| import pandas as pd |
| import gradio as gr |
| import joblib |
|
|
| pipeline = joblib.load("pipeline.joblib") |
|
|
| def predict( |
| Have_IP, |
| Have_At, |
| URL_Length, |
| URL_Depth, |
| Redirection, |
| https_Domain, |
| TinyURL, |
| Prefix_or_Suffix, |
| DNS_Record, |
| Domain_Age, |
| Domain_End, |
| iFrame, |
| Mouse_Over, |
| Right_Click, |
| Web_Forwards |
| ): |
|
|
| sample = { |
| "Have_IP": Have_IP, |
| "Have_At": Have_At, |
| "URL_Length": URL_Length, |
| "URL_Depth": URL_Depth, |
| "Redirection": Redirection, |
| "https_Domain": https_Domain, |
| "TinyURL": TinyURL, |
| "Prefix/Suffix": Prefix_or_Suffix, |
| "DNS_Record": DNS_Record, |
| "Domain_Age": Domain_Age, |
| "Domain_End": Domain_End, |
| "iFrame": iFrame, |
| "Mouse_Over": Mouse_Over, |
| "Right_Click": Right_Click, |
| "Web_Forwards": Web_Forwards |
| } |
|
|
| sample_df = pd.DataFrame([sample]) |
|
|
| y_pred = pipeline.predict(sample_df) |
| y_pred = int(y_pred[0]) |
|
|
| return y_pred |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("# URL Classification Demo") |
| Have_IP = gr.Checkbox(label="Have_IP") |
| Have_At = gr.Checkbox(label="Have_At") |
| URL_Length = gr.Checkbox(label="URL_Length") |
| URL_Depth = gr.Number(label="URL_Depth", value=0) |
| Redirection = gr.Checkbox(label="Redirection") |
| https_Domain = gr.Checkbox(label="https_Domain") |
| TinyURL = gr.Checkbox(label="TinyURL") |
| Prefix_or_Suffix = gr.Checkbox(label="Prefix/Suffix") |
| DNS_Record = gr.Checkbox(label="DNS_Record") |
| Domain_Age = gr.Checkbox(label="Domain_Age") |
| Domain_End = gr.Checkbox(label="Domain_End") |
| iFrame = gr.Checkbox(label="iFrame") |
| Mouse_Over = gr.Checkbox(label="Mouse_Over") |
| Right_Click = gr.Checkbox(label="Right_Click") |
| Web_Forwards = gr.Checkbox(label="Web_Forwards") |
| |
| output = gr.Label(label="Prediction Output") |
|
|
| inputs = [ |
| Have_IP, Have_At, URL_Length, URL_Depth, Redirection, https_Domain, TinyURL, |
| Prefix_or_Suffix, DNS_Record, Domain_Age, Domain_End, iFrame, |
| Mouse_Over, Right_Click, Web_Forwards |
| ] |
| outputs = output |
|
|
| predict_btn = gr.Button("Predict", variant="primary") |
| predict_btn.click(predict, inputs=inputs, outputs=outputs) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
