Update app.py

app.py

@@ -40,9 +40,9 @@ transform = transforms.Compose([
 class_names = ['BacterialBlights', 'Healthy', 'Mosaic', 'RedRot', 'Rust', 'Yellow']
 
 # Function to predict disease type from an image
-def predict_disease(image_path):
+def predict_disease(image):
     # Open the image file
-    img = Image.open(image_path)
+    img = Image.open(image)
     
     # Apply transformations to the image
     img_tensor = transform(img).unsqueeze(0)  # Add batch dimension
@@ -57,7 +57,21 @@ def predict_disease(image_path):
     
     return predicted_label
 
-# Test with a new image
-image_path = 'img1.png'  # Replace with your image path
-predicted_label = predict_disease(image_path)
-print(f'The predicted disease type is: {predicted_label}')
+# Gradio interface
+inputs = gr.inputs.Image(type="pil")
+outputs = gr.outputs.Text()
+
+EXAMPLES = ["img1.png"]
+
+demo_app = gr.Interface(
+    fn=predict_disease, 
+    inputs=inputs,
+    outputs=outputs,
+    title="Sugarcane Disease Prediction with ViT",
+    examples=EXAMPLES,
+    live=True,
+    theme="huggingface"
+)
+
+demo_app.launch(debug=True, enable_queue=True)
+