kmckee95 commited on
Commit
9f04aa3
1 Parent(s): 902c094

Create app.py

Browse files
Files changed (1) hide show
  1. app.py +80 -0
app.py ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+ import pickle
3
+ import pandas as pd
4
+ import numpy as np
5
+ import matplotlib.pyplot as plt
6
+ import seaborn as sns
7
+ print('Loading......')
8
+
9
+ # load the saved model
10
+ rfc_saved = pickle.load(open('rfc.pickle','rb'))
11
+
12
+ full_pipeline_saved = pickle.load(open('full_pipeline.pickle','rb'))
13
+
14
+
15
+ # function to check the heart disease risk
16
+ def CheckHeartDisease(age,sex,ChestPainType,RestingBP,Cholesterol,
17
+ FastingBS,RestingECG,MaxHR,ExerciseAngina,Oldpeak,ST_Slope):
18
+ try:
19
+ df_model = pd.DataFrame([],columns=['Age','Sex','ChestPainType','RestingBP','Cholesterol','FastingBS','RestingECG','MaxHR','ExerciseAngina', 'Oldpeak','ST_Slope'])
20
+
21
+ df_model.loc[0] = [age,sex,ChestPainType,RestingBP,Cholesterol,FastingBS,RestingECG,MaxHR,ExerciseAngina,Oldpeak,ST_Slope]
22
+
23
+ # preprocess the person details
24
+ X_processed = full_pipeline_saved.transform(df_model)
25
+
26
+ # do the prediction
27
+ y_pred = rfc_saved.predict(X_processed)
28
+
29
+ # plot risk of heart disease based on sex
30
+ df = pd.read_csv('heart.csv')
31
+ target = df['HeartDisease'].replace([0,1],['Low','High'])
32
+ data = pd.crosstab(index=df['Sex'],
33
+ columns=target)
34
+
35
+ data.plot(kind='bar',stacked=True)
36
+ fig1 = plt.gcf()
37
+ plt.close()
38
+
39
+ # plot count of person within given age range, with heart disease risk
40
+ bins=[0,30,50,80]
41
+ sns.countplot(x=pd.cut(df.Age,bins=bins),hue=target,color='r')
42
+ fig2 = plt.gcf()
43
+ plt.close()
44
+
45
+ # plot graph based on ChestPainType
46
+ sns.countplot(x=target,hue=df.ChestPainType)
47
+ plt.xticks(np.arange(2), ['No', 'Yes'])
48
+ fig3 = plt.gcf()
49
+
50
+ if y_pred[0]==0:
51
+ return 'Low Risk of Heart Disease',fig1,fig2,fig3
52
+ else:
53
+ return 'High Risk of Heart Disease',fig1,fig2,fig3
54
+
55
+ except:
56
+ return 'Wrong inputs',fig1,fig2,fig3
57
+
58
+ # create GUI
59
+ iface = gr.Interface(
60
+ CheckHeartDisease, # its the function to be called with below parameters
61
+ [
62
+ gr.inputs.Number(label='Age (0-115)'),
63
+ gr.inputs.Dropdown(['M','F'],default='M'),
64
+ gr.inputs.Dropdown(['ATA', 'NAP', 'ASY','TA'],default='TA'),
65
+ gr.inputs.Number(label='RESTINGBP (0-200)'),
66
+ gr.inputs.Number(label='CHOLESTEROL (0-603)'),
67
+ gr.inputs.Number(label='FASTINGBS (0-1)'),
68
+ gr.inputs.Dropdown(['Normal', 'ST' ,'LVH'],default='ST'),
69
+ gr.inputs.Number(label='MAXHR (60-202)'),
70
+
71
+ gr.inputs.Dropdown(['Y','N'],default='Y'),
72
+ gr.inputs.Number(label='OLDPEAK (-2.6 to 6.2)'),
73
+ gr.inputs.Dropdown(['Up', 'Flat', 'Down'],default='Up')
74
+ ],
75
+ [gr.outputs.Textbox(),"plot","plot","plot"]
76
+
77
+ , live=False,layout='vertical',title='Get Your Heart Disease Status',
78
+ )
79
+
80
+ iface.launch() # launch the gui