Upload app.py

app.py

@@ -520,10 +520,10 @@ async def handle_upright_challenge(data: dict) -> dict:
         # Debug: Log image dimensions
         logger.info(f"🔍 UPRIGHT DEBUG: Original image dimensions: {original_w}x{original_h}")
 
-        # Determine input size for this inference (prefer model config, default to 640 for consistency with ONNX test)
+        # Determine input size for this inference (prefer model config, default to 300 for upright 3x2 grid)
         input_size = model_data.get('input_size')
-        if not isinstance(input_size, int) or input_size <= 0:
-            input_size = 640
+        if not isinstance(input_size) or not isinstance(input_size, int) or input_size <= 0:
+            input_size = 300
 
         input_tensor = preprocess_image(image_bytes, input_size)
         outputs = model_data['session'].run(None, {model_data['input_name']: input_tensor})[0]