Beladiaamy commited on
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cbecc6c
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1 Parent(s): ec9edc0

Update app.py

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Files changed (1) hide show
  1. app.py +23 -26
app.py CHANGED
@@ -7,17 +7,17 @@ import numpy as np
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  import matplotlib.pyplot as plt
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9
  # load the model from disk
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- loaded_model = pickle.load(open("heart_xgb.pkl", 'rb'))
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12
  # Setup SHAP
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  explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
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15
  # Create the main function for server
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- def main_func(age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall):
17
- new_row = pd.DataFrame.from_dict({'age':age,'sex':sex,
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- 'cp':cp,'trtbps':trtbps,'chol':chol,
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- 'fbs':fbs, 'restecg':restecg,'thalachh':thalachh,'exng':exng,
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- 'oldpeak':oldpeak,'slp':slp,'caa':caa,'thall':thall},
21
  orient = 'index').transpose()
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23
  prob = loaded_model.predict_proba(new_row)
@@ -34,8 +34,8 @@ def main_func(age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,sl
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  return {"Low Chance": float(prob[0][0]), "High Chance": 1-float(prob[0][0])}, local_plot
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36
  # Create the UI
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- title = "**Heart Attack Predictor & Interpreter** 🪐"
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- description1 = """This app takes info from subjects and predicts their heart attack likelihood. Do not use for medical diagnosis."""
39
 
40
  description2 = """
41
  To use the app, click on one of the examples, or adjust the values of the factors, and click on Analyze. 🤞
@@ -48,22 +48,19 @@ with gr.Blocks(title=title) as demo:
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  gr.Markdown(description2)
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  gr.Markdown("""---""")
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51
- age = gr.Number(label="age Score", value=40)
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- sex = gr.Slider(label="sex Score", minimum=0, maximum=1, value=1, step=1)
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- cp = gr.Slider(label="cp Score", minimum=1, maximum=5, value=4, step=1)
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- trtbps = gr.Slider(label="trtbps Score", minimum=1, maximum=5, value=4, step=1)
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- chol = gr.Slider(label="chol Score", minimum=1, maximum=5, value=4, step=1)
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- fbs = gr.Slider(label="fbs Score", minimum=1, maximum=5, value=4, step=1)
 
 
 
 
 
 
57
 
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- restecg = gr.Slider(label="restecg Score", minimum=1, maximum=5, value=4, step=1)
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- thalachh = gr.Slider(label="thalachh Score", minimum=1, maximum=5, value=4, step=1)
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-
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- exng = gr.Slider(label="exng Score", minimum=1, maximum=5, value=4, step=1)
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- oldpeak = gr.Slider(label="oldpeak Score", minimum=1, maximum=5, value=4, step=1)
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- slp = gr.Slider(label="slp Score", minimum=1, maximum=5, value=4, step=1)
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- caa = gr.Slider(label="caa Score", minimum=1, maximum=5, value=4, step=1)
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- thall = gr.Slider(label="thall Score", minimum=1, maximum=5, value=4, step=1)
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-
67
  submit_btn = gr.Button("Analyze")
68
 
69
  with gr.Column(visible=True) as output_col:
@@ -72,11 +69,11 @@ with gr.Blocks(title=title) as demo:
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73
  submit_btn.click(
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  main_func,
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- [age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall],
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- [label,local_plot], api_name="Heart_Predictor"
77
  )
78
 
79
  gr.Markdown("### Click on any of the examples below to see how it works:")
80
- gr.Examples([[24,0,4,4,5,5,4,4,5,5,1,2,3], [24,0,4,4,5,3,3,2,1,1,1,2,3]], [age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall], [label,local_plot], main_func, cache_examples=True)
81
 
82
  demo.launch()
 
7
  import matplotlib.pyplot as plt
8
 
9
  # load the model from disk
10
+ loaded_model = pickle.load(open("Disease_DAndRFTrees.pkl", 'rb'))
11
 
12
  # Setup SHAP
13
  explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
14
 
15
  # Create the main function for server
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+ def main_func(HighBP, HighChol, BMI, Smoker, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, GenHlth, PhysHlth, Sex, Age):
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+ new_row = pd.DataFrame.from_dict({'BP':highBP,'Chol':HighChol,
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+ 'BMI':BMI,'Smoker':Smoker,'PhysActivity':PhysActivity,
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+ 'Fruits':Fruits, 'Veggies':Veggies,'HvyAlcoholConsump': HvyAlcoholConsump,'GenHlth':GenHlth,
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+ 'PhysHlth':PhysHlth,'Sex':Sex,'Age':Age},
21
  orient = 'index').transpose()
22
 
23
  prob = loaded_model.predict_proba(new_row)
 
34
  return {"Low Chance": float(prob[0][0]), "High Chance": 1-float(prob[0][0])}, local_plot
35
 
36
  # Create the UI
37
+ title = "**Diabetes Predictor & Interpreter** 🪐"
38
+ description1 = """This app takes info from subjects and predicts their diabetes likelihood. Do not use for medical diagnosis."""
39
 
40
  description2 = """
41
  To use the app, click on one of the examples, or adjust the values of the factors, and click on Analyze. 🤞
 
48
  gr.Markdown(description2)
49
  gr.Markdown("""---""")
50
 
51
+ Age = gr.Number(label="age Score", value=40)
52
+ BMI = gr.Number(label="BMI Score", value=98)
53
+ Sex = gr.Slider(label="sex Score", minimum=0, maximum=1, value=1, step=1)
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+ Smoker = gr.Slider(label="Smoker Score", minimum=0, maximum=1, value=1, step=1)
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+ PhysActivity = gr.Slider(label="Physical Activity Score", minimum=0, maximum=1, value=1, step=1)
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+ Fruits = gr.Slider(label="Fruits Score", minimum=0, maximum=1, value=1, step=1)
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+ Veggies = gr.Slider(label="Veggies Score", minimum=0, maximum=1, value=1, step=1)
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+ HvyAlcoholConsump = gr.Slider(label="Alcohol Consumption Score", minimum=0, maximum=1, value=1, step=1)
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+ HighBP = gr.Slider(label="BP Score", minimum=1, maximum=1, value=1, step=1)
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+ HighChol = gr.Slider(label="Cholesterol Score", minimum=1, maximum=1, value=1, step=1)
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+ GenHlth = gr.Slider(label="GenHlth Score", minimum=1, maximum=5, value=4, step=1)
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+ PhysHealth = gr.Number(label="PhysHealth Score", value=40)
63
 
 
 
 
 
 
 
 
 
 
64
  submit_btn = gr.Button("Analyze")
65
 
66
  with gr.Column(visible=True) as output_col:
 
69
 
70
  submit_btn.click(
71
  main_func,
72
+ [HighBP, HighChol, BMI, Smoker, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, GenHlth, PhysHlth, Sex, Age],
73
+ [label,local_plot], api_name="Diabetes_Predictor"
74
  )
75
 
76
  gr.Markdown("### Click on any of the examples below to see how it works:")
77
+ gr.Examples([[24,0,4,4,5,5,4,4,5,5,1,2,3], [24,0,4,4,5,3,3,2,1,1,1,2,3]], [HighBP, HighChol, BMI, Smoker, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, GenHlth, PhysHlth, Sex, Age], [label,local_plot], main_func, cache_examples=True)
78
 
79
  demo.launch()