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
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
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)
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)
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"
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()
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()
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')
