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")
