app.py

# %%
#/default_exp app

# %%
#/export
from fastai.vision.all import *
import gradio as gr

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

# %%
#/export
learn = load_learner('model.pkl')

# %%
#/export
categories = ('Dog','Cat')

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

# %%
#/export
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
title = "Pet Breed Classifier"
description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace spaces."
examples = ['dog.jpeg','cat.jpeg','dunno.jpeg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label,examples=examples)
intf.launch(inline=False)