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from fastai.vision import * | |
import gradio as gr | |
from pathlib import Path | |
from fastbook import load_learner | |
model_path = Path('models') | |
image_path = Path('images') | |
learn = load_learner(model_path/'cloudmodel.pkl') | |
categories = ( | |
'Cirrus', | |
'Cirrostratus', | |
'Cirrocumulus', | |
'Altostratus', | |
'Altocumulus', | |
'Stratus', | |
'Stratocumulus', | |
'Nimbostratus', | |
'Cumulus', | |
'Cumulonimbus', | |
'Lenticular' | |
) | |
image = gr.inputs.Image(shape=(192,192)) | |
label = gr.outputs.Label() | |
learn = load_learner(model_path/'cloudmodel.pkl') | |
examples = [image_path / f"{c}.jpg" for c in categories] | |
def classify_image(img): | |
pred,idx,probs = learn.predict(img) | |
return dict(zip(categories, map(float, probs))) | |
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, | |
examples=examples) | |
iface.launch() | |