from fastai.vision.all import * | |
import gradio as gr | |
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 = "Bears Classifier" | |
description = "A simple bears classifier trained on the dataset created with fastai & bing search." | |
examples = ['grizzly.jpg'] | |
gr.Interface(fn=predict, | |
inputs=gr.Image(shape=(512, 512)), | |
outputs=gr.Label(num_top_classes=3), | |
title=title, | |
description=description, | |
examples=examples, | |
).launch(enable_queue=True) |