from fastai.vision.all import *
import gradio as gr

# def greet(name):
#     return "Hello " + name + "!!"

def is_cat(x): 
    return x[0].isupper() 

learn = load_learner('model.pkl')

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(learn.dls.vocab, map(float, probs)))

image = gr.Image(shape=(192, 192))
label = gr.outputs.Label()

demo = gr.Interface(fn=classify_image, inputs=image, outputs=label)
# demo.launch()


# demo = gr.Interface(
#     fn = classify_image,
#     inputs=gr.Image(type='pil'),
#     outputs=[gr.Textbox(label="Predicted Label"), gr.Image(label="Labeled Image")],
#     title="Image Classification App",
#     description="Upload an image and get the predicted label and labeled image."

# )
if __name__ == "__main__":
    demo.launch(share=True)