Update app.py

app.py

@@ -2,33 +2,21 @@ import spaces
 import supervision as sv
 import PIL.Image as Image
 from ultralytics import YOLO
-from huggingface_hub import hf_hub_download, HfApi
+from huggingface_hub import hf_hub_download
 import gradio as gr
 
 global repo_id
 
 def download_models(model_id):
-    hf_hub_download(repo_id, filename = f"{model_id}", local_dir = f"./")
+    hf_hub_download(repo_id, filename=f"{model_id}", local_dir=f"./")
     return f"./{model_id}"
 
-def get_model_filenames(repo_id, file_extension = ".pt"):
-    api = HfApi()
-    files = api.list_repo_files(repo_id)
-    model_filenames = [file for file in files if file.endswith(file_extension)]
-    return model_filenames
-
 repo_id = "atalaydenknalbant/asl-yolo-models"
-model_filenames = get_model_filenames(repo_id)
-print("Model filenames:", model_filenames)
-
 box_annotator = sv.BoxAnnotator()
 category_dict = {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F', 6: 'G', 7: 'H', 8: 'I',
                  9: 'J', 10: 'K', 11: 'L', 12: 'M', 13: 'N', 14: 'O', 15: 'P', 16: 'Q',
                  17: 'R', 18: 'S', 19: 'T', 20: 'U', 21: 'V', 22: 'W', 23: 'X', 24: 'Y', 25: 'Z'}
 
-
-
-
 @spaces.GPU
 def yolo_inference(image, model_id, conf_threshold, iou_threshold, max_detection):
     model_path = download_models(model_id)
@@ -50,11 +38,8 @@ def app():
             with gr.Column():
                 image = gr.Image(type="pil", label="Image", interactive=True)
     
-                model_id = gr.Dropdown(
-                    label="Model",
-                    choices=model_filenames,
-                    value=model_filenames[0] if model_filenames else "",
-                )
+                model_id = gr.Textbox(label="Model ID", placeholder="Enter model filename (.pt)")
+                
                 conf_threshold = gr.Slider(
                     label="Confidence Threshold",
                     minimum=0.1,
@@ -142,4 +127,4 @@ with gradio_app:
         with gr.Column():
             app()
 
-gradio_app.launch(debug=True)
+gradio_app.launch(debug=True)