Spaces:
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from fastai.vision.all import * | |
import gradio as gr | |
learn = load_learner("model.pkl") | |
labels = learn.dls.vocab | |
def classify_image(img): | |
pred, idx, probs = learn.predict(img) | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
image = gr.inputs.Image(shape=(192,192)) | |
label = gr.outputs.Label() | |
examples = ['flag_australia.jpg', 'flag_chad.jpg', 'flag_ecuador.jpg', 'flag_monaco.jpg'] | |
title = "Confusing flags" | |
description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces." | |
description = """ | |
There are too many countries in the world, and even though it'd be interesting to cover all of them, there are a few sets of flags \[0] that look _very_ similar. Namely: | |
* Chad and Romania | |
* Senegal and Mali | |
* Indoneasia and Monaco | |
* New Zealand and Australia | |
* Ireland and Côte d’Ivoire | |
* Norway and Iceland | |
* Venezuela, Ecuador, and Colombia | |
* Luxembourg and the Netherlands | |
* Slovenia, Russia, and Slovakia | |
This is where this space helps. | |
\[0]: https://www.britannica.com/list/flags-that-look-alike | |
""" | |
iface = gr.Interface(fn=classify_image, inputs=image, outputs=gr.outputs.Label(num_top_classes=3), examples=examples, title=title, description=description) | |
iface.launch(inline=False) | |