Hugging Face's logo

Spaces:
asadwaris
/
breast-cancer-detection
Sleeping

App Files Community
asadwaris commited on
Commit
fa54835
•
1 Parent(s): c8d3f2c

Upload 8 files

Browse files
Files changed (8) hide show
  1. CNAME +1 -0
  2. Procfile +1 -0
  3. app.py +40 -0
  4. model.pkl +3 -0
  5. requirements.txt +9 -0
  6. static/images/img.jpeg +0 -0
  7. svc_classifier.pickle +3 -0
  8. templates/index.html +105 -0
CNAME ADDED
@@ -0,0 +1 @@
 
 
1
+ asad-999.com
Procfile ADDED
@@ -0,0 +1 @@
 
 
1
+ web: gunicorn app:app
app.py ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import numpy as np
2
+ import pandas as pd
3
+ from flask import Flask, request, render_template
4
+ import pickle
5
+
6
+ app = Flask(__name__)
7
+ model = pickle.load(open('svc_classifier.pickle', 'rb'))
8
+
9
+ @app.route('/')
10
+ def home():
11
+ return render_template('index.html')
12
+
13
+ @app.route('/predict',methods=['POST'])
14
+ def predict():
15
+ input_features = [float(x) for x in request.form.values()]
16
+ features_value = [np.array(input_features)]
17
+
18
+ features_name = ['mean radius', 'mean texture', 'mean perimeter', 'mean area',
19
+ 'mean smoothness', 'mean compactness', 'mean concavity',
20
+ 'mean concave points', 'mean symmetry', 'mean fractal dimension',
21
+ 'radius error', 'texture error', 'perimeter error', 'area error',
22
+ 'smoothness error', 'compactness error', 'concavity error',
23
+ 'concave points error', 'symmetry error', 'fractal dimension error',
24
+ 'worst radius', 'worst texture', 'worst perimeter', 'worst area',
25
+ 'worst smoothness', 'worst compactness', 'worst concavity',
26
+ 'worst concave points', 'worst symmetry', 'worst fractal dimension']
27
+
28
+ df = pd.DataFrame(features_value, columns=features_name)
29
+ output = model.predict(df)
30
+
31
+ if output == 0:
32
+ res_val = "** breast cancer **"
33
+ else:
34
+ res_val = "no breast cancer"
35
+
36
+
37
+ return render_template('index.html', prediction_text='Patient has {}'.format(res_val))
38
+
39
+ if __name__ == "__main__":
40
+ app.run()
model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:eef4ae4799bff48855bd1d73051e3f41acdd3c76ad830f10798ea33ae180ef12
3
+ size 64035
requirements.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ Flask>=2.0.2
2
+ numpy>=1.21.2
3
+ pandas>=1.3.3
4
+ scikit-learn>=0.24.2
5
+ gunicorn
6
+ itsdangerous
7
+ Jinja2
8
+ MarkupSafe
9
+ Werkzeug
static/images/img.jpeg ADDED
svc_classifier.pickle ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b0bbd5fa668224b007085d458c09867b0a258e24577b14cfc9782329999db061
3
+ size 33622
templates/index.html ADDED
@@ -0,0 +1,105 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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/img.jpeg');
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
+
43
+ <div class="login">
44
+
45
+ <!-- Get input for predict the cancer -->
46
+ <center>
47
+ <form action="{{ url_for('predict')}}"method="post">
48
+ <h1>Enter the value of tumor features >>></h1>
49
+
50
+ <input type="text" name="mean_radius" placeholder="mean radius" required="required" />
51
+ <input type="text" name="mean_texture" placeholder="mean texture" required="required" />
52
+ <input type="text" name="mean_perimeter" placeholder="mean perimeter" required="required" />
53
+ <input type="text" name="mean_area" placeholder="mean area" required="required" />
54
+ <input type="text" name="mean_smoothness" placeholder="mean smoothness" required="required" />
55
+ <input type="text" name="mean_compactness" placeholder="mean compactness" required="required" />
56
+ <br>
57
+ <input type="text" name="mean_concavity" placeholder="mean concavity" required="required" />
58
+ <input type="text" name="mean_concave_points" placeholder="mean concave points" required="required" />
59
+ <input type="text" name="mean_symmetry" placeholder="mean symmetry" required="required" />
60
+ <input type="text" name="mean_fractal_dimension" placeholder="mean fractal dimension" required="required" />
61
+ <input type="text" name="radius_error" placeholder="radius error" required="required" />
62
+ <input type="text" name="texture_error" placeholder="texture error" required="required" />
63
+ <br>
64
+ <input type="text" name="perimeter_error" placeholder="perimeter error" required="required" />
65
+ <input type="text" name="area_error" placeholder="area error " required="required" />
66
+ <input type="text" name="smoothness_error" placeholder="smoothness error" required="required" />
67
+ <input type="text" name="compactness_error" placeholder="compactness error" required="required" />
68
+ <input type="text" name="concavity_error" placeholder="concavity error" required="required" />
69
+ <input type="text" name="concave_points_error" placeholder="concave points error" required="required" />
70
+ <br>
71
+ <input type="text" name="symmetry_error" placeholder="symmetry error" required="required" />
72
+ <input type="text" name="fractal_dimension_error" placeholder="fractal dimension error" required="required" />
73
+ <input type="text" name="worst_radius" placeholder="worst radius" required="required" />
74
+ <input type="text" name="worst_texture" placeholder="worst texture" required="required" />
75
+ <input type="text" name="worst_perimeter" placeholder="worst perimeter" required="required" />
76
+ <input type="text" name="worst_area" placeholder="worst area" required="required" />
77
+ <br>
78
+ <input type="text" name="worst_smoothness" placeholder="worst smoothness" required="required" />
79
+ <input type="text" name="worst_compactness" placeholder="worst compactness" required="required" />
80
+ <input type="text" name="worst_concavity" placeholder="worst concavity" required="required" />
81
+ <input type="text" name="worst_concave_points" placeholder="worst concave points" required="required" />
82
+ <input type="text" name="worst_symmetry" placeholder="'worst symmetry" required="required" />
83
+ <input type="text" name="worst_fractal_dimension" placeholder="worst fractal dimension" required="required" />
84
+ <br>
85
+ <br>
86
+
87
+ <!-- Show button -->
88
+ <div class="button_cont" align="center"><a class="button_css" href="http://bit.ly/breast-cancer-ml-project" target="_blank" rel="nofollow noopener">
89
+ <button type="submit" class="btn btn-primary btn-block btn-large"><strong>Predict Cancer</strong></button></a>
90
+ </div>
91
+
92
+ </form>
93
+ </center>
94
+
95
+ <!-- Show predicted output using ML model -->
96
+ <div>
97
+ <center>
98
+ <h1>{{ prediction_text }}</h1>
99
+ </center>
100
+ </div>
101
+
102
+ </div>
103
+
104
+ </body>
105
+ </html>