from fastai.vision.all import * | |
learn = load_learner('cig_detector_2.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))} | |
import gradio as gr | |
title = "Smoking Classifier" | |
description = "A smoking, not smoking classifier trained with fastai." | |
examples = ['smoking1.jpg', 'smoking2.jpg', 'not_smoking.jpg'] | |
gr.Interface(title=title, description=description, examples=examples,fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True) | |