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import gradio as gr
import pandas as pd
import numpy as np
import pickle
def decode_file(file_path):
with open(file_path, 'rb') as file:
obj = pickle.load(file)
return obj
model = decode_file('model.pkl')
def predict(gender, age, hypertension, ever_married, work_type, heart_disease, avg_glucose_level, bmi, smoking_status, Residence_type):
gender_mapping = {'Male': 1, 'Female': 0}
hypertension_mapping = {'Yes': 1, 'No': 0}
ever_married_mapping = {'Yes': 1, 'No': 0}
work_type_mapping = {'Private': 2, 'Self-employed': 4, 'Govt_job': 3, 'children': 1, 'Never_worked': 0}
heart_disease_mapping = {'Yes': 1, 'No': 0}
smoking_status_mapping = {'formerly smoked': 3, 'smokes': 1, 'never smoked': 2, 'Unknown': 0}
Residence_type_mapping = {'Urban': 1, 'Rural': 0}
# Map categorical variables to their corresponding numerical values
gender = gender_mapping[gender]
hypertension = hypertension_mapping[hypertension]
ever_married = ever_married_mapping[ever_married]
work_type = work_type_mapping[work_type]
heart_disease = heart_disease_mapping[heart_disease]
smoking_status = smoking_status_mapping[smoking_status]
Residence_type = Residence_type_mapping[Residence_type]
inputs = [gender, age, hypertension, ever_married, work_type, heart_disease, avg_glucose_level, bmi, smoking_status, Residence_type]
input_labels = ['gender', 'age', 'hypertension', 'ever_married', 'work_type', 'heart_disease', 'avg_glucose_level', 'bmi', 'smoking_status', 'Residence_type']
input_df = pd.DataFrame([inputs], columns=input_labels)
prediction = model.predict_proba(input_df)[0][1]
result = "The probability of stroke is {:.2f}%".format(prediction * 100) # to give a percentage
return result
input_labels = [
'gender', 'age', 'hypertension', 'ever_married', 'work_type',
'heart_disease', 'avg_glucose_level', 'bmi', 'smoking_status', 'Residence_type'
]
iface = gr.Interface(
fn=predict,
inputs=[
gr.components.Radio(choices=['Female', 'Male'], label="Gender"),
gr.components.Slider(label="Age"),
gr.components.Radio(choices=['Yes', 'No'], label="Hypertension"),
gr.components.Radio(choices=['Yes', 'No'], label="Ever Married"),
gr.components.Radio(choices=['Private', 'Self-employed', 'Govt_job', 'children', 'Never_worked'], label="Work Type"),
gr.components.Radio(choices=['Yes', 'No'], label="Heart Disease"),
gr.components.Number(label="Average Glucose Level"),
gr.components.Slider(label="BMI"),
gr.components.Radio(choices=['formerly smoked', 'never smoked', 'smokes', 'Unknown'], label="Smoking Status"),
gr.components.Radio(choices=['Urban', 'Rural'], label="Residence Type")
],
outputs='text',
title='Stroke Probability Predictor',
description='Predicts the probability of having a stroke based on input features.'
)
iface.launch() |