43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
from copy import deepcopy, copy
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import numpy as np
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from DeviceDefine.consensus import UNKNOWN
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from MCamera.mn_algorithm import MoveNetAlgorithmPlugin
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from MCamera.mp_algorithm import MediapipeAlgorithmPlugin
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from MCamera.mp_camera import Camera
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from PureBackend.base_driver import MODEL_MEDIAPIPE, MODEL_MOVE_NET
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from PureBackend.exam_driver import ExamDriver
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def base_detect_image(camera: Camera, model):
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if model == MODEL_MEDIAPIPE:
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_map = MediapipeAlgorithmPlugin()
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_img = deepcopy(camera.get_frame())
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img = _map.find_pose_with_drawing(_img, True)
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elif model == MODEL_MOVE_NET:
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_map = MoveNetAlgorithmPlugin()
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_img = deepcopy(camera.get_frame())
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img = _map.find_pose_with_drawing(_img, True)
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return img
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class CameraBackend(ExamDriver):
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def __init__(self, master_mode=True, positioning=True, camera=True, model=MODEL_MEDIAPIPE, speaker=True,
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multi_positioning_mode=True, device_type=UNKNOWN, pure_mode=False):
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super().__init__(master_mode, positioning, camera, model, speaker, multi_positioning_mode, device_type, pure_mode)
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self.model = model
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def get_exercise_video(self):
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if self.project is None:
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video_response = base_detect_image(self.camera, model=self.model)
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elif self.project and not self.project.is_start:
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video_response = self.project.pure_video_gen()
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else:
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video_response = self.project.pure_streaming_gen()
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if video_response is None:
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video_response = base_detect_image(self.camera, model=self.model)
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frame = np.array(copy(video_response))
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return frame
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