Update app.py

app.py

@@ -3,7 +3,7 @@ import spaces
 from huggingface_hub import hf_hub_download
 
 @spaces.GPU
-def yolov9_inference(img_path, model_id, image_size, conf_threshold, iou_threshold):
+def yolov9_inference(img_path, conf_threshold, iou_threshold):
     """
     Load a YOLOv9 model, configure it, perform inference on an image, and optionally adjust 
     the input size and apply test time augmentation.
@@ -20,14 +20,14 @@ def yolov9_inference(img_path, model_id, image_size, conf_threshold, iou_thresho
     
     # Load the model
     model_path = "yolov9-plant.pt"
-    model = yolov9.load(model_path, device="cpu")
+    model = yolov9.load(model_path, device="cuda:0")
     
     # Set model parameters
     model.conf = conf_threshold
     model.iou = iou_threshold
     
     # Perform inference
-    results = model(img_path, size=image_size)
+    results = model(img_path, size=640)
 
     # Optionally, show detection bounding boxes on image
     output = results.render()
@@ -40,23 +40,6 @@ def app():
         with gr.Row():
             with gr.Column():
                 img_path = gr.Image(type="filepath", label="Image")
-                model_path = gr.Dropdown(
-                    label="Model",
-                    choices=[
-                        "gelan-c.pt",
-                        "gelan-e.pt",
-                        "yolov9-c.pt",
-                        "yolov9-e.pt",
-                    ],
-                    value="gelan-e.pt",
-                )
-                image_size = gr.Slider(
-                    label="Image Size",
-                    minimum=320,
-                    maximum=1280,
-                    step=32,
-                    value=640,
-                )
                 conf_threshold = gr.Slider(
                     label="Confidence Threshold",
                     minimum=0.1,
@@ -80,8 +63,6 @@ def app():
             fn=yolov9_inference,
             inputs=[
                 img_path,
-                model_path,
-                image_size,
                 conf_threshold,
                 iou_threshold,
             ],
@@ -91,16 +72,7 @@ def app():
         gr.Examples(
             examples=[
                 [
-                    "data/zidane.jpg",
-                    "gelan-e.pt",
-                    640,
-                    0.4,
-                    0.5,
-                ],
-                [
-                    "data/huggingface.jpg",
-                    "yolov9-c.pt",
-                    640,
+                    "data/apple_d1.jpg",
                     0.4,
                     0.5,
                 ],
@@ -126,13 +98,6 @@ with gradio_app:
     YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
     </h1>
     """)
-    gr.HTML(
-        """
-        <h3 style='text-align: center'>
-        Follow me for more!
-        <a href='https://twitter.com/kadirnar_ai' target='_blank'>Twitter</a> | <a href='https://github.com/kadirnar' target='_blank'>Github</a> | <a href='https://www.linkedin.com/in/kadir-nar/' target='_blank'>Linkedin</a>  | <a href='https://www.huggingface.co/kadirnar/' target='_blank'>HuggingFace</a>
-        </h3>
-        """)
     with gr.Row():
         with gr.Column():
             app()