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import gradio as gr
from fastai.vision.all import *
def get_headcount(filepath):
filepath = str(filepath)
filename = filepath.split('/')[-1]
return df[df['Name'] == filename]['HeadCount'].values[0]
learn = load_learner('export_ver2.pkl')
def predict(img):
img = PILImage.create(img)
op = learn.predict(img)
return int(op[0][0])
title = "Face count"
description = "This model that is trained to counts the number of faces in the uploaded picture."
eg = ['cam_mit.jpg', 'dunphys.jpg', 'group.jpg']
gr.Interface(
fn=predict,
inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Textbox(type="number", label="Number of faces"),
title=title,
description=description,
examples=eg,
).launch(share=False)