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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()
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