import gradio as gr | |
from fastai.vision.all import * | |
import skimage | |
learn = load_learner('export.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 = "Bear Classifier" | |
description = "A classifier that differentiates between grizzly, black, and teddy bears." | |
examples = [f'examples/{bear_type}.jpg' for bear_type in {'grizzly', 'black', 'teddy'}] | |
queue_size = 20 | |
demo = gr.Interface( | |
fn=predict, | |
inputs=gr.Image(width=512, height=512), | |
outputs=gr.Label(num_top_classes=3), | |
title=title, | |
description=description, | |
examples=examples | |
) | |
demo.queue(max_size=queue_size) | |
demo.launch() | |