app.py

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

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

learn = load_learner('model.pkl')

categories = ('Dog', 'Cat')

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

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['dog.jpeg', 'cat.jpeg', 'dunno.jpeg'];

iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title="Cat or Dog Classifier", description="This is a cat or dog classifier. It uses a ResNet34 model trained on the Oxford-IIIT Pet Dataset. The dataset has 12 cat breeds and 25 dog breeds. The model was trained for 5 epochs.")
iface.launch(inline=False)