Update app.py

app.py

@@ -1,3 +1,59 @@
-# Load model directly
+# app.py
+import gradio as gr
 from transformers import AutoModel
-model = AutoModel.from_pretrained("zxhezexin/openlrm-mix-large-1.1")
+import torch
+import numpy as np
+from PIL import Image
+
+def load_model():
+    # 加载模型
+    model = AutoModel.from_pretrained("jadechoghari/vfusion3d", trust_remote_code=True)
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model.to(device)
+    return model
+
+def process_image(input_image):
+    try:
+        # 确保输入图像是PIL Image格式
+        if not isinstance(input_image, Image.Image):
+            input_image = Image.fromarray(input_image)
+        
+        # 加载模型
+        model = load_model()
+        
+        # 图像预处理
+        input_image = input_image.resize((256, 256))
+        
+        # 转换为tensor
+        image_tensor = torch.from_numpy(np.array(input_image)).float()
+        image_tensor = image_tensor.permute(2, 0, 1).unsqueeze(0)
+        
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        image_tensor = image_tensor.to(device)
+        
+        # 模型推理
+        with torch.no_grad():
+            output = model(image_tensor)
+            
+        return output
+        
+    except Exception as e:
+        return f"错误: {str(e)}"
+
+# 创建Gradio界面
+demo = gr.Interface(
+    fn=process_image,
+    inputs=[
+        gr.Image(type="pil", label="上传图片")
+    ],
+    outputs=[
+        gr.Model3D(label="生成的3D模型"),
+        gr.Text(label="处理状态")
+    ],
+    title="麒迹云台 - 2D转3D模型生成器",
+    description="上传一张图片，AI将自动生成对应的3D模型。支持格式：jpg, png, jpeg",
+    theme=gr.themes.Soft()
+)
+
+if __name__ == "__main__":
+    demo.launch()