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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner('export-castles.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = "Japanese Castle (Tenshu) Classifier"
description = '''A castle classifier trained on a small set of Japanese Castles with fastai.
Demo for Gradio and HuggingFace Spaces. Based on blog and demo from Tanisq Abraham. Example images below are from jcastle.info.'''
# link
article='''
<p>There are many hundreds of castle sites scattered across Japan, for this demo we have trained on just 9 <a href="https://en.wikipedia.org/wiki/Tenshu">Tenshu.</a>
Images sourced from my own collection and Bing Image Search.
<br>Learn more about Japanese Castles and their history at
<a href='https://jcastle.info/' target='_blank'>Jcastle - Guide to Japanese Castles</a>.
<ul>
<li><a href='https://jcastle.info/view/Hiroshima_Castle' target='_blank'>Hiroshima</a></li>
<li><a href='https://jcastle.info/view/Marugame_Castle' target='_blank'>Marugame</a></li>
<li><a href='https://jcastle.info/view/Matsue_Castle' target='_blank'>Matsue</a></li>
<li><a href='https://jcastle.info/view/Matsumae_Castle' target='_blank'>Matsumae</a></li>
<li><a href='https://jcastle.info/view/Matsumoto_Castle' target='_blank'>Matsumoto</a></li>
<li><a href='https://jcastle.info/view/Nagoya_Castle' target='_blank'>Nagoya</a></li>
<li><a href='https://jcastle.info/view/Okayama_Castle' target='_blank'>Okayama</a></li>
<li><a href='https://jcastle.info/view/Osaka_Castle' target='_blank'>Osaka</a></li>
<li><a href='https://jcastle.info/view/Shimabara_Castle' target='_blank'>Shimabara</a></li>
</ul>
</p>
<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Tanisq Abraham's Blog post</a>
</p>
</p>'''
interpretation='default' #'default' None
examples = ['osaka.jpg','matsumoto.jpg','nagoya.jpg','okayama.jpg','shimabara.jpg']
enable_queue=True
share = False
gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=9),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch(share=share)
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