| import gradio as gr | |
| def classify(img): | |
| pred, probability = predict_one_image(img, model_VGG19) | |
| return class_names[pred] | |
| demo = gr.Interface(fn=classify, | |
| inputs = gr.inputs.Image(shape=(224,224)), | |
| outputs =gr.outputs.Textbox(), | |
| title = "Flower Recognition", | |
| examples =['tulip.jpg','rose.jpg','daisy.jpg','dandelion.jpg','sunflower.jpg',], | |
| description = "Transfer Learning Application", | |
| allow_flagging = "never" | |
| ).launch(inbrowser=True) |