Hackathon2022/BigColumnDiabetes

1import pandas as pd2import pickle3import numpy as np4from sklearn import tree5 6import gradio as gr7 8# Load the Random Forest CLassifier model9filename = 'model.pkl'10loaded_model = pickle.load(open(filename, 'rb'))11print(loaded_model)12 13 14def multiline(textData):15        print("inp", textData)16        col=["HighBP","HighChol","CholCheck","BMI","Smoker","Stroke","HeartDiseaseorAttack","PhysActivity","Fruits"17        ,"Veggies","HvyAlcoholConsump","AnyHealthcare","NoDocbcCost","GenHlth","MentHlth","PhysHlth","DiffWalk"18        ,"Sex","Age","Education","Income"]19        #empty_array = []20        empty_array = np.empty((0, 21), float)21        for line in textData.split("\n"):22          abc = list(map(float, line.split(",")));23          print(abc)24          empty_array = np.append(empty_array, np.array([abc]), axis=0)   25        print("empty_array")   26        print(empty_array)27        ddf = pd.DataFrame(empty_array, columns=col)28        print("ddf")29        print(ddf)30 31        #print(loaded_model.predict(ddf))32        return ddf33 34 35def predict2(content):36        multiple_records = multiline(content)37        result = loaded_model.predict(multiple_records)38        print(result)39        return result40 41 42iface = gr.Interface(fn=predict2, inputs="text", outputs="text")43iface.launch()44