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from pathlib import Path | |
from fastai.vision.learner import load_learner | |
import gradio as gr | |
MODELPATH='cygnet-vs-duckling.pkl' | |
learn = load_learner(MODELPATH) | |
categories = learn.dls.vocab | |
def classify_image(image): | |
_, _, probs = learn.predict(image) | |
return dict(zip(categories, map(float, probs))) | |
title = 'Mirror, mirror on the wall, am I a duckling or a cygnet after all?' | |
description = """Hans Christian Andersen's tale of the ugly duckling tells us about the sad youth of a cygnet which is accidentally brought up in a family of ducks and is ostrized on the account of it being different. But what if the cygnet had a magic mirror to tell it that it was in fact a young swan after all? Machine learning to the rescue!""" | |
examples = ['duckling.jpg', 'cygnet.jpg', 'sunflower.jpg', 'whiteclouds.jpg', 'yellowclouds.jpg'] | |
article = 'This model was build using a resnet-18 architecture, pretrained on ImageNet and finetuned using 100 images of ducklings and cygnets each.' | |
app = gr.Interface(fn=classify_image, | |
inputs=gr.components.Image(), | |
outputs=gr.components.Label(), | |
examples=examples, | |
title=title, | |
description=description, | |
article=article, | |
allow_flagging='never') | |
app.launch() | |