from copy import deepcopy, copy

import numpy as np

from DeviceDefine.consensus import UNKNOWN
from MCamera.mn_algorithm import MoveNetAlgorithmPlugin
from MCamera.mp_algorithm import MediapipeAlgorithmPlugin
from MCamera.mp_camera import Camera
from PureBackend.base_driver import MODEL_MEDIAPIPE, MODEL_MOVE_NET
from PureBackend.exam_driver import ExamDriver


def base_detect_image(camera: Camera, model):
    if model == MODEL_MEDIAPIPE:
        _map = MediapipeAlgorithmPlugin()
        _img = deepcopy(camera.get_frame())
        img = _map.find_pose_with_drawing(_img, True)
    elif model == MODEL_MOVE_NET:
        _map = MoveNetAlgorithmPlugin()
        _img = deepcopy(camera.get_frame())
        img = _map.find_pose_with_drawing(_img, True)
    return img


class CameraBackend(ExamDriver):

    def __init__(self, master_mode=True, positioning=True, camera=True, model=MODEL_MEDIAPIPE, speaker=True,
                 multi_positioning_mode=True, device_type=UNKNOWN, pure_mode=False):
        super().__init__(master_mode, positioning, camera, model, speaker, multi_positioning_mode, device_type, pure_mode)
        self.model = model

    def get_exercise_video(self):
        if self.project is None:
            video_response = base_detect_image(self.camera, model=self.model)
        elif self.project and not self.project.is_start:
            video_response = self.project.pure_video_gen()
        else:
            video_response = self.project.pure_streaming_gen()
        if video_response is None:
            video_response = base_detect_image(self.camera, model=self.model)
        frame = np.array(copy(video_response))
        return frame