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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner('resnet.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 = "Skin Disease Classifier"
description = "A prototype app for classifying common skin diseases, developed with fastai. Created as a demo for Gradio and HuggingFace Spaces."
examples = ['acne.jpg']
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, examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch() |