import pyodbc
#from neuro import Neuro


server = '10.0.0.43'
database = 'mb'
username = 'usrMB'
password = 'asdqaz'


class Processing(object):
    def __init__(self, image_path, save_path, sqr_percent):
        self.save_path = save_path
        self.image_path = image_path
        self.sqr_percent = sqr_percent

        self.conn = pyodbc.connect('DRIVER={ODBC Driver 13 for SQL Server};SERVER='+server+';DATABASE='+database+';UID='+username+';PWD='+ password)

        self.cam_zone_command = "SELECT id_cam, id_type_zone, sensitivity, x1, y1 ,x2, y2, x3, y3, x4, y4 " \
                           "FROM CamZones WHERE id_cam = '%s' AND (" \
                           "SELECT id_type_processing FROM TypesProcessingZone WHERE id_type_zone = '%s') = 1;"

        self.sql_command = 'SELECT id, id_video, shopNo, date_add, id_cam, id_type_processing, data_processing, alarm ' \
                      'FROM TasksForAnalisis WHERE id_type_processing = 1'

        self.update_task_alarm = "UPDATE TasksForAnalisis SET alarm = %s WHERE id = '%s'"

        self.times_for_video = "SELECT link_download FROM times_for_video WHERE id = '%s'"

    def close_connection(self):
        self.conn.close()


    def get_db_version(self):
        cursor = self.conn.cursor()
        cursor.execute("SELECT @@version;")
        row = cursor.fetchone()
        while row:
            print(row)
            break

    def process(self):
        self.neuro_network = Neuro()

        cursor = self.conn.cursor()
        cursor.execute(self.sql_command)
        results = cursor.fetchall()
        for result in results:
            print("MAIN:", result)
            cursor.execute(self.times_for_video % result[1])
            link_for_download = cursor.fetchone()[0]
            print('Link for download', link_for_download)
            #Frame.download_image(link_for_download, self.image_path)

            interest_zones = []
            yolo_thresh = 0.13

            cursor.execute(self.cam_zone_command % (result[1], result[5]))
            for row in cursor.fetchall():
                print('SUBQUERY:', row)

                interest_zones.append(row[3])
                interest_zones.append(row[4])
                interest_zones.append(row[5])
                interest_zones.append(row[6])

                interest_zones.append(row[7])
                interest_zones.append(row[8])
                interest_zones.append(row[9])
                interest_zones.append(row[10])

                yolo_thresh = float(row[2])
            #images = Frame.image_treatment(self.image_path, self.save_path, interest_zones, yolo_thresh,
                              #             self.sqr_percent)
            #if neuro_network.predict_images_with_alarm(images):
             #   cursor.execute(self.update_task_alarm % ('TRUE', result[0]))


if __name__ == '__main__':
    p = Processing('.', '.', '.')
    p.get_db_version()