├── .gitattributes
├── LICENSE
├── Procfile
├── README.md
├── app.py
├── basics.py
├── iri.pkl
├── iris.data
├── iris.py
├── requirements.txt
├── static
    ├── flower1.jpg
    ├── setosa.jpg
    └── verci.jpg
└── templates
    ├── after.html
    └── home.html


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


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/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2020 Pawandeep-prog
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/Procfile:
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1 | web: gunicorn app:app
2 | 


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/README.md:
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1 | # deploy-ml-model-flask
2 |  deploy your ml model using flask
3 | 


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/app.py:
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 1 | from flask import Flask, render_template, request
 2 | import pickle
 3 | import numpy as np
 4 | 
 5 | model = pickle.load(open('iri.pkl', 'rb'))
 6 | 
 7 | app = Flask(__name__)
 8 | 
 9 | 
10 | 
11 | @app.route('/')
12 | def man():
13 |     return render_template('home.html')
14 | 
15 | 
16 | @app.route('/predict', methods=['POST'])
17 | def home():
18 |     data1 = request.form['a']
19 |     data2 = request.form['b']
20 |     data3 = request.form['c']
21 |     data4 = request.form['d']
22 |     arr = np.array([[data1, data2, data3, data4]])
23 |     pred = model.predict(arr)
24 |     return render_template('after.html', data=pred)
25 | 
26 | 
27 | if __name__ == "__main__":
28 |     app.run(debug=True)
29 | 
30 | 
31 | 
32 | 
33 | 
34 | 
35 | 
36 | 
37 | 
38 | 
39 | 
40 | 
41 | 
42 | 
43 | 
44 | 


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/basics.py:
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 1 | from flask import Flask, render_template
 2 | 
 3 | app = Flask(__name__)
 4 | 
 5 | 
 6 | @app.route('/home')
 7 | def home():
 8 |     return render_template('home.html')
 9 | 
10 | if __name__ == "__main__":
11 |     app.run(debug=True)
12 | 
13 | 
14 | 


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/iri.pkl:
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https://raw.githubusercontent.com/Pawandeep-prog/deploy-ml-model-flask/4b419c9a834384ff8716c09ba810e5723b4858ce/iri.pkl


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/iris.data:
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  1 | 5.1,3.5,1.4,0.2,Iris-setosa
  2 | 4.9,3.0,1.4,0.2,Iris-setosa
  3 | 4.7,3.2,1.3,0.2,Iris-setosa
  4 | 4.6,3.1,1.5,0.2,Iris-setosa
  5 | 5.0,3.6,1.4,0.2,Iris-setosa
  6 | 5.4,3.9,1.7,0.4,Iris-setosa
  7 | 4.6,3.4,1.4,0.3,Iris-setosa
  8 | 5.0,3.4,1.5,0.2,Iris-setosa
  9 | 4.4,2.9,1.4,0.2,Iris-setosa
 10 | 4.9,3.1,1.5,0.1,Iris-setosa
 11 | 5.4,3.7,1.5,0.2,Iris-setosa
 12 | 4.8,3.4,1.6,0.2,Iris-setosa
 13 | 4.8,3.0,1.4,0.1,Iris-setosa
 14 | 4.3,3.0,1.1,0.1,Iris-setosa
 15 | 5.8,4.0,1.2,0.2,Iris-setosa
 16 | 5.7,4.4,1.5,0.4,Iris-setosa
 17 | 5.4,3.9,1.3,0.4,Iris-setosa
 18 | 5.1,3.5,1.4,0.3,Iris-setosa
 19 | 5.7,3.8,1.7,0.3,Iris-setosa
 20 | 5.1,3.8,1.5,0.3,Iris-setosa
 21 | 5.4,3.4,1.7,0.2,Iris-setosa
 22 | 5.1,3.7,1.5,0.4,Iris-setosa
 23 | 4.6,3.6,1.0,0.2,Iris-setosa
 24 | 5.1,3.3,1.7,0.5,Iris-setosa
 25 | 4.8,3.4,1.9,0.2,Iris-setosa
 26 | 5.0,3.0,1.6,0.2,Iris-setosa
 27 | 5.0,3.4,1.6,0.4,Iris-setosa
 28 | 5.2,3.5,1.5,0.2,Iris-setosa
 29 | 5.2,3.4,1.4,0.2,Iris-setosa
 30 | 4.7,3.2,1.6,0.2,Iris-setosa
 31 | 4.8,3.1,1.6,0.2,Iris-setosa
 32 | 5.4,3.4,1.5,0.4,Iris-setosa
 33 | 5.2,4.1,1.5,0.1,Iris-setosa
 34 | 5.5,4.2,1.4,0.2,Iris-setosa
 35 | 4.9,3.1,1.5,0.1,Iris-setosa
 36 | 5.0,3.2,1.2,0.2,Iris-setosa
 37 | 5.5,3.5,1.3,0.2,Iris-setosa
 38 | 4.9,3.1,1.5,0.1,Iris-setosa
 39 | 4.4,3.0,1.3,0.2,Iris-setosa
 40 | 5.1,3.4,1.5,0.2,Iris-setosa
 41 | 5.0,3.5,1.3,0.3,Iris-setosa
 42 | 4.5,2.3,1.3,0.3,Iris-setosa
 43 | 4.4,3.2,1.3,0.2,Iris-setosa
 44 | 5.0,3.5,1.6,0.6,Iris-setosa
 45 | 5.1,3.8,1.9,0.4,Iris-setosa
 46 | 4.8,3.0,1.4,0.3,Iris-setosa
 47 | 5.1,3.8,1.6,0.2,Iris-setosa
 48 | 4.6,3.2,1.4,0.2,Iris-setosa
 49 | 5.3,3.7,1.5,0.2,Iris-setosa
 50 | 5.0,3.3,1.4,0.2,Iris-setosa
 51 | 7.0,3.2,4.7,1.4,Iris-versicolor
 52 | 6.4,3.2,4.5,1.5,Iris-versicolor
 53 | 6.9,3.1,4.9,1.5,Iris-versicolor
 54 | 5.5,2.3,4.0,1.3,Iris-versicolor
 55 | 6.5,2.8,4.6,1.5,Iris-versicolor
 56 | 5.7,2.8,4.5,1.3,Iris-versicolor
 57 | 6.3,3.3,4.7,1.6,Iris-versicolor
 58 | 4.9,2.4,3.3,1.0,Iris-versicolor
 59 | 6.6,2.9,4.6,1.3,Iris-versicolor
 60 | 5.2,2.7,3.9,1.4,Iris-versicolor
 61 | 5.0,2.0,3.5,1.0,Iris-versicolor
 62 | 5.9,3.0,4.2,1.5,Iris-versicolor
 63 | 6.0,2.2,4.0,1.0,Iris-versicolor
 64 | 6.1,2.9,4.7,1.4,Iris-versicolor
 65 | 5.6,2.9,3.6,1.3,Iris-versicolor
 66 | 6.7,3.1,4.4,1.4,Iris-versicolor
 67 | 5.6,3.0,4.5,1.5,Iris-versicolor
 68 | 5.8,2.7,4.1,1.0,Iris-versicolor
 69 | 6.2,2.2,4.5,1.5,Iris-versicolor
 70 | 5.6,2.5,3.9,1.1,Iris-versicolor
 71 | 5.9,3.2,4.8,1.8,Iris-versicolor
 72 | 6.1,2.8,4.0,1.3,Iris-versicolor
 73 | 6.3,2.5,4.9,1.5,Iris-versicolor
 74 | 6.1,2.8,4.7,1.2,Iris-versicolor
 75 | 6.4,2.9,4.3,1.3,Iris-versicolor
 76 | 6.6,3.0,4.4,1.4,Iris-versicolor
 77 | 6.8,2.8,4.8,1.4,Iris-versicolor
 78 | 6.7,3.0,5.0,1.7,Iris-versicolor
 79 | 6.0,2.9,4.5,1.5,Iris-versicolor
 80 | 5.7,2.6,3.5,1.0,Iris-versicolor
 81 | 5.5,2.4,3.8,1.1,Iris-versicolor
 82 | 5.5,2.4,3.7,1.0,Iris-versicolor
 83 | 5.8,2.7,3.9,1.2,Iris-versicolor
 84 | 6.0,2.7,5.1,1.6,Iris-versicolor
 85 | 5.4,3.0,4.5,1.5,Iris-versicolor
 86 | 6.0,3.4,4.5,1.6,Iris-versicolor
 87 | 6.7,3.1,4.7,1.5,Iris-versicolor
 88 | 6.3,2.3,4.4,1.3,Iris-versicolor
 89 | 5.6,3.0,4.1,1.3,Iris-versicolor
 90 | 5.5,2.5,4.0,1.3,Iris-versicolor
 91 | 5.5,2.6,4.4,1.2,Iris-versicolor
 92 | 6.1,3.0,4.6,1.4,Iris-versicolor
 93 | 5.8,2.6,4.0,1.2,Iris-versicolor
 94 | 5.0,2.3,3.3,1.0,Iris-versicolor
 95 | 5.6,2.7,4.2,1.3,Iris-versicolor
 96 | 5.7,3.0,4.2,1.2,Iris-versicolor
 97 | 5.7,2.9,4.2,1.3,Iris-versicolor
 98 | 6.2,2.9,4.3,1.3,Iris-versicolor
 99 | 5.1,2.5,3.0,1.1,Iris-versicolor
100 | 5.7,2.8,4.1,1.3,Iris-versicolor
101 | 6.3,3.3,6.0,2.5,Iris-virginica
102 | 5.8,2.7,5.1,1.9,Iris-virginica
103 | 7.1,3.0,5.9,2.1,Iris-virginica
104 | 6.3,2.9,5.6,1.8,Iris-virginica
105 | 6.5,3.0,5.8,2.2,Iris-virginica
106 | 7.6,3.0,6.6,2.1,Iris-virginica
107 | 4.9,2.5,4.5,1.7,Iris-virginica
108 | 7.3,2.9,6.3,1.8,Iris-virginica
109 | 6.7,2.5,5.8,1.8,Iris-virginica
110 | 7.2,3.6,6.1,2.5,Iris-virginica
111 | 6.5,3.2,5.1,2.0,Iris-virginica
112 | 6.4,2.7,5.3,1.9,Iris-virginica
113 | 6.8,3.0,5.5,2.1,Iris-virginica
114 | 5.7,2.5,5.0,2.0,Iris-virginica
115 | 5.8,2.8,5.1,2.4,Iris-virginica
116 | 6.4,3.2,5.3,2.3,Iris-virginica
117 | 6.5,3.0,5.5,1.8,Iris-virginica
118 | 7.7,3.8,6.7,2.2,Iris-virginica
119 | 7.7,2.6,6.9,2.3,Iris-virginica
120 | 6.0,2.2,5.0,1.5,Iris-virginica
121 | 6.9,3.2,5.7,2.3,Iris-virginica
122 | 5.6,2.8,4.9,2.0,Iris-virginica
123 | 7.7,2.8,6.7,2.0,Iris-virginica
124 | 6.3,2.7,4.9,1.8,Iris-virginica
125 | 6.7,3.3,5.7,2.1,Iris-virginica
126 | 7.2,3.2,6.0,1.8,Iris-virginica
127 | 6.2,2.8,4.8,1.8,Iris-virginica
128 | 6.1,3.0,4.9,1.8,Iris-virginica
129 | 6.4,2.8,5.6,2.1,Iris-virginica
130 | 7.2,3.0,5.8,1.6,Iris-virginica
131 | 7.4,2.8,6.1,1.9,Iris-virginica
132 | 7.9,3.8,6.4,2.0,Iris-virginica
133 | 6.4,2.8,5.6,2.2,Iris-virginica
134 | 6.3,2.8,5.1,1.5,Iris-virginica
135 | 6.1,2.6,5.6,1.4,Iris-virginica
136 | 7.7,3.0,6.1,2.3,Iris-virginica
137 | 6.3,3.4,5.6,2.4,Iris-virginica
138 | 6.4,3.1,5.5,1.8,Iris-virginica
139 | 6.0,3.0,4.8,1.8,Iris-virginica
140 | 6.9,3.1,5.4,2.1,Iris-virginica
141 | 6.7,3.1,5.6,2.4,Iris-virginica
142 | 6.9,3.1,5.1,2.3,Iris-virginica
143 | 5.8,2.7,5.1,1.9,Iris-virginica
144 | 6.8,3.2,5.9,2.3,Iris-virginica
145 | 6.7,3.3,5.7,2.5,Iris-virginica
146 | 6.7,3.0,5.2,2.3,Iris-virginica
147 | 6.3,2.5,5.0,1.9,Iris-virginica
148 | 6.5,3.0,5.2,2.0,Iris-virginica
149 | 6.2,3.4,5.4,2.3,Iris-virginica
150 | 5.9,3.0,5.1,1.8,Iris-virginica
151 | 
152 | 


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/iris.py:
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 1 | import pandas as pd
 2 | import numpy as np
 3 | import pickle
 4 | 
 5 | df = pd.read_csv('iris.data')
 6 | 
 7 | X = np.array(df.iloc[:, 0:4])
 8 | y = np.array(df.iloc[:, 4:])
 9 | 
10 | from sklearn.preprocessing import LabelEncoder
11 | le = LabelEncoder()
12 | y = le.fit_transform(y.reshape(-1))
13 | 
14 | from sklearn.model_selection import train_test_split
15 | X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
16 | 
17 | from sklearn.svm import SVC
18 | sv = SVC(kernel='linear').fit(X_train,y_train)
19 | 
20 | 
21 | pickle.dump(sv, open('iri.pkl', 'wb'))
22 | 


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/requirements.txt:
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1 | pandas==1.0.3
2 | Flask==1.1.1
3 | numpy==1.18.1
4 | scikit_learn==0.22.1
5 | gunicorn==20.0.4
6 | 
7 | 
8 | 


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/static/flower1.jpg:
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https://raw.githubusercontent.com/Pawandeep-prog/deploy-ml-model-flask/4b419c9a834384ff8716c09ba810e5723b4858ce/static/flower1.jpg


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/static/setosa.jpg:
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https://raw.githubusercontent.com/Pawandeep-prog/deploy-ml-model-flask/4b419c9a834384ff8716c09ba810e5723b4858ce/static/setosa.jpg


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/static/verci.jpg:
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https://raw.githubusercontent.com/Pawandeep-prog/deploy-ml-model-flask/4b419c9a834384ff8716c09ba810e5723b4858ce/static/verci.jpg


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/templates/after.html:
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 1 | <html>
 2 | 
 3 | <body bgcolor=#a3cfb4>
 4 | 
 5 |     <center>
 6 | 
 7 |         <h1>  PREDICTION :  </h1>
 8 |     
 9 |     {%if data == 0%}
10 |     <h1>Iris-setosa</h1>  
11 |     <img src='static\setosa.jpg'>  
12 | 
13 |     {%else%}
14 |     <h1>Iris-versicolor</h1>
15 |     <img src='static\verci.jpg'>
16 |     
17 |     {%endif%}
18 | 
19 |         <br><br>
20 |     <a href='/'>go back to home page</a>
21 | 
22 |     </center>
23 | 
24 | </body>
25 | 
26 | </html>
27 | 
28 | 
29 | 
30 | 
31 | 
32 | 
33 | 


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/templates/home.html:
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 1 | <html>
 2 |     <body bgcolor=#d4a3ae>
 3 | 
 4 |         <center>
 5 | 
 6 |         <h1> IRIS FLOWER DETECTION </h1><br>
 7 |         
 8 |         <form method="POST", action="{{url_for('home')}}">
 9 |            <b> First value :  <input type="text", name='a', placeholder="enter 1"> <br><br>
10 |             Second value :  <input type="text", name='b', placeholder="enter 2"> <br><br>
11 |             Third value :  <input type="text", name='c', placeholder="enter 3"> <br><br>
12 |             Fourth value : <input type="text", name='d', placeholder="enter 4"> <br><br><br></b>
13 |             <input type="submit" , value='predict!' >
14 |         </form>
15 | 
16 |         <img src='static\flower1.jpg' alt="flower">
17 |         
18 |     </center>
19 | 
20 |     </body>
21 | </html>
22 | 


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