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

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

learn_inf = load_learner('DogCat.pkl')
labels = learn_inf.dls.vocab

labels = ['Cat', 'Not_cat']

def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn_inf.predict(img)
    
    # Check if the prediction is "Cat" and return the appropriate string
    if pred == 'Cat':
        return "Yes, this is a cat"
    else:
        return "No, this is not a cat"

title = "Is this image of a cat?"
iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512,512)), outputs=gr.outputs.Label(num_top_classes=2), title=title)
iface.launch()