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Browse files- app.py +118 -0
- heart1.pkl +3 -0
app.py
ADDED
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import gradio as gr
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import joblib as jb
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import pandas as pd
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pipe = jb.load('heart1.pkl')
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def predict(age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall):
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if sex=="Male":
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sex=1
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else:
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sex=0
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if cp=="Typical Angina":
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cp=0
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elif cp=="Typical Angina":
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cp=1
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elif cp=="Atypical Angina":
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cp=2
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elif cp=="Non-Anginal pain":
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cp=3
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elif cp=="Asymptomatic":
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cp=4
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else:
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cp=0
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if fbs>120:
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fbs=1
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else:
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fbs=0
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if restecg=="Normal":
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restecg=0
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elif restecg=="ST-T wave abnormality":
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restecg=1
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elif restecg=="Definite left Ventricular hypertrophy":
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restecg=2
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else:
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restecg=0
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if slp=="Unsloping":
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slp=0
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elif restecg=="flat":
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slp=1
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elif restecg=="Downsloping":
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slp=2
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else:
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slp=0
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if exng=="Yes":
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exng=1
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else:
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exng=0
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if thall=="Null":
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thall=0
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elif thall=="Fixed defect":
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thall=1
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elif cp=="Normal":
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thall=2
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elif cp=="Reversable defect":
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thall=3
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else:
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thall=0
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x = pd.DataFrame([[age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall]])
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x.columns = ["age", "sex", "cp", "trtbps", "chol", "fbs", "restecg", "thalachh", "exng", "oldpeak", "slp", "caa", "thall"]
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prediction = pipe.predict(x)
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ans = prediction[0]
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if ans>=1:
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ans = 100
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elif ans<=0:
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ans = 0
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else:
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ans = ans*100
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if ans>50:
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final = str(int(ans)) + "%" +"\n>50% Diameter narrowing.\nMore chance of heart disease."
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else:
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final = str(int(ans)) + "%" + "\n< 50% Diameter narrowing.\nLess chance of heart disease."
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return final
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app = gr.Interface(title="Heart Attack Predictor",fn=predict,
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inputs=[
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gr.inputs.Number(label='Age'),
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gr.inputs.Radio(["Male","Female"],label='Sex'),
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gr.inputs.Radio(["Typical Angina","Atypical Angina","Non-Anginal pain","Asymptomatic"],label='Chest Pain'),
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gr.inputs.Number(label='Resting blood pressure (in mm Hg)'),
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gr.inputs.Number(label='Cholestoral in mg/dl '),
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gr.inputs.Number(label='Fasting blood sugar'),
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gr.inputs.Radio(["Normal","ST-T wave abnormality","Definite left Ventricular hypertrophy"],label='Resting Rlectrocardiographic Results'),
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gr.inputs.Number(label='Maximum Heartrate achieved'),
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gr.inputs.Radio(["Yes","No"],label='Exercise induced Angina'),
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gr.inputs.Number(label='ST depression induced by exercise'),
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gr.inputs.Radio(["Unsloping","flat","Downsloping"],label='Slope of the peak exercise ST segment'),
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gr.inputs.Slider(minimum=0,maximum=3,step=1,label='Number of major vessels'),
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gr.inputs.Radio(["Null","Fixed defect","Normal","Reversable defect"],label='Thalassemia'),
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],
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outputs=gr.outputs.Textbox(label="Prediction")
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)
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app.launch()
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heart1.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0ea135ed7e84201ee0622c35a012a0757d2d291a33f0a751910db244c702c57e
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size 3367
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