Update app.py (#1)

- Update app.py (bd611f2c35d6496b9092fb876e3d7bc2f72113c4)

app.py

@@ -1,4 +1,3 @@
-
 import json
 import gradio as gr
 import yolov5
@@ -9,13 +8,14 @@ app_title = "Football Object Detection"
 models_ids = ['keremberke/yolov5n-football', 'keremberke/yolov5s-football', 'keremberke/yolov5m-football']
 article = f"<p style='text-align: center'> <a href='https://huggingface.co/{models_ids[-1]}'>huggingface.co/{models_ids[-1]}</a> | <a href='https://huggingface.co/keremberke/football-object-detection'>huggingface.co/keremberke/football-object-detection</a> | <a href='https://github.com/keremberke/awesome-yolov5-models'>awesome-yolov5-models</a> </p>"
 
-current_model_id = models_ids[-1]
+# Set default model_id here
+default_model_id = models_ids[-1]
+current_model_id = default_model_id
 model = yolov5.load(current_model_id)
 
 examples = [['test_images/18_pp_jpg.rf.912a54e24d38371daf61114b9a6b18be.jpg', 0.25, 'keremberke/yolov5m-football'], ['test_images/54881_jpg.rf.62b337bc47dbf6fbf5a34e18a361de97.jpg', 0.25, 'keremberke/yolov5m-football'], ['test_images/55219_jpg.rf.cdfe02a50951cf1ad449e940fbb646ac.jpg', 0.25, 'keremberke/yolov5m-football']]
 
-
-def predict(image, threshold=0.25, model_id=None):
+def predict(image, threshold=0.25, model_id=default_model_id):
     # update model if required
     global current_model_id
     global model
@@ -36,7 +36,6 @@ def predict(image, threshold=0.25, model_id=None):
     output_image = Image.fromarray(numpy_image)
     return output_image
 
-
 gr.Interface(
     title=app_title,
     description="Created by 'keremberke'",
@@ -44,8 +43,7 @@ gr.Interface(
     fn=predict,
     inputs=[
         gr.Image(type="pil"),
-        gr.Slider(maximum=1, step=0.01, value=0.25),
-        gr.Dropdown(models_ids, value=models_ids[-1]),
+        gr.Slider(maximum=1, step=0.01, value=0.25)
     ],
     outputs=gr.Image(type="pil"),
     examples=examples,