| import gradio as gr |
| import tensorflow as tf |
| import numpy as np |
| import pandas as pd |
|
|
| model_path = "kia_apartment_keras_model.keras" |
| model = tf.keras.models.load_model(model_path) |
|
|
| df_bfs_data = pd.read_csv('bfs_municipality_and_tax_data.csv', sep=',', encoding='utf-8') |
| df_bfs_data['tax_income'] = df_bfs_data['tax_income'].str.replace("'", "").astype(float) |
|
|
| locations = { |
| "Zürich": 261, |
| "Kloten": 62, |
| "Uster": 198, |
| "Illnau-Effretikon": 296, |
| "Feuerthalen": 27, |
| "Pfäffikon": 177, |
| "Ottenbach": 11, |
| "Dübendorf": 191, |
| "Richterswil": 138, |
| "Maur": 195, |
| "Embrach": 56, |
| "Bülach": 53, |
| "Winterthur": 230, |
| "Oetwil am See": 157, |
| "Russikon": 178, |
| "Obfelden": 10, |
| "Wald (ZH)": 120, |
| "Niederweningen": 91, |
| "Dällikon": 84, |
| "Buchs (ZH)": 83, |
| "Rüti (ZH)": 118, |
| "Hittnau": 173, |
| "Bassersdorf": 52, |
| "Glattfelden": 58, |
| "Opfikon": 66, |
| "Hinwil": 117, |
| "Regensberg": 95, |
| "Langnau am Albis": 136, |
| "Dietikon": 243, |
| "Erlenbach (ZH)": 151, |
| "Kappel am Albis": 6, |
| "Stäfa": 158, |
| "Zell (ZH)": 231, |
| "Turbenthal": 228, |
| "Oberglatt": 92, |
| "Winkel": 72, |
| "Volketswil": 199, |
| "Kilchberg (ZH)": 135, |
| "Wetzikon (ZH)": 121, |
| "Zumikon": 160, |
| "Weisslingen": 180, |
| "Elsau": 219, |
| "Hettlingen": 221, |
| "Rüschlikon": 139, |
| "Stallikon": 13, |
| "Dielsdorf": 86, |
| "Wallisellen": 69, |
| "Dietlikon": 54, |
| "Meilen": 156, |
| "Wangen-Brüttisellen": 200, |
| "Flaach": 28, |
| "Regensdorf": 96, |
| "Niederhasli": 90, |
| "Bauma": 297, |
| "Aesch (ZH)": 241, |
| "Schlieren": 247, |
| "Dürnten": 113, |
| "Unterengstringen": 249, |
| "Gossau (ZH)": 115, |
| "Oberengstringen": 245, |
| "Schleinikon": 98, |
| "Aeugst am Albis": 1, |
| "Rheinau": 38, |
| "Höri": 60, |
| "Rickenbach (ZH)": 225, |
| "Rafz": 67, |
| "Adliswil": 131, |
| "Zollikon": 161, |
| "Urdorf": 250, |
| "Hombrechtikon": 153, |
| "Birmensdorf (ZH)": 242, |
| "Fehraltorf": 172, |
| "Weiach": 102, |
| "Männedorf": 155, |
| "Küsnacht (ZH)": 154, |
| "Hausen am Albis": 4, |
| "Hochfelden": 59, |
| "Fällanden": 193, |
| "Greifensee": 194, |
| "Mönchaltorf": 196, |
| "Dägerlen": 214, |
| "Thalheim an der Thur": 39, |
| "Uetikon am See": 159, |
| "Seuzach": 227, |
| "Uitikon": 248, |
| "Affoltern am Albis": 2, |
| "Geroldswil": 244, |
| "Niederglatt": 89, |
| "Thalwil": 141, |
| "Rorbas": 68, |
| "Pfungen": 224, |
| "Weiningen (ZH)": 251, |
| "Bubikon": 112, |
| "Neftenbach": 223, |
| "Mettmenstetten": 9, |
| "Otelfingen": 94, |
| "Flurlingen": 29, |
| "Stadel": 100, |
| "Grüningen": 116, |
| "Henggart": 31, |
| "Dachsen": 25, |
| "Bonstetten": 3, |
| "Bachenbülach": 51, |
| "Horgen": 295 |
| } |
|
|
| |
| def predict_apartment(rooms, area, town): |
| bfs_number = locations[town] |
| df = df_bfs_data[df_bfs_data['bfs_number']==bfs_number] |
| |
| if len(df) != 1: |
| return -1 |
| |
| input = np.array([rooms, area, df['pop'].iloc[0], df['pop_dens'].iloc[0], df['frg_pct'].iloc[0], df['emp'].iloc[0], df['tax_income'].iloc[0]]) |
| input = input.reshape(1, 7) |
| prediction = model.predict(input) |
| return np.round(prediction[0][0], 0) |
|
|
| |
| iface = gr.Interface( |
| fn=predict_apartment, |
| inputs=["number", "number", gr.Dropdown(choices=locations.keys(), label="Town", type="value")], |
| outputs=gr.Number() |
| ) |
|
|
| iface.launch() |
