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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner("house_model.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 = "House Style Classifier"
description = (
"Classifier that will classify a style of house into modern, ranch or victorian."
)
examples = ["modern_house.jpg", "ranch_house.jpg", "victorian_house.jpg"]
interpretation = "default"
gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
title=title,
description=description,
examples=examples,
interpretation=interpretation,
).launch()
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