Update app.py

app.py

@@ -18,13 +18,19 @@ transform = transforms.Compose([
 # Function to classify posture images
 def classify_image(image):
     if image is None:
-        return "No image provided!"
+        return "No image provided! Please capture or upload an image."
     
     image = transform(image).unsqueeze(0)
     output = model(image)
     _, predicted = torch.max(output, 1)
-    return "Good Posture! Sit exactly like that for your Interview!" if predicted.item() == 0 else "Bad Posture, you should think of sitting a little straighter or more in frame for your real interview."
+    return (
+        "Good Posture! Sit exactly like that for your Interview!" 
+        if predicted.item() == 0 
+        else "Bad Posture, you should think of sitting a little straighter or more in frame for your real interview."
+    )
 
-# Set up Gradio interface
-iface = gr.Interface(fn=classify_image, inputs=gr.Image(type="pil", height=150, width=150), outputs="text")
-iface.launch()
+# Create a compact Gradio layout using Blocks
+with gr.Blocks() as demo:
+    gr.Markdown("### Posture Classifier")
+    
+    img_input = gr.Image