1

docker-compose.yaml

@@ -1,7 +1,7 @@
 services:
   trellis:
-    image: zhouchengrong/fida-trellis:latest  # 你 commit 的镜像
-    container_name: trellis-dev
+    image: zhouchengrong/fida-trellis-a6000:latest  # 你 commit 的镜像
+    container_name: FiDA_3D_Trellis
     restart: unless-stopped
     environment:
       - NVIDIA_VISIBLE_DEVICES=all
@@ -24,8 +24,5 @@ services:
               capabilities: [ gpu, compute, utility ]  # 移除 video（非必需，减少兼容问题）
     command: >
       bash -c "
-        /opt/conda/envs/trellis/bin/python -c 'import torch; print(torch.__version__, torch.cuda.is_available())' &&
-        /opt/conda/envs/trellis/bin/python server.py
-      "
-#        /opt/conda/envs/trellis/bin/python server.py
-#        tail -f /dev/null
+        conda run --no-capture-output -n trellis python server.py
+      "

server.py

@@ -144,11 +144,12 @@ class TrellisAPI(ls.LitAPI):
 
     def decode_request(self, request):
         image_paths = request["image_paths"]
+        bucket_name = request["bucket_name"]
+        user_id = request["user_id"]
+
         images = []
         for path in image_paths:
-            bucket = path.split('/')[0]
-            object_name = path[path.find('/') + 1:]
-
+            bucket, object_name = path.split('/', 1)
             image = minio_get_image(minio_client, bucket, object_name)
             images.append(image)
 
@@ -163,6 +164,8 @@ class TrellisAPI(ls.LitAPI):
             "simplify": request.get("simplify", 0.95),
             "texture_size": request.get("texture_size", 1024),
             "fps": request.get("fps", 30),
+            "bucket_name": bucket_name,
+            "user_id": user_id
         }
 
         return images, params
@@ -202,8 +205,7 @@ class TrellisAPI(ls.LitAPI):
 
         glb_info = analyze_mesh(local_glb_path)
 
-        local_static_model_image_path = os.path.join("glb_output", generate_unique_name("static_model_image.png"))
-        static_model_image = self.get_static_model_image(model_path=local_glb_path, output_path=local_static_model_image_path)
+        static_model_image = self.get_static_model_image(model_path=local_glb_path, params=params)
 
         return {
             "glb_path": minio_glb_path,
@@ -214,49 +216,49 @@ class TrellisAPI(ls.LitAPI):
     def encode_response(self, output):
         return output
 
-    def upload_video(self, outputs, params):
-        gaussian_name = f"3d_result/video/{params['file_name']}-gaussian.mp4"
-        radiance_field_name = f"3d_result/video/{params['file_name']}-radiance_field.mp4"
-        mesh_name = f"3d_result/video/{params['file_name']}-mesh.mp4"
-
-        # gaussian video
-        video = render_utils.render_video(outputs["gaussian"][0])["color"]
-        buffer = BytesIO()
-        imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
-        gaussian_video_path = upload_bytes(
-            buffer.getvalue(),
-            gaussian_name,
-            "video/mp4",
-        )
-
-        # radiance field video
-        video = render_utils.render_video(outputs["radiance_field"][0])["color"]
-        buffer = BytesIO()
-        imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
-        radiance_field_video_path = upload_bytes(
-            buffer.getvalue(),
-            radiance_field_name,
-            "video/mp4",
-        )
-
-        # mesh video
-        video = render_utils.render_video(outputs["mesh"][0])["normal"]
-        buffer = BytesIO()
-        imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
-        mesh_path = upload_bytes(
-            buffer.getvalue(),
-            mesh_name,
-            "video/mp4",
-        )
-
-        return {
-            "gaussian": gaussian_video_path,
-            "radiance_field": radiance_field_video_path,
-            "mesh": mesh_path
-        }
+    # def upload_video(self, outputs, params):
+    #     gaussian_name = f"3d_result/video/{params['file_name']}-gaussian.mp4"
+    #     radiance_field_name = f"3d_result/video/{params['file_name']}-radiance_field.mp4"
+    #     mesh_name = f"3d_result/video/{params['file_name']}-mesh.mp4"
+    #
+    #     # gaussian video
+    #     video = render_utils.render_video(outputs["gaussian"][0])["color"]
+    #     buffer = BytesIO()
+    #     imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
+    #     gaussian_video_path = upload_bytes(
+    #         buffer.getvalue(),
+    #         gaussian_name,
+    #         "video/mp4",
+    #     )
+    #
+    #     # radiance field video
+    #     video = render_utils.render_video(outputs["radiance_field"][0])["color"]
+    #     buffer = BytesIO()
+    #     imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
+    #     radiance_field_video_path = upload_bytes(
+    #         buffer.getvalue(),
+    #         radiance_field_name,
+    #         "video/mp4",
+    #     )
+    #
+    #     # mesh video
+    #     video = render_utils.render_video(outputs["mesh"][0])["normal"]
+    #     buffer = BytesIO()
+    #     imageio.mimsave(buffer, video, format="mp4", fps=params['fps'])
+    #     mesh_path = upload_bytes(
+    #         buffer.getvalue(),
+    #         mesh_name,
+    #         "video/mp4",
+    #     )
+    #
+    #     return {
+    #         "gaussian": gaussian_video_path,
+    #         "radiance_field": radiance_field_video_path,
+    #         "mesh": mesh_path
+    #     }
 
     def upload_glb(self, outputs, params):
-        file_name = f"3d_result/glb/{params['file_name']}.glb"
+        minio_path = f"{params['bucket_name']}/{params['user_id']}/3d_result/{params['file_name']}.glb"
         local_glb_path = os.path.join("glb_output", generate_unique_name("sample.glb"))
         out_dir = os.path.dirname(local_glb_path)
         if out_dir:
@@ -275,31 +277,28 @@ class TrellisAPI(ls.LitAPI):
         )
 
         glb_path = upload_local_file(
-            local_glb_path,
-            file_name,
-            "application/octet-stream",
+            file_path=local_glb_path,
+            minio_path=minio_path,
+            content_type="application/octet-stream"
         )
         return glb_path, local_glb_path
 
-    def upload_ply(self, outputs, params):
-        file_name = f"3d_result/ply/{params['file_name']}.ply"
+    # def upload_ply(self, outputs, params):
+    #     file_name = f"3d_result/ply/{params['file_name']}.ply"
+    #
+    #     with tempfile.NamedTemporaryFile(suffix=".ply") as tmp:
+    #         outputs["gaussian"][0].save_ply(tmp.name)
+    #         tmp.seek(0)
+    #
+    #         ply_path = upload_bytes(
+    #             tmp.read(),
+    #             file_name,
+    #             "application/octet-stream",
+    #         )
+    #     return {"ply": ply_path}
 
-        with tempfile.NamedTemporaryFile(suffix=".ply") as tmp:
-            outputs["gaussian"][0].save_ply(tmp.name)
-            tmp.seek(0)
-
-            ply_path = upload_bytes(
-                tmp.read(),
-                file_name,
-                "application/octet-stream",
-            )
-        return {"ply": ply_path}
-
-    def get_static_model_image(self, model_path, output_path):
-        local_static_model_image_path = os.path.join(
-            "glb_output",
-            generate_unique_name("static_model_image.png")
-        )
+    def get_static_model_image(self, model_path, params):
+        local_static_model_image_path = os.path.join("glb_output", generate_unique_name("static_model_image.png"))
 
         print(f"model_path : {model_path}")
         print(f"local_static_model_image_path :{local_static_model_image_path}")
@@ -307,17 +306,18 @@ class TrellisAPI(ls.LitAPI):
 
         static_model_image = self.upload_local_file(
             output_path,
-            "png"
+            params['bucket_name'],
+            params['user_id'],
         )
 
         print(f"Saved to {static_model_image}")
         return static_model_image
 
-    def upload_local_file(self, local_path, type):
+    def upload_local_file(self, local_path, bucket_name, user_id):
         """
         通用上传函数：支持 SVG, PNG, OBJ 等
         """
-        object_name = f"3d_result/{type}/{uuid.uuid4().hex}.{type}"
+        object_name = f"{user_id}/3d_result/{uuid.uuid4().hex}.png"
         if not os.path.exists(local_path):
             print(f"错误: 文件 {local_path} 不存在")
             return None
@@ -330,13 +330,13 @@ class TrellisAPI(ls.LitAPI):
 
         try:
             minio_client.fput_object(
-                bucket_name=MINIO_BUCKET,
+                bucket_name=bucket_name,
                 object_name=object_name,
                 file_path=local_path,
                 content_type=content_type
             )
             print(f"成功上传 [{content_type}]: {object_name}")
-            return f"{MINIO_BUCKET}/{object_name}"
+            return f"{bucket_name}/{object_name}"
         except Exception as e:
             print(f"上传失败: {e}")
             return None

utils/new_oss_client.py

@@ -76,7 +76,7 @@ def upload_bytes(data_bytes, object_name, content_type):
     return f"{MINIO_BUCKET}/{object_name}"
 
 
-def upload_local_file(file_path, object_name, content_type="application/octet-stream"):
+def upload_local_file(file_path, minio_path, content_type="application/octet-stream"):
     """
     将本地磁盘上的文件上传到 MinIO
     :param file_path: 本地文件路径 (如: 'output/sample.obj')
@@ -88,14 +88,15 @@ def upload_local_file(file_path, object_name, content_type="application/octet-st
         raise FileNotFoundError(f"本地文件未找到: {file_path}")
 
     # 使用 fput_object 直接从磁盘流式上传，不占用过多内存
+    bucket, object_name = minio_path.split('/', 1)
+
     minio_client.fput_object(
-        bucket_name=MINIO_BUCKET,
+        bucket_name=bucket,
         object_name=object_name,
         file_path=file_path,
         content_type=content_type
     )
-
-    return f"{MINIO_BUCKET}/{object_name}"
+    return f"{bucket}/{object_name}"
 
 
 def download_from_minio(object_path, local_path):