Upload application files

app.py

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+import gradio as gr
+import numpy as np
+import joblib
+
+def predict(region1, region2, region3, region4, region5, region6):
+    model = joblib.load('./localoutlierfactor.joblib')
+    print(np.array([[region1, region2, region3, region4, region5, region6]]))
+    ypredict = model.predict(np.array([[region1, region2, region3, region4, region5, region6]]))
+    return "Abnormal traffic" if ypredict == -1 else "Normal traffic"
+
+app = gr.Interface(
+    title='Traffic Anomaly Detection',
+    fn = predict, # the function that we create to 
+    inputs=[gr.Slider(0,800),gr.Slider(0,800),gr.Slider(0,800),
+            gr.Slider(0,800),gr.Slider(0,800),gr.Slider(0,800)], # represent each region inputs
+    outputs='text'
+)
+
+# Launch the app
+app.launch()

localoutlierfactor.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2b2ca0c9629841fbfa394de9e4909c1ba9f68e9c7cf0f5b07ebd24f17abc0688
+size 63329

requirements.txt

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+scikit-learn== 1.2.2