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# AUTOGENERATED! DO NOT EDIT! File to edit: evclassifierapp.ipynb.
# %% auto 0
__all__ = ['learn', 'labels', 'title', 'description', 'interpretation', 'examples', 'enable_queue', 'intf', 'classify_image']
# %% evclassifierapp.ipynb 1
from fastai.vision.all import *
# %% evclassifierapp.ipynb 2
learn = load_learner('export.pkl')
# %% evclassifierapp.ipynb 4
labels = learn.dls.vocab
def classify_image(img):
img = PILImage.create(img)
pred,idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
# %% evclassifierapp.ipynb 5
title = "EV Car Classifier"
description = "This model will recognise the EV car in question"
interpretation='default'
examples = ['bmw ix.jpg','merc eqc.jpg','tesla model 3.jpg']
enable_queue=True
# %% evclassifierapp.ipynb 6
import gradio as gr
intf = gr.Interface(fn=classify_image,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=3),
title=title,
description=description,
examples=examples,
interpretation=interpretation,
enable_queue=enable_queue)
intf.launch()
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