app.py

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

learn = load_learner('model.pkl')

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return pred

title = "Bird Species Classifier"
description = "A bird species classifier trained on Kaggle dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces(Only identifies bird species)."
examples = ['3.jpg','5.jpg','images.jpeg']
enable_queue=True

gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(224, 224)),outputs=gr.outputs.Label(num_top_classes=1),title=title,description=description,examples=examples,enable_queue=enable_queue).launch()