完成简单版本的逻辑

app.py

@@ -8,9 +8,11 @@ from pathlib import Path
 import uuid
 import argparse
 import torch
+import uvicorn
+from fastapi import FastAPI
+from fastapi.staticfiles import StaticFiles
 import trimesh
 
-
 parser = argparse.ArgumentParser()
 parser.add_argument("--model_path", type=str, default='tencent/Hunyuan3D-2mini')
 parser.add_argument("--subfolder", type=str, default='hunyuan3d-dit-v2-mini-turbo')
@@ -178,39 +180,49 @@ def gen_shape(
 
     path = export_mesh(mesh, save_folder, textured=False)
 
-    model_viewer_html = build_model_viewer_html(save_folder, height=HTML_HEIGHT, width=HTML_WIDTH)
+    # model_viewer_html = build_model_viewer_html(save_folder, height=HTML_HEIGHT, width=HTML_WIDTH)
 
-    return model_viewer_html, path
+    # return model_viewer_html, path
 
-    # if args.low_vram_mode:
-    #     torch.cuda.empty_cache()
+    if args.low_vram_mode:
+        torch.cuda.empty_cache()
     
-    # if path is None:
-    #     raise gr.Error('Please generate a mesh first.')
+    if path is None:
+        raise gr.Error('Please generate a mesh first.')
 
-    # # 简化模型
-    # print(f'exporting {path}')
-    # print(f'reduce face to {target_face_num}')
+    # 简化模型
+    print(f'exporting {path}')
+    print(f'reduce face to {target_face_num}')
 
-    # mesh = trimesh.load(path)
-    # progress(0.5,desc="Optimizing mesh")
+    mesh = trimesh.load(path)
+    progress(0.5,desc="Optimizing mesh")
 
-    # mesh = floater_remove_worker(mesh)
-    # mesh = degenerate_face_remove_worker(mesh)
-    # progress(0.6,desc="Reducing mesh faces")
-    # mesh = face_reduce_worker(mesh, target_face_num)
-    # save_folder = gen_save_folder()
+    mesh = floater_remove_worker(mesh)
+    mesh = degenerate_face_remove_worker(mesh)
+    progress(0.6,desc="Reducing mesh faces")
+    mesh = face_reduce_worker(mesh, target_face_num)
+    save_folder = gen_save_folder()
 
-    # file_type = "obj"
-    # path = export_mesh(mesh, save_folder, textured=False, type=file_type)
+    file_type = "obj"
+    objPath = export_mesh(mesh, save_folder, textured=False, type=file_type)
+    rel_objPath = os.path.relpath(objPath, SAVE_DIR)
+    objPath = "/static/"+rel_objPath
 
-    # # for preview
-    # save_folder = gen_save_folder()
-    # _ = export_mesh(mesh, save_folder, textured=False)
-    # model_viewer_html = build_model_viewer_html(save_folder, height=HTML_HEIGHT, width=HTML_WIDTH, textured=False)
+    # for preview
+    save_folder = gen_save_folder()
+    _ = export_mesh(mesh, save_folder, textured=False)
+    model_viewer_html = build_model_viewer_html(save_folder, height=HTML_HEIGHT, width=HTML_WIDTH, textured=False)
 
-    # progress(1,desc="Complete")
-    # return model_viewer_html, path
+
+    glbPath = os.path.join(save_folder, f'white_mesh.glb')
+    rel_glbPath = os.path.relpath(glbPath, SAVE_DIR)
+    glbPath = "/static/"+rel_glbPath
+
+
+
+
+    progress(1,desc="Complete")
+    return model_viewer_html, glbPath, objPath
 
 
 
@@ -262,7 +274,8 @@ with gr.Blocks().queue() as demo:
         with gr.Column(scale=6):
             gr.Markdown("#### Generated Mesh")
             html_export_mesh = gr.HTML(HTML_OUTPUT_PLACEHOLDER, label='Output')
-            path_output  = gr.Textbox(label="Mesh Path") 
+            objPath_output  = gr.Textbox(label="Obj Path")
+            glbPath_output  = gr.Textbox(label="Glb Path") 
                 
         with gr.Column(scale=3):
             gr.Markdown("#### Image Examples")
@@ -272,7 +285,21 @@ with gr.Blocks().queue() as demo:
     gen_button.click(
         fn=gen_shape,
         inputs=[image,num_steps,cfg_scale,seed,octree_resolution,num_chunks,target_face_num, randomize_seed], 
-        outputs=[html_export_mesh, path_output]
+        outputs=[html_export_mesh, glbPath_output, objPath_output]
     )    
 
-demo.launch()
+ # https://discuss.huggingface.co/t/how-to-serve-an-html-file/33921/2
+# create a FastAPI app
+app = FastAPI()
+# create a static directory to store the static files
+static_dir = Path(SAVE_DIR).absolute()
+static_dir.mkdir(parents=True, exist_ok=True)
+app.mount("/static", StaticFiles(directory=static_dir, html=True), name="static")
+shutil.copytree('./assets/env_maps', os.path.join(static_dir, 'env_maps'), dirs_exist_ok=True)
+
+if args.low_vram_mode:
+    torch.cuda.empty_cache()
+
+app = gr.mount_gradio_app(app, demo, path="/")
+# demo.launch()
+uvicorn.run(app, host=args.host, port=args.port)