from time import sleep

import cv2
import numpy as np

from robot import Robot

POWER = 70

TURN_T = 7.9 # 1 degree
DRIVE_T = 22 # 1 centimeter

RIGHT_WHEEL_OFFSET = 4

CLOCKWISE_OFFSET = 0.96

FOCAL_LENGTH = 1691

CAMERA_MATRIX = np.array(
    [[FOCAL_LENGTH,0,512],[0,FOCAL_LENGTH,360],[0,0,1]],
    dtype=np.float32
)
DIST_COEF = np.array([0,0,0,0,0], dtype=np.float32)

def find_aruco(image):
    aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
    aruco_params = cv2.aruco.DetectorParameters_create()
    corners, ids, _ = cv2.aruco.detectMarkers(
        image,
        aruco_dict,
        parameters=aruco_params
    )

    if corners is None:
        return []

    return [(box[0], ids[i][0]) for i, box in enumerate(corners)]

def find_arucos(arlo):
    aruco_dict = {}

    while True:
        arucos = find_aruco(arlo.take_photo())
        if arucos != []:
            print(arucos)
            for aruco, id_ in arucos:
                aruco_dict[id_] = aruco

            if len(aruco_dict) >= 2:
                break
        arlo.go_diff(40, 40, 1, 0)
        sleep(0.3)
        arlo.stop()

    return list(arucos.items())[:2]

def main():
    arlo = Robot()
    arucos = find_arucos(arlo)

    aruco_positions = np.array([cv2.aruco.estimatePoseSingleMarkers(
        np.array([aruco[0]]), 14.5, CAMERA_MATRIX, DIST_COEF
    )[0][0] for aruco in arucos])

    position = [
        np.average(aruco_positions[:,0]),
        np.average(aruco_positions[:,2])
    ]

    angle = np.rad2deg(np.arctan(position[0]/position[1]))
    drive_distance = np.sqrt(position[0]**2 + position[1]**2)
    if angle < 0:
        arlo.go_diff(POWER, POWER, 0, 1)
        sleep((abs(angle) * TURN_T)/1000)
        arlo.stop()
    else:
        arlo.go_diff(POWER, POWER, 1, 0)
        sleep((abs(angle) * TURN_T * CLOCKWISE_OFFSET)/1000)
        arlo.stop()

    arlo.go_diff(POWER, POWER + RIGHT_WHEEL_OFFSET, 1, 1)
    sleep((drive_distance * DRIVE_T)/1000)
    arlo.stop()


if __name__ == "__main__":
    main()