Esempio n. 1
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def get_cam(camera_name="91"):
    for cam in m.get_cams():
        if camera_name in cam.name:
            # cam.frame_rate=100
            # m.update()
            # m.update()
            # m.update()
            return cam
Esempio n. 2
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def get_cam(camera_name="91"):
    for cam in m.get_cams():
        if camera_name in cam.name:
            # cam.frame_rate=100
            # m.update()
            # m.update()
            # m.update()
            return cam
Esempio n. 3
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def motive_camera_vislight_configure():

    for cam in motive.get_cams():

        # All cameras should have frame rate changed.
        cam.frame_rate = 30

        if 'Prime 13' in cam.name:
            cam.settings = motive.CameraSettings(video_mode=2, exposure=33000, threshold=200, intensity=0)
            cam.image_gain = 5  # 8 is the maximum image gain setting
            cam.set_filter_switch(False)
        else:
            cam.settings = motive.CameraSettings(video_mode=0, exposure=cam.exposure, threshold=cam.threshold, intensity=cam.intensity)
Esempio n. 4
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def motive_camera_vislight_configure():
    import motive
    for cam in motive.get_cams():

        # All cameras should have frame rate changed.
        cam.frame_rate = 30

        if 'Prime 13' in cam.name:
            cam.set_settings(video_mode=0, exposure=33000, threshold=80, intensity=0)  #check if 480 corresponds to these thousands described in motive
            cam.image_gain = 8  # 8 is the maximum image gain setting
            cam.set_filter_switch(False)
        else:
            cam.set_settings(0, cam.exposure, cam.threshold, cam.intensity)
Esempio n. 5
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def motive_camera_vislight_configure():

    for cam in motive.get_cams():

        # All cameras should have frame rate changed.
        cam.frame_rate = 30

        if 'Prime 13' in cam.name:
            cam.set_settings(
                video_mode=0, exposure=33000, threshold=200, intensity=0
            )  #check if 480 corresponds to these thousands described in motive
            cam.image_gain = 8  # 8 is the maximum image gain setting
            cam.set_filter_switch(False)
        else:
            cam.set_settings(0, cam.exposure, cam.threshold, cam.intensity)
                        help='If this flag is present, the arena will be NOT offset by its mean marker position.')

    parser.add_argument('-r', action='store', dest='rigid_body_name', default='',
                        help='Name of the Arena rigid body. If only one rigid body is present, unnecessary--that one will be used automatically.')

    parser.add_argument('-i', action='store', dest='motive_projectfile', default=motive.utils.backup_project_filename,
                        help='Name of the motive project file to load.  If not used, will load most recent Project file loaded in MotivePy.')

    args = parser.parse_args()

    # Select Rigid Body to track.
    motive.load_project(args.motive_projectfile)
    print("Loaded Motive Project: {}".format(args.motive_projectfile))
    hardware.motive_camera_vislight_configure()
    print("Camera Settings changed to Detect Visible light:")
    print("\t"+"\n\t".join(['{}: FPS={}, Gain={}, Exp.={}, Thresh.={}'.format(cam.name, cam.frame_rate, cam.image_gain, cam.exposure, cam.threshold) for cam in motive.get_cams()]))

    motive.update()

    rigid_bodies = motive.get_rigid_bodies()
    try:
        if not args.rigid_body_name:
            assert len(rigid_bodies) == 1, "Only one rigid body should be present for auto-selection. Please use the -r flag to specify a rigid body name to track for the arena."
        arena_name = args.rigid_body_name if args.rigid_body_name in rigid_bodies else rigid_bodies.keys()[0]
    except IndexError:
        raise IndexError("No Rigid Bodies found in Optitrack tracker.")
    except KeyError:
        raise KeyError("Rigid Body '{}' not found in list of Optitrack Rigid Bodies.".format(arena_name))

    print('Arena Name: {}. N Markers: {}'.format(arena_name, len(rigid_bodies[arena_name].markers)))
    assert len(rigid_bodies[arena_name].markers) > 5, "At least 6 markers in the arena's rigid body is required"
Esempio n. 7
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if __name__ == '__main__':

    import Tkinter, tkFileDialog
    from os import path
    import motive as m

    root = Tkinter.Tk()
    root.withdraw()
    profile_file_u = tkFileDialog.askopenfilename(
        title='Choose a profile file to load: ',
        filetypes=[('motive profilefiles', '*.motive')])
    profile_file = profile_file_u.encode("ascii")
    m.load_profile(profile_file)

    for cam in m.get_cams():
        cam.frame_rate = 30

        if 'Prime 13' in cam.name:
            cam.set_settings(
                videotype=0, exposure=33000, threshold=40, intensity=0
            )  #check if 480 corresponds to these thousands described in motive
            cam.image_gain = 8  # 8 is the maximum image gain setting
            cam.set_filter_switch(False)
        else:
            cam.set_settings(0, cam.exposure, cam.threshold, cam.intensity)

    directory, extension = path.splitext(profile_file)
    saved_profile_pathname = ''.join([directory, '_vislight', extension])
    m.save_profile(saved_profile_pathname)
    m.shutdown()
Esempio n. 8
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if __name__ == '__main__':

    import Tkinter, tkFileDialog
    from os import path
    import motive as m

    root = Tkinter.Tk()
    root.withdraw()
    project_file_u=tkFileDialog.askopenfilename(title='Choose a project file to load: ', filetypes=[('motive projectfiles', '*.ttp')])
    project_file = project_file_u.encode("ascii")
    m.load_project(project_file)

    for cam in m.get_cams():
        cam.frame_rate = 30

        if 'Prime 13' in cam.name:
            cam.set_settings(videotype=0, exposure=33000, threshold=40, intensity=0)  #check if 480 corresponds to these thousands described in motive
            cam.image_gain = 8  # 8 is the maximum image gain setting
            cam.set_filter_switch(False)
        else:
            cam.set_settings(0, cam.exposure, cam.threshold, cam.intensity)

    directory, extension = path.splitext(project_file)
    saved_project_pathname= ''.join([directory, '_vislight', extension])
    m.save_project(saved_project_pathname)
    m.shutdown()




Esempio n. 9
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def scan_arena(motive_filename, output_filename, body, nomeancenter, nsides, screen):
    """Runs Arena Scanning algorithm."""

    output_filename = output_filename + '.obj' if not path.splitext(output_filename)[1] else output_filename
    assert path.splitext(output_filename)[1] == '.obj', "Output arena filename must be a Wavefront (.obj) file"

    # Load Motive Project File
    motive_filename = motive_filename.encode()
    motive.initialize()
    motive.load_project(motive_filename)

    # Get old camera settings before changing them, to go back to them before saving later.
    cam_settings = [cam.settings for cam in motive.get_cams()]
    frame_rate_old = motive.get_cams()[0].frame_rate
    hardware.motive_camera_vislight_configure()
    motive.update()

    # Get Arena's Rigid Body
    rigid_bodies = motive.get_rigid_bodies()
    assert body in rigid_bodies, "RigidBody {} not found in project file.  Available body names: {}".format(body, list(rigid_bodies.keys()))
    # assert len(rigid_bodies[body].markers) > 5, "At least 6 markers in the arena's rigid body is required. Only {} found".format(len(rigid_bodies[body].markers))

    for el in range(3):
        rigid_bodies[body].reset_orientation()
        rigid_bodies[body].reset_pivot_offset()
        motive.update()
    assert np.isclose(np.array(rigid_bodies[body].rotation), 0).all(), "Orientation didn't reset."
    assert np.isclose(np.array(rigid_bodies[body].location), np.mean(rigid_bodies[body].point_cloud_markers, axis=0)).all(), "Pivot didn't reset."
    print("Location and Orientation Successfully reset.")

    # Scan points
    display = pyglet.window.get_platform().get_default_display()
    screen = display.get_screens()[screen]
    window = GridScanWindow(screen=screen, fullscreen=True)
    pyglet.app.run()
    points = np.array(window.marker_pos)
    assert(len(points) > 100), "Only {} points detected.  Tracker is not detecting enough points to model.  Is the projector turned on?".format(len(points))
    assert points.ndim == 2

    # Plot preview of data collected
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    ax.scatter(*points.T)
    plt.show()

    # Get vertex positions and normal directions from the collected data.
    vertices, normals = pointcloud.meshify_arena(points, n_surfaces=nsides)
    vertices, face_indices = pointcloud.face_index(vertices)
    face_indices = pointcloud.fan_triangulate(face_indices)



    # Reapply old camera settings, then save.
    for setting, cam in zip(cam_settings, motive.get_cams()):
        cam.settings = setting
        cam.image_gain = 1
        cam.frame_rate = frame_rate_old
        if 'Prime 13' in cam.name:
            cam.set_filter_switch(True)
    motive.update()


    # me
    if not nomeancenter:

        # import ipdb
        # ipdb.set_trace()
        vertmean = np.mean(vertices[face_indices.flatten(), :], axis=0)

        # vertmean = np.array([np.mean(np.unique(verts)) for verts in vertices.T])  # to avoid counting the same vertices twice.
        vertices -= vertmean
        points -= vertmean
        print('Old Location: {}'.format(rigid_bodies[body].location))
        arena = rigid_bodies[body]
        for attempt in range(300):
            print('Trying to Set New Rigid Body location, attempt {}...'.format(attempt))
            arena.reset_pivot_offset()
            arena.location = vertmean
            if np.isclose(arena.location, vertmean, rtol=.001).all():
                break
        else:
            raise ValueError('Motive failed to properly shift pivot to center of mesh')
        print('Vertex Mean: {}'.format(vertmean))
        print('New Location: {}'.format(arena.location))


    # Write wavefront .obj file to app data directory and user-specified directory for importing into Blender.

    writer = WavefrontWriter.from_indexed_arrays(body, vertices, normals, face_indices)
    with open(output_filename, 'w') as f:
        writer.dump(output_filename)


    # Show resulting plot with points and model in same place.
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')

    ax.scatter(*points[::12, :].T)
    ax.scatter(*vertices.T, c='r')
    plt.show()


    # motive.save_project(motive_filename)
    motive.save_project(path.splitext(motive_filename)[0]+'_scanned.ttp')