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from fastai.vision.all import * | |
import gradio as gr | |
learn = load_learner("bear-classifier.pkl") | |
labels = learn.dls.vocab | |
def predict(img): | |
""" | |
Prediction APIs. | |
""" | |
_, _, probs = learn.predict(PILImage.create(img)) | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
demo = gr.Interface( | |
fn=predict, | |
inputs=gr.Image(), | |
outputs=gr.Label(num_top_classes=3), | |
title="Bear Classifier", | |
description="A bear classifier fine tuned on ResNet18 with a few bear samples from the internet. Its task is to recognize whether an image is a grizzy bear, a black bear or just a cute litte teddy bear!", | |
examples=["grizzly.jpg"] | |
) | |
demo.launch() | |