app.py

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

# Load the learner
learn = load_learner('export (1).pkl')

# Get the labels from the learner's dataloaders
labels = learn.dls.vocab

# Set up Gradio interface
title = "Bird or Not?"
description = "A classifier that detects birds using ResNet18"

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

# Set up the Gradio interface with the predict function
gr.Interface(fn=predict,inputs="image",outputs="label").launch()