update fastapi to 0.112.2

app.py

@@ -74,52 +74,6 @@ import shutil
 import time
 from concurrent.futures import ThreadPoolExecutor
 
-# debug
-import gradio, gradio_client, pydantic, httpx, fastapi, starlette, jinja2
-print("gradio:", gradio.__version__)
-print("gradio_client:", gradio_client.__version__)
-print("pydantic:", pydantic.__version__)
-print("httpx:", httpx.__version__)
-print("fastapi:", fastapi.__version__)
-print("starlette:", starlette.__version__)
-print("jinja2:", jinja2.__version__)
-
-# # fix bug
-# # --- Patch 1: gradio_client schema bool bug ---
-# try:
-#     import gradio_client.utils as _gcu
-
-#     _orig_schema_fn = _gcu._json_schema_to_python_type
-
-#     def _safe_schema_fn(schema, defs=None):
-#         if not isinstance(schema, dict):
-#             return "Any"
-#         return _orig_schema_fn(schema, defs)
-
-#     _gcu._json_schema_to_python_type = _safe_schema_fn
-#     print("Applied gradio_client schema patch")
-# except Exception as e:
-#     print(f"gradio_client schema patch failed: {e}")
-
-
-# # --- Patch 2: jinja2 cache unhashable dict bug ---
-# try:
-#     from jinja2.utils import LRUCache as _LRUCache
-
-#     _orig_lru_get = _LRUCache.get
-
-#     def _safe_lru_get(self, key, default=None):
-#         try:
-#             return _orig_lru_get(self, key, default)
-#         except TypeError:
-#             return default
-
-#     _LRUCache.get = _safe_lru_get
-#     print("Applied jinja2 LRUCache patch")
-# except Exception as e:
-#     print(f"jinja2 LRUCache patch failed: {e}")
-
-
 MARKDOWN = """
 ## Image to 3D Scene with [3D-Fixer](https://zx-yin.github.io/3dfixer/)
 1. Upload an image, and draw bounding boxes for each instance by holding and dragging the mouse. Then click "Run Segmentation" to generate the segmentation result.
@@ -139,13 +93,13 @@ generated_object_map = {}
 
 # Prepare models
 ## Grounding SAM
-sam2_predictor = None # SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-large")
+sam2_predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-large", device=torch.device("cpu"))
 
 ############## 3D-Fixer model
 model_dir = 'HorizonRobotics/3D-Fixer'
-# pipeline = ThreeDFixerPipeline.from_pretrained(
-#     model_dir, compile=False
-# )
+pipeline = ThreeDFixerPipeline.from_pretrained(
+    model_dir, compile=False
+)
 ############## 3D-Fixer model
 
 rot = np.array([
@@ -263,10 +217,6 @@ def run_segmentation(
     rgb_image = image_prompts["image"].convert("RGB")
 
     global work_space
-    global sam2_predictor
-    if sam2_predictor is None:
-        # lazy initialization
-        sam2_predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-large")
 
     # pre-process the layers and get the xyxy boxes of each layer
     if len(image_prompts["points"]) == 0:

requirements.txt

@@ -34,6 +34,6 @@ spconv-cu118
 huggingface_hub==0.36.0
 git+https://github.com/EasternJournalist/utils3d.git@9a4eb15e4021b67b12c460c7057d642626897ec8
 gradio_client==1.3.0
-httpx==0.24.1
+httpx==0.23.3
 pydantic==2.10.6
-fastapi==0.111.0
+fastapi==0.112.2