Update app.py

app.py

@@ -16,19 +16,18 @@ def download_models(model_id):
 def yolov9_inference(img):
     """
     Perform inference on an image using the YOLOv9 model.
-
     :param img: Input image.
     :return: Output image with detections.
     """
     # Load the model
     model_path = download_models("gelan-c-seg.pt")
+    # Assuming you're using a YOLOv9 model from Ultralytics, you would typically use their library to load the model
     model = cv2.dnn.readNetFromDarknet(model_path)
     # Perform inference
-    results = model(img_path)
-
+    # Placeholder for inference code; replace with your actual inference code
+    results = model.forward()
     # Optionally, show detection bounding boxes on image
-    output = results.render()
-    
+    output_image = img  # Placeholder for output image; replace with your actual output image
     return output_image