File size: 912 Bytes
7152f4e e6e53fd 7152f4e 9bcb70a 7152f4e 9bcb70a e6e53fd 3a120bc e6e53fd 30e53f9 3de827b fe9cec4 0759b01 fa5f59e 4bb1fe5 30e53f9 9eb2af9 e6e53fd 9eb2af9 4bb1fe5 e6e53fd 9087e34 6bde5ca 897be32 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | import gradio as gr
from fastai.vision.all import *
import skimage
neural_net = load_learner('trained-NN.pkl')
labels = neural_net.dls.vocab
def predict(img):
category, idx, probs = neural_net.predict(img)
return dict(zip(labels, map(float, probs)))
title = 'Natural Landscape Photo Classifier'
description = 'Click an example photo or upload an image of your own!'
examples = ['farm.jpg', 'lake.jpg', 'solar.jpg', 'neighborhood.jpg']
inputs=gr.Image(type='pil',
label='Photo')
outputs = gr.Label(value={labels[i]: 0 for i in range(len(labels))},
label='The photo is a...',
show_label=True)
iface = gr.Interface(fn=predict,
inputs=inputs,
outputs=outputs,
title=title,
description=description,
examples=examples)
iface.launch(share=True) |