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| import streamlit as st | |
| import hopsworks | |
| import joblib | |
| import pandas as pd | |
| import numpy as np | |
| import folium | |
| from streamlit_folium import st_folium, folium_static | |
| import json | |
| import time | |
| from datetime import timedelta, datetime | |
| from branca.element import Figure | |
| import gradio as gr | |
| from functions import decode_features, get_model, get_weather_df, get_weather_data | |
| project = hopsworks.login() | |
| fs = project.get_feature_store() | |
| feature_view = fs.get_feature_view( | |
| name = 'oslo_air_quality_fv', | |
| version = 1 | |
| ) | |
| model = get_model(project=project, | |
| model_name="air_quality_model", | |
| evaluation_metric="f1_score", | |
| sort_metrics_by="max", | |
| version_name=3) | |
| def pred(name): | |
| str1 = " " | |
| for i in range(8): | |
| target_date = datetime.today() + timedelta(days=i) | |
| target_date = target_date.strftime('%Y-%m-%d') | |
| data_weather = [get_weather_data('oslo',target_date)] | |
| df_weather = get_weather_df(data_weather) | |
| df_weather['conditions'] = df_weather['conditions'].replace(['Rain','Clear','Snow','Partially cloudy','Overcast','Snow, Partially cloudy', | |
| 'Rain, Partially cloudy','Rain, Overcast','Snow, Overcast', | |
| 'Snow, Freezing Drizzle/Freezing Rain, Overcast','Snow, Rain', | |
| 'Snow, Rain, Freezing Drizzle/Freezing Rain, Ice, Overcast', | |
| 'Snow, Rain, Freezing Drizzle/Freezing Rain, Overcast','Snow, Rain, Ice, Overcast', | |
| 'Snow, Rain, Overcast','Snow, Rain, Partially cloudy'],[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]) | |
| df_weather = df_weather.drop(columns=["date"]).fillna(0) | |
| df_weather["aqi"] = 0 | |
| preds = model.predict(df_weather) | |
| print(preds) | |
| if(i!=0): | |
| str1 += target_date + " predicted aqi:" + str(int(preds))+"\n" | |
| return str1 | |
| # next_day_date = datetime.today() + timedelta(days=i) | |
| # next_day = next_day_date.strftime ('%d/%m/%Y') | |
| demo = gr.Interface(fn=pred,title="Predict AQI of Oslo" ,inputs="text", outputs="text") | |
| if __name__ == "__main__": | |
| demo.launch() |