app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: app1.ipynb.

# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'description', 'intf', 'classify_image']

# %% app1.ipynb 2
from fastai.vision.all import *
import gradio as gr
import timm

# %% app1.ipynb 3
learn = load_learner('pets_classifier_model.pkl')

# %% app1.ipynb 5
categories = learn.dls.vocab

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

# %% app1.ipynb 6
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['samoyed.jpg']
description="A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Deep Learning app using HuggingFace Spaces and Gradio"

# %% app1.ipynb 7
intf = gr.Interface(fn=classify_image, 
                    inputs=image, 
                    outputs=label,
                    title="Pets classifier",
                    description=description,
                    interpretation='default',
                    examples=examples, enable_queue=True)
intf.launch(inline=False)