rafat0421 commited on
Commit
79d29f1
1 Parent(s): 675b342
Files changed (2) hide show
  1. .hw_api_key +1 -0
  2. app.py +47 -0
.hw_api_key ADDED
@@ -0,0 +1 @@
 
 
1
+ q6HWgUYrlRxX1FZR.fFpWHb1SouzKzgVWxgsbcBfDfE0zOyk8r8kOBFchmFI8EaspiT7Le9YnUZHU45Gc
app.py ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+ import numpy as np
3
+ from PIL import Image
4
+ import requests
5
+
6
+ import hopsworks
7
+ import joblib
8
+
9
+ project = hopsworks.login()
10
+ fs = project.get_feature_store()
11
+
12
+
13
+ mr = project.get_model_registry()
14
+ model = mr.get_model("iris_modal", version=1)
15
+ model_dir = model.download()
16
+ model = joblib.load(model_dir + "/iris_model.pkl")
17
+
18
+
19
+ def iris(sepal_length, sepal_width, petal_length, petal_width):
20
+ input_list = []
21
+ input_list.append(sepal_length)
22
+ input_list.append(sepal_width)
23
+ input_list.append(petal_length)
24
+ input_list.append(petal_width)
25
+ # 'res' is a list of predictions returned as the label.
26
+ res = model.predict(np.asarray(input_list).reshape(1, -1))
27
+ # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
28
+ # the first element.
29
+ flower_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + res[0] + ".png"
30
+ img = Image.open(requests.get(flower_url, stream=True).raw)
31
+ return img
32
+
33
+ demo = gr.Interface(
34
+ fn=iris,
35
+ title="Iris Flower Predictive Analytics",
36
+ description="Experiment with sepal/petal lengths/widths to predict which flower it is.",
37
+ allow_flagging="never",
38
+ inputs=[
39
+ gr.inputs.Number(default=1.0, label="sepal length (cm)"),
40
+ gr.inputs.Number(default=1.0, label="sepal width (cm)"),
41
+ gr.inputs.Number(default=1.0, label="petal length (cm)"),
42
+ gr.inputs.Number(default=1.0, label="petal width (cm)"),
43
+ ],
44
+ outputs=gr.Image(type="pil"))
45
+
46
+ demo.launch()
47
+