Move @spaces.GPU functions before Gradio Blocks for HF detection

app.py

@@ -150,7 +150,43 @@ def api_download_requirements():
 
 
 # ---------------------------------------------------------------------------
-# Gradio UI Functions
+# Helper functions (non-GPU)
+# ---------------------------------------------------------------------------
+
+def get_objects_table():
+    objs = db.get_all_objects()
+    data = []
+    for o in objs:
+        data.append([o.id, o.name, o.category, o.image_count, o.embedding_count, o.created_at])
+    return data
+
+
+def delete_selected_object(object_id):
+    if not object_id or not object_id.strip():
+        return "❌ Please enter a valid Object ID to delete.", get_objects_table()
+    success = db.delete_object(object_id.strip())
+    if success:
+        return f"✅ Deleted object '{object_id}'.", get_objects_table()
+    return f"❌ Object '{object_id}' not found.", get_objects_table()
+
+
+def load_doc_file(doc_name):
+    doc_path = os.path.join("docs", f"{doc_name}.md")
+    if os.path.exists(doc_path):
+        with open(doc_path, "r", encoding="utf-8") as f:
+            return f.read()
+    return f"Documentation file '{doc_name}' not found."
+
+
+def export_db_handler():
+    temp_dir = tempfile.mkdtemp()
+    export_path = os.path.join(temp_dir, "object_library_export.zip")
+    db.export_database_zip(export_path)
+    return export_path
+
+
+# ---------------------------------------------------------------------------
+# GPU Functions — defined BEFORE Gradio Blocks for HF ZeroGPU detection
 # ---------------------------------------------------------------------------
 
 @spaces.GPU
@@ -166,7 +202,6 @@ def run_gradio_detection(
     if input_image is None:
         return None, "Please upload or capture an image to perform detection."
 
-    # Convert PIL Image or NumPy to OpenCV BGR array
     if isinstance(input_image, Image.Image):
         img_np = np.array(input_image)
         img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR)
@@ -186,8 +221,7 @@ def run_gradio_detection(
     )
 
     annotated_rgb = cv2.cvtColor(annotated_bgr, cv2.COLOR_BGR2RGB)
-    
-    # Log detection summary to DB
+
     for det in detections:
         db.log_detection(
             object_name=det["label"],
@@ -208,7 +242,6 @@ def teach_new_object(name, category, description, reference_images):
         return "❌ Error: Please upload at least one reference photo.", get_objects_table()
 
     try:
-        # Check if exists or create
         existing = db.get_object_by_name(name.strip())
         if existing:
             obj = existing
@@ -236,38 +269,6 @@ def teach_new_object(name, category, description, reference_images):
         return f"❌ Error teaching object: {str(e)}", get_objects_table()
 
 
-def get_objects_table():
-    objs = db.get_all_objects()
-    data = []
-    for o in objs:
-        data.append([o.id, o.name, o.category, o.image_count, o.embedding_count, o.created_at])
-    return data
-
-
-def delete_selected_object(object_id):
-    if not object_id or not object_id.strip():
-        return "❌ Please enter a valid Object ID to delete.", get_objects_table()
-    success = db.delete_object(object_id.strip())
-    if success:
-        return f"✅ Deleted object '{object_id}'.", get_objects_table()
-    return f"❌ Object '{object_id}' not found.", get_objects_table()
-
-
-def load_doc_file(doc_name):
-    doc_path = os.path.join("docs", f"{doc_name}.md")
-    if os.path.exists(doc_path):
-        with open(doc_path, "r", encoding="utf-8") as f:
-            return f.read()
-    return f"Documentation file '{doc_name}' not found."
-
-
-def export_db_handler():
-    temp_dir = tempfile.mkdtemp()
-    export_path = os.path.join(temp_dir, "object_library_export.zip")
-    db.export_database_zip(export_path)
-    return export_path
-
-
 # ---------------------------------------------------------------------------
 # Building Modern Glassmorphic Gradio UI
 # ---------------------------------------------------------------------------