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from fastai.vision.all import *
import gradio as gr
def greet(name):
return "Hello " + name + "!!"
learn = load_learner("model-v7.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))}
examples = [
"a2_b_m.jpg",
"a2_coeur_lyon.jpg",
"gzup_america.jpg",
"gzup_gameboy.jpg",
"pa_425.jpg",
"pa_1341.jpg",
"stork_music.jpg",
"stork_prince.jpg",
]
DESCRIPTION = """
Street art deep learning model. It's trained to recognize the style of the following artists active in Paris:
[A2](https://a2-streetart.com/), [gzup](https://www.gzup.fr/in-the-streets/), [invader](https://www.instagram.com/invaderwashere), [stork](https://www.instagram.com/stork_pixelart/).
For more AI experiments check out my [newsletter](https://newsletter.pnote.eu) 💫.
"""
gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
examples=examples,
title="Art reco, recognizer of street art",
description=DESCRIPTION
).launch(share=True)
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