 @@ def generate_3d_fitting(selected_design, progress=gr.Progress()):
         
         # 回退到普通SD模型
         progress(0.5, desc="使用标准模型生成...")
-        image = model_manager.generate_image(
-            prompt=fitting_prompt,
-            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
-            guidance_scale=7.5
-        )
+        try:
+            image = model_manager.generate_image(
+                prompt=fitting_prompt,
+                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
+                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))
         
         progress(0.9, desc="完成3D渲染")
         return image
@@ -561,7 +587,9 @@ def create_gradio_interface():
             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** → 选择喜欢的设计，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
+            💡 **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