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

# Load the pre-trained model
learn_inf = load_learner('export.pkl')
labels = learn_inf.dls.vocab

# Prediction function
def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn_inf.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

# Create and launch the Gradio interface
interface = gr.Interface(
    fn=predict, 
    inputs=gr.Image(), 
    outputs=gr.Label(num_top_classes=3), 
    title="Domestic animal  Classifier",
    description="Domestic animal classifier using a deep learning model"
)

interface.launch(share=True)