├── .gitattributes
├── .gitignore
├── Procfile
├── README.md
├── app.py
├── breast_cancer_detector.pickle
├── requirements.txt
├── static
    └── images
    │   └── world.jpg
└── templates
    └── index.html


/.gitattributes:
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1 | # Auto detect text files and perform LF normalization
2 | * text=auto
3 | 


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/.gitignore:
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  1 | # Byte-compiled / optimized / DLL files
  2 | __pycache__/
  3 | *.py[cod]
  4 | *$py.class
  5 | 
  6 | # C extensions
  7 | *.so
  8 | 
  9 | # Distribution / packaging
 10 | .Python
 11 | build/
 12 | develop-eggs/
 13 | dist/
 14 | downloads/
 15 | eggs/
 16 | .eggs/
 17 | lib/
 18 | lib64/
 19 | parts/
 20 | sdist/
 21 | var/
 22 | wheels/
 23 | pip-wheel-metadata/
 24 | share/python-wheels/
 25 | *.egg-info/
 26 | .installed.cfg
 27 | *.egg
 28 | MANIFEST
 29 | 
 30 | # PyInstaller
 31 | #  Usually these files are written by a python script from a template
 32 | #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 33 | *.manifest
 34 | *.spec
 35 | 
 36 | # Installer logs
 37 | pip-log.txt
 38 | pip-delete-this-directory.txt
 39 | 
 40 | # Unit test / coverage reports
 41 | htmlcov/
 42 | .tox/
 43 | .nox/
 44 | .coverage
 45 | .coverage.*
 46 | .cache
 47 | nosetests.xml
 48 | coverage.xml
 49 | *.cover
 50 | *.py,cover
 51 | .hypothesis/
 52 | .pytest_cache/
 53 | 
 54 | # Translations
 55 | *.mo
 56 | *.pot
 57 | 
 58 | # Django stuff:
 59 | *.log
 60 | local_settings.py
 61 | db.sqlite3
 62 | db.sqlite3-journal
 63 | 
 64 | # Flask stuff:
 65 | instance/
 66 | .webassets-cache
 67 | 
 68 | # Scrapy stuff:
 69 | .scrapy
 70 | 
 71 | # Sphinx documentation
 72 | docs/_build/
 73 | 
 74 | # PyBuilder
 75 | target/
 76 | 
 77 | # Jupyter Notebook
 78 | .ipynb_checkpoints
 79 | 
 80 | # IPython
 81 | profile_default/
 82 | ipython_config.py
 83 | 
 84 | # pyenv
 85 | .python-version
 86 | 
 87 | # pipenv
 88 | #   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
 89 | #   However, in case of collaboration, if having platform-specific dependencies or dependencies
 90 | #   having no cross-platform support, pipenv may install dependencies that don't work, or not
 91 | #   install all needed dependencies.
 92 | #Pipfile.lock
 93 | 
 94 | # celery beat schedule file
 95 | celerybeat-schedule
 96 | 
 97 | # SageMath parsed files
 98 | *.sage.py
 99 | 
100 | # Environments
101 | .env
102 | .venv
103 | env/
104 | venv/
105 | ENV/
106 | env.bak/
107 | venv.bak/
108 | 
109 | # Spyder project settings
110 | .spyderproject
111 | .spyproject
112 | 
113 | # Rope project settings
114 | .ropeproject
115 | 
116 | # mkdocs documentation
117 | /site
118 | 
119 | # mypy
120 | .mypy_cache/
121 | .dmypy.json
122 | dmypy.json
123 | 
124 | # Pyre type checker
125 | .pyre/
126 | 


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/Procfile:
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1 | web: gunicorn app:app


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/README.md:
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1 | # Breast-Cancer-Detection-App
2 |  Breast Cancer Detection App Using Machine Learning XGBoost Classifier
3 | 


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/app.py:
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 1 | # -*- coding: utf-8 -*-
 2 | """
 3 | Created on Sun Jul 11 11:18:10 2021
 4 | 
 5 | @author: SACHANs
 6 | """
 7 | 
 8 | 
 9 |   
10 | import numpy as np
11 | import pandas as pd
12 | from flask import Flask, request, render_template
13 | import pickle
14 | 
15 | app = Flask(__name__)
16 | model = pickle.load(open('breast_cancer_detector.pickle', 'rb'))
17 | 
18 | @app.route('/')
19 | def home():
20 |     return render_template('index.html')
21 | 
22 | @app.route('/predict',methods=['POST'])
23 | def predict():
24 |     input_features = [float(x) for x in request.form.values()]
25 |     features_value = [np.array(input_features)]
26 |     
27 |     features_name = ['mean radius', 'mean texture', 'mean perimeter', 'mean area',
28 |        'mean smoothness', 'mean compactness', 'mean concavity',
29 |        'mean concave points', 'mean symmetry', 'mean fractal dimension',
30 |        'radius error', 'texture error', 'perimeter error', 'area error',
31 |        'smoothness error', 'compactness error', 'concavity error',
32 |        'concave points error', 'symmetry error', 'fractal dimension error',
33 |        'worst radius', 'worst texture', 'worst perimeter', 'worst area',
34 |        'worst smoothness', 'worst compactness', 'worst concavity',
35 |        'worst concave points', 'worst symmetry', 'worst fractal dimension']
36 |     
37 |     df = pd.DataFrame(features_value, columns=features_name)
38 |     output = model.predict(df)
39 |         
40 |     if output == 0:
41 |         res_val = "** breast cancer !**"
42 |     else:
43 |         res_val = "no breast cancer !"
44 |         
45 | 
46 |     return render_template('index.html', prediction_text='Patient has {}'.format(res_val))
47 | 
48 | if __name__ == "__main__":
49 |     app.run()
50 | 


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/breast_cancer_detector.pickle:
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https://raw.githubusercontent.com/CRYPTOcoderAS/Breast-Cancer-Detection-ML-Project/8332b0f4b685c201155da96f696bad243d689689/breast_cancer_detector.pickle


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/requirements.txt:
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 1 | Flask>=2.0.1
 2 | numpy>=1.21.0
 3 | pandas>=1.3.0
 4 | scikit-learn>=0.21.3
 5 | xgboost>=0.90
 6 | gunicorn==19.9.0
 7 | itsdangerous==2.0
 8 | Jinja2==3.0
 9 | MarkupSafe==1.1.1
10 | Werkzeug==2.0


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/static/images/world.jpg:
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https://raw.githubusercontent.com/CRYPTOcoderAS/Breast-Cancer-Detection-ML-Project/8332b0f4b685c201155da96f696bad243d689689/static/images/world.jpg


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/templates/index.html:
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  1 | <!-- This is GUI for Breast Cancer Detection Application Using Machine Learning Classifer -->
  2 | 
  3 | <!DOCTYPE html>
  4 | <html >
  5 | <head>
  6 |   <meta charset="UTF-8">
  7 |   <title>ML API</title>
  8 | 
  9 |   <style>
 10 |     /* CSS code for button */
 11 |     body {
 12 |       background-image: url('static/images/world.jpg');
 13 |       background-repeat: no-repeat;
 14 |       background-attachment: fixed;
 15 |       background-size: cover;
 16 |     }
 17 | 
 18 |     /* CSS code for button */
 19 |     .button_css {
 20 |     color: #494949 !important;
 21 |     text-transform: uppercase;
 22 |     text-decoration: none;
 23 |     background: #ffffff;
 24 |     padding: 20px;
 25 |     border: 4px solid #494949 !important;
 26 |     display: inline-block;
 27 |     transition: all 0.4s ease 0s;
 28 |     }
 29 |     
 30 |     .button_css:hover {
 31 |     color: #ffffff !important;
 32 |     background: #f6b93b;
 33 |     border-color: #f6b93b !important;
 34 |     transition: all 0.4s ease 0s;
 35 |     }
 36 |   </style>
 37 | 
 38 | </head>
 39 | 
 40 | <body>
 41 | 
 42 |   <!-- Show Indian AI Hospital banner-->
 43 |   <div>
 44 |     <img src="static/images/Indian AI Hospital.png" class="w3-border w3-padding" alt="" style="width:100%">
 45 |     Breast Cancer Detection Application Using Machine Learning Model
 46 |   </div>
 47 |  
 48 |  
 49 |  <div class="login">
 50 | 	
 51 |     <!-- Get input for predict the cancer -->
 52 |     <center>
 53 |     <form action="{{ url_for('predict')}}"method="post">
 54 |         <h1>Enter the value of tumor features --->>></h1>
 55 |         
 56 |     	<input type="text" name="mean_radius" placeholder="mean radius" required="required" />
 57 |         <input type="text" name="mean_texture" placeholder="mean texture" required="required" />
 58 | 		<input type="text" name="mean_perimeter" placeholder="mean perimeter" required="required" />
 59 | 		<input type="text" name="mean_area" placeholder="mean area" required="required" />
 60 |         <input type="text" name="mean_smoothness" placeholder="mean smoothness" required="required" />
 61 | 		<input type="text" name="mean_compactness" placeholder="mean compactness" required="required" />
 62 | 		<br>
 63 |     	<input type="text" name="mean_concavity" placeholder="mean concavity" required="required" />
 64 |         <input type="text" name="mean_concave_points" placeholder="mean concave points" required="required" />
 65 | 		<input type="text" name="mean_symmetry" placeholder="mean symmetry" required="required" />
 66 |     	<input type="text" name="mean_fractal_dimension" placeholder="mean fractal dimension" required="required" />
 67 |         <input type="text" name="radius_error" placeholder="radius error" required="required" />
 68 | 		<input type="text" name="texture_error" placeholder="texture error" required="required" />
 69 | 		<br>
 70 |     	<input type="text" name="perimeter_error" placeholder="perimeter error" required="required" />
 71 |         <input type="text" name="area_error" placeholder="area error " required="required" />
 72 | 		<input type="text" name="smoothness_error" placeholder="smoothness error" required="required" />
 73 |     	<input type="text" name="compactness_error" placeholder="compactness error" required="required" />
 74 |         <input type="text" name="concavity_error" placeholder="concavity error" required="required" />
 75 | 		<input type="text" name="concave_points_error" placeholder="concave points error" required="required" />
 76 |     	<br>
 77 |     	<input type="text" name="symmetry_error" placeholder="symmetry error" required="required" />
 78 |         <input type="text" name="fractal_dimension_error" placeholder="fractal dimension error" required="required" />
 79 | 		<input type="text" name="worst_radius" placeholder="worst radius" required="required" />
 80 |     	<input type="text" name="worst_texture" placeholder="worst texture" required="required" />
 81 |         <input type="text" name="worst_perimeter" placeholder="worst perimeter" required="required" />
 82 | 		<input type="text" name="worst_area" placeholder="worst area" required="required" />
 83 | 		<br>
 84 |     	<input type="text" name="worst_smoothness" placeholder="worst smoothness" required="required" />
 85 |         <input type="text" name="worst_compactness" placeholder="worst compactness" required="required" />
 86 | 		<input type="text" name="worst_concavity" placeholder="worst concavity" required="required" />
 87 |     	<input type="text" name="worst_concave_points" placeholder="worst concave points" required="required" />
 88 |         <input type="text" name="worst_symmetry" placeholder="'worst symmetry" required="required" />
 89 | 		<input type="text" name="worst_fractal_dimension" placeholder="worst fractal dimension" required="required" />
 90 |         <br>
 91 |         <br>
 92 |         
 93 |         <!-- Show button -->
 94 |         <div class="button_cont" align="center"><a class="button_css" href="" target="_blank" rel="nofollow noopener">
 95 |             <button type="submit" class="btn btn-primary btn-block btn-large"><strong>Predict Cancer</strong></button></a>
 96 |         </div>
 97 |         
 98 |     </form>
 99 |     </center>
100 |    
101 |    <!-- Show predicted output using ML model --> 
102 |    <div>
103 |        <center>
104 |    <h1>{{ prediction_text }}</h1>
105 |        </center>
106 |    </div>
107 | 
108 |  </div>
109 | 
110 | </body>
111 | </html>
112 | 


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