current_time = datetime.strptime(current_time, '%H:%M:%S').time() ### Cropping image to have just the radar image img = original.crop((120, 120, 600, 600)) logger.info('image cropped') ### Removing unnecessary colors img = processor.remove_colors(img) logger.info('color removed') ### Getting Color Coding in Dataframe clouds = processor.cloudcolor(img) logger.info('cloud color coding done') ### Getting location for each pixel clouds = processor.pixelcoding(clouds, img) logger.info('pixel coding done') ### Mapping Rainfall Intensity of each pixel rain = processor.rainfallcoding(clouds) logger.info('rainfall intensity done') ### Getting cloud information cloud_group = processor.group_clouds(clouds) logger.info('clouds formed') ### Getting the centre of the rain centre = processor.get_centre(cloud_group) logger.info('got weighted mean') df = pd.DataFrame(columns=['datetime', 'cloud_mean'])
img = processor.remove_colors(img) logger.info('color removed') ### Replacing red with green to have a single color img = processor.replace_colors(img) logger.info('color replaced') ### Making List of rain forecasting pixels rain = processor.rainbar(img) logger.info('rain bars ready') ### Checking if rain forecasted if rain: logger.info('There is some rain!') ### Getting location for each pixel rain = processor.pixelcoding(rain, img) logger.info('Pixel coding done') ### Gettiung forecast barish = processor.get_forecast(rain, img, dates) logger.info('Getting forecast') else: barish = processor.no_rain(img, dates) logger.info('No rain and df ready') barish['created_at'] = datetime.now() barish['forecast'] = barish['forecast'].apply(lambda x: int(1) if x > 0 else int(0)) logger.info('DF ready to go') # processor.store_forecast(barish) conn = pymysql.connect("139.59.42.147", "dummy", "dummy123", "energy_consumption")