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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], num_workers = 0) | |
| preds,_ = learn.get_preds(dl=tst_dl) | |
| result_text = "This person is " + str(round(preds[0][0].item(), 0)) + " years old with a BMI of " + str(round(preds[0][1].item(), 1)) + " kg/m^2" | |
| return result_text | |
| image = gr.inputs.Image() | |
| examples = ['A00147.png','K86344.png','A00360.png', "R89614.png", 'A01681.png', 'R79591.png','R86556.png', "R43263.png", 'Y15554.png', "X78069.png"] | |
| 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) | |