Update app.py

app.py

@@ -4,9 +4,9 @@
 # # Import YOLOv9
 # import yolov9
 
-# # def download_models(model_id):
-# #     hf_hub_download("SakshiRathi77/void-space-detection/weights", filename=f"{model_id}", local_dir=f"./")
-# #     return f"./{model_id}"
+# def download_models(model_id):
+#     hf_hub_download("SakshiRathi77/void-space-detection/weights", filename=f"{model_id}", local_dir=f"./")
+#     return f"./{model_id}"
 
 # def download_models(model_id):
 #     hf_hub_download("merve/yolov9", filename=f"{model_id}", local_dir=f"./")
@@ -157,9 +157,9 @@ import spaces
 from huggingface_hub import hf_hub_download
 
 
-def download_models(model_id):
-    hf_hub_download("merve/yolov9", filename=f"{model_id}", local_dir=f"./")
-    return f"./{model_id}"
+# def download_models(model_id):
+#     hf_hub_download("SakshiRathi77/void-space-detection/weights", filename=f"{model_id}", local_dir=f"./")
+#     return f"./{model_id}"
 
 
 def yolov9_inference(img_path, model_id, image_size, conf_threshold, iou_threshold):
@@ -178,8 +178,8 @@ def yolov9_inference(img_path, model_id, image_size, conf_threshold, iou_thresho
     import yolov9
     
     # Load the model
-    model_path = download_models(model_id)
-    model = yolov9.load(model_path)
+    # model_path = download_models(model_id)
+    model = yolov9.load(model_id)
     
     # Set model parameters
     model.conf = conf_threshold
@@ -204,7 +204,7 @@ def app():
                     choices=[
                         "best.pt",
                     ],
-                    value="best.pt",
+                    value="./best.pt",
                 )
                 image_size = gr.Slider(
                     label="Image Size",