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Kidney_stones.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2e96916cfaff34f24d6e6903ebf2560f5045395c239a4a44b8b28049b9c41678
+size 2514

app.py

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+import gradio as gr
+import pandas as pd
+import torch
+import torch.nn.functional as F
+from fastai.tabular.all import *
+import pickle
+
+with open('Kidney_stones.pkl', 'rb') as arquivo:
+    modelo = pickle.load(arquivo)
+
+def calc_preds(coeffs, indeps):
+    layers,consts = coeffs
+    n = len(layers)
+    res = indeps
+    for i,l in enumerate(layers):
+        res = res@l + consts[i]
+        if i!=n-1: res = F.relu(res)
+    return torch.sigmoid(res)
+
+def predict(Gravity, Ph, Osmo, Cond, Urea, Calc):
+    input = torch.tensor([Gravity, Ph, Osmo, Cond, Urea, Calc], dtype=torch.float)
+    pred = calc_preds(coeffs=modelo, indeps=input)
+    return 'Kidney Stone' if pred.item() < 0.55 else 'No Kidney Stones'
+
+interface = gr.Interface(
+    fn=predict,
+    inputs=["number", "number", "number", "number", "number", "number"],
+    outputs="text",
+    layout="vertical",
+    title="Verificador de Pedras nos Rins",
+    description="Esse modelo é capaz de realizar uma análise com base nos dados da urina de uma pessoa e identificar se ela possui pedra nos rins",
+    interpretation="default",
+    enable_queue=True
+)
+
+interface.launch(share=True)

requirements.txt

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+pandas
+Pytorch
+Datasets
+torch
+pickle