Enhance Gradio interface with settings accordion and user guidance

- Move confidence threshold slider into a collapsible settings accordion
- Update project description with a user-friendly hint for interaction
- Fix image resizing for ViT models by using the correct input image

app.py

@@ -90,7 +90,7 @@ def predict_image(img, confidence_threshold):
     # Resize the image
     img_pil = transforms.Resize((256, 256))(img_pil)
     # Size 224 for vits models
-    img_pilvits = transforms.Resize((224, 224))(img_pilvits)
+    img_pilvits = transforms.Resize((224, 224))(img_pil)
     
     # Predict using the first model
     try:
@@ -508,11 +508,12 @@ with gr.Blocks() as iface:
     with gr.Row():
         with gr.Column(scale=1):
             image_input = gr.Image(label="Upload Image to Analyze", sources=['upload'], type='pil')
-            confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")
+            with gr.Accordion("Settings", open=False):
+                confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")
             inputs = [image_input, confidence_slider]
         with gr.Column(scale=2):
             with gr.Accordion("Project OpenSight - Model Evaluations & Playground", open=True):
-                gr.Markdown("## OpenSight is a SOTA gen. image detection model, in pre-release prep.\n\nThis HF Space is a temporary home for us and the public to evaluate the shortcomings of current open source models.")
+                gr.Markdown("## OpenSight is a SOTA gen. image detection model, in pre-release prep.\n\nThis HF Space is a temporary home for us and the public to evaluate the shortcomings of current open source models.\n\n<-- Feel free to play around by starting with an image as we prepare our formal announcement.")
             image_output = gr.Image(label="Processed Image", visible=False)
             # Custom HTML component to display results in 5 columns
             results_html = gr.HTML(label="Model Predictions")