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from fastai.vision.all import * | |
import gradio as gr | |
def get_bmi(): return _ | |
def get_age(): return _ | |
def combine_loss(): return _ | |
def age_loss(): return _ | |
def bmi_loss(): return _ | |
learn = load_learner("export.pkl") | |
def classify_image(img): | |
tst_dl = learn.dls.test_dl(img) | |
preds,_ = learn.get_preds(dl=tst_dl) | |
result_text = "This is a picture of a " + round(preds[0], 0) + " person with a BMI of" + round(preds[0], 1) + " kg/m^2" | |
return result_text | |
image = gr.inputs.Image() | |
label = gr.outputs.Label() | |
examples = ['A00147.png','A00360.png','angela lansbury.jpg'] | |
title = 'Predict Age and Body Mass Index from a Picture' | |
description = 'This app predicts the age and BMI of a person just from their face.' | |
article = "Author: <a href=\"https://huggingface.co/archietram\">Archie Tram</a>. " | |
intf = gr.Interface(fn=classify_image, inputs=image, outputs="text", examples=examples, title=title, description=description, article=article) | |
intf.launch(inline=False) |