Hugging Face's logo

Spaces:
LuckRafly
/
Stroke_Prediction
Sleeping

App Files Community
LuckRafly commited on
Commit
35b3531
·
1 Parent(s): c1ae77f

Upload 8 files

Browse files
Files changed (8) hide show
  1. Dockerfile +17 -0
  2. app.py +71 -0
  3. artifacts/best_model.pkl +3 -0
  4. artifacts/healthcare-dataset-stroke-data-cleaned.csv +0 -0
  5. artifacts/preprocessor.pkl +3 -0
  6. artifacts/threshold.txt +1 -0
  7. requirements.txt +0 -0
  8. templates/home.html +179 -0
Dockerfile ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Use a slim Python image as the base
2
+ FROM python:3.11-slim
3
+
4
+ # Set the working directory to /app
5
+ WORKDIR /app
6
+
7
+ # Copy only the necessary files to the container
8
+ COPY app.py requirements.txt ./
9
+ COPY src ./src
10
+ COPY artifacts ./artifacts
11
+ COPY templates ./templates
12
+
13
+ # Install packages and clean up
14
+ RUN pip install -r requirements.txt && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
15
+
16
+ # Run your Flask app with Gunicorn
17
+ CMD ["gunicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
app.py ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from flask import Flask, request, app, jsonify, render_template
2
+ import numpy as np
3
+ import pandas as pd
4
+ from joblib import dump, load
5
+ from src.utils import LoadClassifierThreshold
6
+ import os
7
+
8
+ app = Flask(__name__)
9
+
10
+ model_path = os.path.join('artifacts', 'best_model.pkl')
11
+ threshold_path = os.path.join('artifacts', 'threshold.txt')
12
+ preprocessor_path = os.path.join('artifacts', 'preprocessor.pkl')
13
+ # Load the model and preprocessor
14
+ model = LoadClassifierThreshold(model_path= model_path,
15
+ threshold_path=threshold_path)
16
+ preprocessor = load(preprocessor_path)
17
+
18
+ # Create first route
19
+ @app.route('/')
20
+ def home():
21
+ return render_template('home.html')
22
+
23
+ @app.route('/predict_api', methods=['POST'])
24
+ def predict_api():
25
+ data = request.json['data']
26
+ # Create a DataFrame from the JSON data
27
+ data_df = pd.DataFrame(data, index=[0])
28
+ print(data_df)
29
+ new_data = preprocessor.transform(data_df)
30
+ output = model.predict_with_threshold(new_data)
31
+ # Convert the output to an integer
32
+ prediction = int(output[0])
33
+ return jsonify(prediction)
34
+
35
+ @app.route('/predict', methods=['POST'])
36
+ def predict():
37
+ # Get data from the HTML form and create a DataFrame
38
+ data = {
39
+ 'gender': [request.form['gender']],
40
+ 'age': [int(request.form['age'])],
41
+ 'hypertension': [int(request.form['hypertension'])],
42
+ 'heart_disease': [int(request.form['heart_disease'])],
43
+ 'ever_married': [request.form['ever_married']],
44
+ 'work_type': [request.form['work_type']],
45
+ 'Residence_type': [request.form['Residence_type']],
46
+ 'avg_glucose_level': [float(request.form['avg_glucose_level'])],
47
+ 'bmi': [float(request.form['bmi'])],
48
+ 'smoking_status': [request.form['smoking_status']]
49
+ }
50
+ data_df = pd.DataFrame(data)
51
+ print(data_df)
52
+
53
+ # Transform the data using the preprocessor
54
+ final_input = preprocessor.transform(data_df)
55
+
56
+ # Make predictions using the model
57
+ output = model.predict_with_threshold(final_input)
58
+ prediction = int(output[0])
59
+
60
+ # # Define the prediction message
61
+ # if prediction == 1:
62
+ # prediction_message = "There is an indication of stroke."
63
+ # else:
64
+ # prediction_message = "There is no indication of stroke."
65
+
66
+ return render_template("home.html", prediction_text=prediction)
67
+
68
+
69
+
70
+ if __name__ == "__main__":
71
+ app.run(host="0.0.0.0",port=5000)
artifacts/best_model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:261538acd5a93027d8a8f9ac6703a47e042707cc88f20e6d19f08588f73adfd2
3
+ size 14859001
artifacts/healthcare-dataset-stroke-data-cleaned.csv ADDED
The diff for this file is too large to render. See raw diff
 
artifacts/preprocessor.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d1dbb821ccacd5307e0db1324c88318f9e33d0576f246c9effa2372898ff5219
3
+ size 4617
artifacts/threshold.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ 0.19
requirements.txt ADDED
Binary file (1.99 kB). View file
 
templates/home.html ADDED
@@ -0,0 +1,179 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!DOCTYPE html>
2
+ <html>
3
+
4
+ <head>
5
+ <meta charset="UTF-8">
6
+ <title>Stroke Prediction</title>
7
+ <link href='https://fonts.googleapis.com/css?family=Pacifico' rel='stylesheet' type='text/css'>
8
+ <link href='https://fonts.googleapis.com/css?family=Arimo' rel='stylesheet' type='text/css'>
9
+ <link href='https://fonts.googleapis.com/css?family=Hind:300' rel='stylesheet' type='text/css'>
10
+ <link href='https://fonts.googleapis.com/css?family=Open+Sans+Condensed:300' rel='stylesheet' type='text/css'>
11
+ <style>
12
+ .login {
13
+ width: 300px;
14
+ margin: 0 auto;
15
+ padding: 20px;
16
+ border: 1px solid #ccc;
17
+ border-radius: 5px;
18
+ background: #f9f9f9;
19
+ }
20
+
21
+ .login h1 {
22
+ font-family: 'Pacifico', cursive;
23
+ font-size: 28px;
24
+ text-align: center;
25
+ color: #333;
26
+ }
27
+
28
+ .login form {
29
+ font-family: 'Arimo', sans-serif;
30
+ font-size: 14px;
31
+ }
32
+
33
+ .login form select,
34
+ .login form input {
35
+ width: 100%;
36
+ padding: 10px;
37
+ margin-bottom: 10px;
38
+ border: 1px solid #ccc;
39
+ border-radius: 3px;
40
+ }
41
+
42
+ .login form select {
43
+ height: 35px;
44
+ }
45
+
46
+ .login form button {
47
+ width: 100%;
48
+ padding: 10px;
49
+ background: #333;
50
+ border: none;
51
+ border-radius: 3px;
52
+ color: #fff;
53
+ font-weight: bold;
54
+ cursor: pointer;
55
+ }
56
+
57
+ .login form button:hover {
58
+ background: #555;
59
+ }
60
+
61
+ .prediction-result {
62
+ text-align: center;
63
+ font-family: 'Arimo', sans-serif;
64
+ font-size: 18px;
65
+ margin-top: 20px;
66
+ }
67
+
68
+ .indication {
69
+ color: red;
70
+ font-weight: bold;
71
+ }
72
+
73
+ .no-indication {
74
+ color: green;
75
+ font-weight: bold;
76
+ }
77
+
78
+ .error {
79
+ color: #FF5733;
80
+ font-weight: bold;
81
+ }
82
+ </style>
83
+ </head>
84
+
85
+ <body>
86
+ <div class="login">
87
+ <h1>Stroke Prediction</h1>
88
+
89
+ <!-- Main Input For Receiving Query to our ML -->
90
+ <form action="{{ url_for('predict') }}" method="post">
91
+ <!-- Section 1: Gender -->
92
+ <label for="gender">Select Gender:</label>
93
+ <select name="gender">
94
+ <option value="Male">Male</option>
95
+ <option value="Female">Female</option>
96
+ <option value="Other">Other</option>
97
+ </select><br>
98
+
99
+ <!-- Section 2: Age -->
100
+ <label for="age">Enter Age:</label>
101
+ <input type="number" step="1" name="age" placeholder="Age" required="required" /><br>
102
+
103
+ <!-- Section 3: Average Glucose Level -->
104
+ <label for="avg_glucose_level">Enter Average Glucose Level:</label>
105
+ <input type="number" step="any" name="avg_glucose_level" placeholder="Average Glucose Level" required="required" /><br>
106
+
107
+ <!-- Section 4: BMI (Body Mass Index) -->
108
+ <label for "bmi">Enter BMI (Body Mass Index):</label>
109
+ <input type="number" step="any" name="bmi" placeholder="BMI" required="required" /><br>
110
+
111
+ <!-- Section 5: Hypertension -->
112
+ <label for="hypertension">Select Hypertension Status:</label>
113
+ <select name="hypertension">
114
+ <option value="0">No Hypertension</option>
115
+ <option value="1">Hypertension</option>
116
+ </select><br>
117
+
118
+ <!-- Section 6: Heart Disease -->
119
+ <label for="heart_disease">Select Heart Disease Status:</label>
120
+ <select name="heart_disease">
121
+ <option value="0">No Heart Disease</option>
122
+ <option value="1">Heart Disease</option>
123
+ </select><br>
124
+
125
+ <!-- Section 7: Ever Married -->
126
+ <label for="ever_married">Select Marital Status:</label>
127
+ <select name="ever_married">
128
+ <option value="Yes">Yes</option>
129
+ <option value="No">No</option>
130
+ </select><br>
131
+
132
+ <!-- Section 8: Work Type -->
133
+ <label for="work_type">Select Work Type:</label>
134
+ <select name="work_type">
135
+ <option value="Private">Private</option>
136
+ <option value="Self-employed">Self-employed</option>
137
+ <option value="Govt_job">Govt_job</option>
138
+ <option value="children">Children</option>
139
+ <option value="Never_worked">Never_worked</option>
140
+ </select><br>
141
+
142
+ <!-- Section 9: Residence Type -->
143
+ <label for="Residence_type">Select Residence Type:</label>
144
+ <select name="Residence_type">
145
+ <option value="Urban">Urban</option>
146
+ <option value="Rural">Rural</option>
147
+ </select><br>
148
+
149
+ <!-- Section 10: Smoking Status -->
150
+ <label for="smoking_status">Select Smoking Status:</label>
151
+ <select name="smoking_status">
152
+ <option value="formerly smoked">Formerly Smoked</option>
153
+ <option value="never smoked">Never Smoked</option>
154
+ <option value="smokes">Smokes</option>
155
+ <option value="Unknown">Unknown</option>
156
+ </select><br>
157
+
158
+ <button type="submit" class="btn btn-primary btn-block btn-large">Do The Prediction</button>
159
+ </form>
160
+
161
+ <br>
162
+ <br>
163
+
164
+ <!-- Section 11: Prediction Result -->
165
+ <div class="prediction-result">
166
+ <p>Prediction Result:</p>
167
+ {% if prediction_text == 1 %}
168
+ <p class="indication">There is an indication of stroke.</p>
169
+ {% elif prediction_text == 0 %}
170
+ <p class="no-indication">There is no indication of stroke.</p>
171
+ {% else %}
172
+ <p class="error">Prediction result unavailable.</p>
173
+ {% endif %}
174
+ </div>
175
+ </div>
176
+ </body>
177
+
178
+ </html>
179
+