Update app.py

app.py

@@ -81,10 +81,12 @@ def set_example_url(example: list) -> dict:
     return gr.Textbox.update(value=example[0])
 
 
-title = """<h1 id="title">Face Mask Detection App with YOLOS</h1>"""
+title = """<h1 id="title">Face Mask Detection with YOLOS</h1>"""
 
 description = """
-Links to HuggingFace Models:
+The model used in this space is the fine-tuned version of the COCO trained [hustlv/yolos-small](https://huggingface.co/hustlv/yolos-small). This fine-tuned model was trained for 200 epochs on the [face-mask-dataset]() from Kaggle which consisted of 853 images.
+
+Links to HuggingFace Model:
 - [nickmuchi/yolos-small-finetuned-masks](https://huggingface.co/nickmuchi/yolos-small-finetuned-masks)  
 """
 
@@ -107,7 +109,7 @@ with demo:
     gr.Markdown(description)
     gr.Markdown(twitter_link)
     options = gr.Dropdown(choices=models,label='Select Object Detection Model',show_label=True)
-    slider_input = gr.Slider(minimum=0.2,maximum=1,value=0.7,label='Prediction Threshold')
+    slider_input = gr.Slider(minimum=0.2,maximum=1,value=0.5,step=0.1,label='Prediction Threshold')
     
     with gr.Tabs():
         with gr.TabItem('Image URL'):
@@ -123,7 +125,7 @@ with demo:
         with gr.TabItem('Image Upload'):
             with gr.Row():
                 img_input = gr.Image(type='pil')
-                img_output_from_upload= gr.Image(shape=(650,650))
+                img_output_from_upload= gr.Image(shape=(750,750))
                 
             with gr.Row(): 
                 example_images = gr.Dataset(components=[img_input],