testing / app.py
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# %%
#/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','Dunno')
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()
examples= ['dog.jpeg','cat.jpeg','dunno.jpeg']
iface = gr.Interface(fn=classify_image,
inputs=image,
outputs=label,
examples=examples,
title = 'Simple Image Classifier',
description = "A cat vs dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace spaces.")
iface.launch(inline=False)