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| import pickle | |
| import gradio as gr | |
| import numpy as np | |
| import pandas as pd | |
| import tensorflow as tf | |
| from imblearn.over_sampling import RandomOverSampler | |
| from sklearn.linear_model import LogisticRegression | |
| from sklearn.metrics import classification_report | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.naive_bayes import GaussianNB | |
| from sklearn.preprocessing import StandardScaler | |
| from tensorflow.keras.models import load_model | |
| def greet( | |
| gender, | |
| age, | |
| smoking, | |
| pp, | |
| allergy, | |
| wheezing, | |
| alcohol, | |
| cp, | |
| bp, | |
| sugar, | |
| bu, | |
| na, | |
| k, | |
| hb, | |
| rbc, | |
| wbc, | |
| htn, | |
| appet, | |
| ane, | |
| hd, | |
| bmi, | |
| chol, | |
| ca, | |
| thal, | |
| insulin, | |
| ): | |
| with open("nvd.pkl", "rb") as f: | |
| nvd = pickle.load(f) | |
| with open("kcd.pkl", "rb") as f: | |
| kcd = pickle.load(f) | |
| with open("mp.pkl", "rb") as f: | |
| mp = pickle.load(f) | |
| with open("osp.pkl", "rb") as f: | |
| osp = pickle.load(f) | |
| with open("sk.pkl", "rb") as f: | |
| sk = pickle.load(f) | |
| lung = nvd.predict( | |
| np.array([[gender, age, smoking, pp, allergy, wheezing, alcohol, cp]]) | |
| ) | |
| kid = kcd.predict( | |
| np.array([[age, bp, sugar, bu, na, k, hb, wbc, rbc, htn, appet, ane]]) | |
| ) | |
| bra = mp.predict(np.array([[gender, age, htn, hd, sugar, bmi, smoking]])) | |
| hrt = osp.predict(np.array([[age, gender, cp, chol, ca, thal]])) | |
| dia = sk.predict(np.array([[sugar, bp, insulin, bmi, age]])) | |
| return [str(lung[0]), str(kid[0]), str(bra[0]), str(hrt[0]), str(dia[0])] | |
| iface = gr.Interface( | |
| fn=greet, | |
| inputs=[ | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| "number", | |
| ], | |
| outputs=["number", "number", "number", "number", "number"], | |
| ) | |
| iface.launch(share=True) |