Update app.py

app.py

@@ -10,12 +10,19 @@ from tensorflow.keras.models import Sequential
 
 from keras.models import load_model
 model1 = load_model('model1.h5')
+
+class_names = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips'] 
 def predict_image(img):
   img_4d=img.reshape(-1,180,180,3)
   prediction=model1.predict(img_4d)[0]
   return {class_names[i]: float(prediction[i]) for i in range(5)}
-class_names = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips'] 
+
 image = gr.inputs.Image(shape=(180,180))
 label = gr.outputs.Label(num_top_classes=5)
+enable_queue=True
+description="This is a Flower Classification Model made using a CNN.Deployed to Hugging Faces using Gradio."
+examples = ['dandelion.jpg','sunflower.jpeg','tulip.jpg']
+article="<p style='text-align: center'>Made by Aditya Narendra with 🖤</p>"
+
 
-gr.Interface(fn=predict_image, inputs=image, outputs=label,interpretation='default').launch(debug='True')
+gr.Interface(fn=predict_image, inputs=image, outputs=label,title="Flower Classifier",description=description,article=article,examples=examples,enable_queue=enable_queue,interpretation='default').launch(debug='True')