Update app.py

app.py

@@ -13,16 +13,13 @@ def download_models(model_id):
     return local_model_path
 
 
-def yolov9_inference(img_path):
+def yolov9_inference(img):
     """
     Perform inference on an image using the YOLOv9 model.
 
-    :param img_path: Path to the image file.
+    :param img: Input image.
     :return: Output image with detections.
     """
-    # Load the image from the file path
-    image = cv2.imread(img_path)  # Use OpenCV to read the image
-
     # Load the model
     model_path = download_models("gelan-c-seg.pt")
     model = cv2.dnn.readNetFromDarknet(model_path)
@@ -30,14 +27,15 @@ def yolov9_inference(img_path):
     # Perform inference
     # (Add your inference code here)
 
-    # Optionally, show detection bounding boxes on image
-    output_image = image  # Placeholder for the output image
+    # Placeholder for the output image
+    output_image = img
 
     return output_image
 
+
 def app():
     return gr.Interface(
-        yolov9_inference,
+        fn=yolov9_inference,
         inputs=gr.inputs.Image(type="pil", label="Upload Image"),
         outputs="image",
         title="YOLOv9 Inference",
@@ -48,4 +46,3 @@ def app():
 
 gradio_app = app()
 gradio_app.launch(debug=True)
-