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#Import necessary libraries | |
import gradio as gr | |
from fastai.vision.all import * | |
import skimage | |
bear_learner = load_learner('export.pkl') | |
#Create function that accepth image path and | |
labels = bear_learner.dls.vocab | |
def predict(img): | |
img = PILImage.create(img) | |
pred, idx, probs = bear_learner.predict(img) | |
return {labels[i]: round(float(probs[i]), 2) for i in range(len(labels))} | |
examples = ["black_bear.jpg", "teddy_bear.jpg"] | |
#interface = | |
gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label()).launch() |