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| import gradio as gr | |
| from fastai.tabular.all import * | |
| import pandas as pd | |
| import torch | |
| df_framework = pd.read_csv('./healthcare-dataset-stroke-data.csv') | |
| splits = RandomSplitter(seed=42)(df_framework) | |
| dls = TabularPandas( | |
| df_framework, splits=splits, | |
| procs = [Categorify, FillMissing, Normalize], | |
| cat_names=["gender","ever_married","work_type","Residence_type", "smoking_status"], | |
| cont_names=['age', 'hypertension', 'heart_disease', 'avg_glucose_level', 'bmi'], | |
| y_names="stroke", y_block = CategoryBlock(), | |
| ).dataloaders(path=".") | |
| learn = tabular_learner(dls, metrics=accuracy, layers=[10,10]) | |
| learn.fit(16, lr=0.025) | |
| def convert_yes_no(data): | |
| if data == "Yes": | |
| return 1 | |
| else: | |
| return 0 | |
| def predict(age, hypertension, heart_disease, avg_glucose_level, bmi, gender, married, work_type, residence_type, smoking_status): | |
| data = [[str(gender), float(age), int(convert_yes_no(hypertension)), int(convert_yes_no(heart_disease)), str(married), str(work_type), str(residence_type), float(avg_glucose_level), float(bmi), str(smoking_status)]] | |
| columns_df = ['gender', 'age', 'hypertension', 'heart_disease', 'ever_married', 'work_type', 'Residence_type', 'avg_glucose_level', 'bmi','smoking_status'] | |
| df_row = pd.DataFrame(data,columns=columns_df) | |
| dl = learn.dls.test_dl(df_row) | |
| preds,_ = learn.get_preds(dl=dl) | |
| return f"O paciente tem a seguinte possibilidade de infarto: {preds[0][1]:.2f}" | |
| gr.Interface( | |
| fn=predict, | |
| title="Stroke predict Model", | |
| allow_flagging="never", | |
| share=True, | |
| inputs=[ | |
| gr.inputs.Number(default=30, label="Age"), | |
| gr.Dropdown(["Yes", "No"], label="Hypertension"), | |
| gr.Dropdown(["Yes", "No"], label="Heart disease"), | |
| gr.inputs.Number(default=100, label="Average glucose level"), | |
| gr.inputs.Number(default=28.8, label="Body Mass Index (BMI)"), | |
| gr.inputs.Radio(choices=["Female", "Male", "Other"], default="Female", label="Gender"), | |
| gr.Dropdown(["No", "Yes"], label="Married"), | |
| gr.Dropdown(["Governamental", "Never worked", "Private", "Self-employed", "Children"], label="Work type"), | |
| gr.Dropdown(["Rural", "Urban"], label="Residence type"), | |
| gr.Dropdown(["Unknown", "Formely smoked", "Never smoked", "Smokes"], label="Smoking status"), | |
| ], | |
| outputs="text").launch() |