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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner('dog_breed.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 = "Doge Breed Classifier"
description = "A dog breed classifier trained on duckduckgo images with fastai."
interpretation='default'
enable_queue=True
gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
title=title,
description=description,
interpretation=interpretation,
enable_queue=enable_queue
).launch() |