SevenhuijsenM commited on
Commit
fc39a90
·
1 Parent(s): a77aa54

Fixed the functions

Browse files
Files changed (1) hide show
  1. app.py +19 -17
app.py CHANGED
@@ -1,6 +1,4 @@
1
  import gradio as gr
2
- from PIL import Image
3
- import requests
4
  import hopsworks
5
  import joblib
6
  import pandas as pd
@@ -32,14 +30,18 @@ def wine(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides
32
  'free_sulfur_dioxide': [free_sulfur_dioxide],
33
  'total_sulfur_dioxide': [total_sulfur_dioxide],
34
  'density': [density],
35
- 'pH': [ph],
36
  'sulphates': [sulphates],
37
  'alcohol': [alcohol],
38
- 'type': [type],
39
  })
40
 
 
 
 
41
  # Predict the wine quality
42
- return model.predict(df)[0]
 
43
 
44
  demo = gr.Interface(
45
  fn=wine,
@@ -47,21 +49,21 @@ demo = gr.Interface(
47
  description="Predict the quality of a wine based on its characteristics",
48
  allow_flagging="never",
49
  inputs=[
50
- gr.inputs.Slider(4, 15, 0.1, label="Fixed Acidity"),
51
- gr.inputs.Slider(0, 2, 0.1, label="Volatile Acidity"),
52
- gr.inputs.Slider(0, 1, 0.1, label="Citric Acid"),
53
- gr.inputs.Slider(0, 20, 0.1, label="Residual Sugar"),
54
- gr.inputs.Slider(0, 1, 0.1, label="Chlorides"),
55
- gr.inputs.Slider(1, 100, 0.1, label="Free Sulfur Dioxide"),
56
- gr.inputs.Slider(6, 300, 0.1, label="Total Sulfur Dioxide"),
57
- gr.inputs.Slider(0, 1, 0.1, label="Density"),
58
- gr.inputs.Slider(2, 5, 0.1, label="pH"),
59
- gr.inputs.Slider(0, 1, 0.1, label="Sulphates"),
60
- gr.inputs.Slider(8, 15, 0.1, label="Alcohol"),
61
  gr.inputs.Radio(["Red", "White"], label="Type"),
62
  ],
63
  outputs=[
64
- gr.outputs.Label(label="Quality"),
65
  ]
66
  )
67
 
 
1
  import gradio as gr
 
 
2
  import hopsworks
3
  import joblib
4
  import pandas as pd
 
30
  'free_sulfur_dioxide': [free_sulfur_dioxide],
31
  'total_sulfur_dioxide': [total_sulfur_dioxide],
32
  'density': [density],
33
+ 'ph': [ph],
34
  'sulphates': [sulphates],
35
  'alcohol': [alcohol],
36
+ 'type': [type]
37
  })
38
 
39
+ # Change the type to integer
40
+ df['type'] = df['type'].map({'Red': 0, 'White': 1})
41
+
42
  # Predict the wine quality
43
+ print(f"Predicting wine quality for: {df.to_dict()}, outcome is: {model.predict(df)[0]}")
44
+ return round(model.predict(df)[0])
45
 
46
  demo = gr.Interface(
47
  fn=wine,
 
49
  description="Predict the quality of a wine based on its characteristics",
50
  allow_flagging="never",
51
  inputs=[
52
+ gr.inputs.Slider(3.8, 15.9, 0.121, label= 'fixed_acidity'),
53
+ gr.inputs.Slider(0.08, 1.58, 0.015, label= 'volatile_acidity'),
54
+ gr.inputs.Slider(0.0, 1.66, 0.017, label= 'citric_acid'),
55
+ gr.inputs.Slider(0.6, 65.8, 0.652, label= 'residual_sugar'),
56
+ gr.inputs.Slider(0.009, 0.611, 0.006, label= 'chlorides'),
57
+ gr.inputs.Slider(1.0, 289.0, 2.88, label= 'free_sulfur_dioxide'),
58
+ gr.inputs.Slider(6.0, 440.0, 4.34, label= 'total_sulfur_dioxide'),
59
+ gr.inputs.Slider(0.98711, 1.03898, 0.001, label= 'density'),
60
+ gr.inputs.Slider(2.72, 4.01, 0.013, label= 'ph'),
61
+ gr.inputs.Slider(0.22, 2.0, 0.018, label= 'sulphates'),
62
+ gr.inputs.Slider(8.0, 14.9, 0.069, label= 'alcohol'),
63
  gr.inputs.Radio(["Red", "White"], label="Type"),
64
  ],
65
  outputs=[
66
+ gr.outputs.Textbox(label="Quality"),
67
  ]
68
  )
69