def check_mcsc_roundtrip(with_rad_files=False,align_existing=False):
np.random.seed(3)
mcscdir = os.path.join( os.path.dirname(mcsce.__file__),
'..', '..', 'MultiCamSelfCal' )
mcscdir = os.path.abspath(mcscdir)
out_dirname = tempfile.mkdtemp()
try:
mcsc = mcsce.MultiCamSelfCal(out_dirname=out_dirname,mcscdir=mcscdir)
if with_rad_files:
orig_cams = make_default_system(with_separate_distorions=True)
else:
orig_cams = make_default_system()
cam_resolutions = dict( (n['name'], (n['width'],n['height']))
for n in orig_cams.to_dict()['camera_system'])
pts_3d = get_default_points()
if 0:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from pymvg.plot_utils import plot_camera
np.set_printoptions(precision=3, suppress=True)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for name,cam in orig_cams.get_camera_dict().iteritems():
print()
print(name,'-'*80)
print(' center:',cam.get_camcenter())
print(' lookat:',cam.get_lookat())
print(' up:',cam.get_up())
print(' P')
print(cam.P)
print()
plot_camera( ax, cam)#, scale = dim/5.0 )
ax.plot( pts_3d[:,0], pts_3d[:,1], pts_3d[:,2], 'k.')
plt.show()
cam_points=defaultdict(list)
nan_tup = (np.nan, np.nan)
for pt_3d in pts_3d:
valid = True
for name in orig_cams.get_names():
w,h = cam_resolutions[name]
x,y = orig_cams.find2d( name, pt_3d )
if 1:
# add noise to the 2D images
xn, yn = 0.01*np.random.randn( 2 )
x += xn
y += yn
if (0 <= x) and (x < w) and (0 <= y) and (y < h):
cam_points[name].append((x,y))
else:
cam_points[name].append(nan_tup)
valid = False
if not valid:
for name in orig_cams.get_names():
cam_points[name].pop()
cam_ids=orig_cams.get_names()
if with_rad_files:
cam_calibrations = {} # dictionary of .yaml filenames with ROS yaml format
raise NotImplementedError
else:
cam_calibrations = {}
if align_existing:
cam_centers = np.array([ orig_cams.get_cam(n).get_camcenter() for n in orig_cams.get_names() ]).T
else:
cam_centers = []
mcsc.create_from_cams(cam_ids=cam_ids,
cam_resolutions=cam_resolutions,
cam_points=cam_points,
cam_calibrations=cam_calibrations,
cam_centers=cam_centers,
)
result = mcsc.execute(silent=True)
raw_cams = MultiCameraSystem.from_mcsc( result )
if align_existing:
aligned_cams = raw_cams
else:
aligned_cams = raw_cams.get_aligned_copy( orig_cams )
assert is_close(orig_cams,aligned_cams,pts_3d)
finally:
shutil.rmtree(out_dirname)
def test_load_mcsc():
mydir = os.path.dirname(__file__)
mcsc_dirname = os.path.join(mydir,'mcsc_output_20130726')
cam_system = MultiCameraSystem.from_mcsc( mcsc_dirname )
def check_mcsc_roundtrip(with_rad_files=False, align_existing=False):
np.random.seed(3)
mcscdir = os.path.join(os.path.dirname(mcsce.__file__), '..', '..',
'MultiCamSelfCal')
mcscdir = os.path.abspath(mcscdir)
out_dirname = tempfile.mkdtemp()
try:
mcsc = mcsce.MultiCamSelfCal(out_dirname=out_dirname, mcscdir=mcscdir)
if with_rad_files:
orig_cams = make_default_system(with_separate_distorions=True)
else:
orig_cams = make_default_system()
cam_resolutions = dict((n['name'], (n['width'], n['height']))
for n in orig_cams.to_dict()['camera_system'])
pts_3d = get_default_points()
if 0:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from pymvg.plot_utils import plot_camera
np.set_printoptions(precision=3, suppress=True)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for name, cam in orig_cams.get_camera_dict().iteritems():
print()
print(name, '-' * 80)
print(' center:', cam.get_camcenter())
print(' lookat:', cam.get_lookat())
print(' up:', cam.get_up())
print(' P')
print(cam.P)
print()
plot_camera(ax, cam) #, scale = dim/5.0 )
ax.plot(pts_3d[:, 0], pts_3d[:, 1], pts_3d[:, 2], 'k.')
plt.show()
cam_points = defaultdict(list)
nan_tup = (np.nan, np.nan)
for pt_3d in pts_3d:
valid = True
for name in orig_cams.get_names():
w, h = cam_resolutions[name]
x, y = orig_cams.find2d(name, pt_3d)
if 1:
# add noise to the 2D images
xn, yn = 0.01 * np.random.randn(2)
x += xn
y += yn
if (0 <= x) and (x < w) and (0 <= y) and (y < h):
cam_points[name].append((x, y))
else:
cam_points[name].append(nan_tup)
valid = False
if not valid:
for name in orig_cams.get_names():
cam_points[name].pop()
cam_ids = orig_cams.get_names()
if with_rad_files:
cam_calibrations = {
} # dictionary of .yaml filenames with ROS yaml format
raise NotImplementedError
else:
cam_calibrations = {}
if align_existing:
cam_centers = np.array([
orig_cams.get_cam(n).get_camcenter()
for n in orig_cams.get_names()
]).T
else:
cam_centers = []
mcsc.create_from_cams(
cam_ids=cam_ids,
cam_resolutions=cam_resolutions,
cam_points=cam_points,
cam_calibrations=cam_calibrations,
cam_centers=cam_centers,
)
result = mcsc.execute(silent=True)
raw_cams = MultiCameraSystem.from_mcsc(result)
if align_existing:
aligned_cams = raw_cams
else:
aligned_cams = raw_cams.get_aligned_copy(orig_cams)
assert is_close(orig_cams, aligned_cams, pts_3d)
finally:
shutil.rmtree(out_dirname)
def test_load_mcsc():
mydir = os.path.dirname(__file__)
mcsc_dir = os.path.join(mydir, 'external', 'mcsc')
mcsc_dirname = os.path.join(mcsc_dir, 'mcsc_output_20130726')
cam_system = MultiCameraSystem.from_mcsc(mcsc_dirname)
def test_pymvg_roundtrip():
from pymvg.camera_model import CameraModel
from pymvg.multi_camera_system import MultiCameraSystem
from flydra_core.reconstruct import Reconstructor
# ----------- with no distortion ------------------------
center1 = np.array( (0, 0.0, 5) )
center2 = np.array( (1, 0.0, 5) )
lookat = np.array( (0,1,0))
cam1 = CameraModel.load_camera_simple(fov_x_degrees=90,
name='cam1',
eye=center1,
lookat=lookat)
cam2 = CameraModel.load_camera_simple(fov_x_degrees=90,
name='cam2',
eye=center2,
lookat=lookat)
mvg = MultiCameraSystem( cameras=[cam1, cam2] )
R = Reconstructor.from_pymvg(mvg)
mvg2 = R.convert_to_pymvg()
cam_ids = ['cam1','cam2']
for distorted in [True,False]:
for cam_id in cam_ids:
v1 = mvg.find2d( cam_id, lookat, distorted=distorted )
v2 = R.find2d( cam_id, lookat, distorted=distorted )
v3 = mvg2.find2d( cam_id, lookat, distorted=distorted )
assert np.allclose(v1,v2)
assert np.allclose(v1,v3)
# ----------- with distortion ------------------------
cam1dd = cam1.to_dict()
cam1dd['D'] = (0.1, 0.2, 0.3, 0.4, 0.0)
cam1d = CameraModel.from_dict(cam1dd)
cam2dd = cam2.to_dict()
cam2dd['D'] = (0.11, 0.21, 0.31, 0.41, 0.0)
cam2d = CameraModel.from_dict(cam2dd)
mvgd = MultiCameraSystem( cameras=[cam1d, cam2d] )
Rd = Reconstructor.from_pymvg(mvgd)
mvg2d = Rd.convert_to_pymvg()
cam_ids = ['cam1','cam2']
for distorted in [True,False]:
for cam_id in cam_ids:
v1 = mvgd.find2d( cam_id, lookat, distorted=distorted )
v2 = Rd.find2d( cam_id, lookat, distorted=distorted )
v3 = mvg2d.find2d( cam_id, lookat, distorted=distorted )
assert np.allclose(v1,v2)
assert np.allclose(v1,v3)
# ------------ with distortion at different focal length ------
mydir = os.path.dirname(__file__)
caldir = os.path.join(mydir,'sample_calibration')
print mydir
print caldir
R3 = Reconstructor(caldir)
mvg3 = R3.convert_to_pymvg()
#R4 = Reconstructor.from_pymvg(mvg3)
mvg3b = MultiCameraSystem.from_mcsc( caldir )
for distorted in [True,False]:
for cam_id in R3.cam_ids:
v1 = R3.find2d( cam_id, lookat, distorted=distorted )
v2 = mvg3.find2d( cam_id, lookat, distorted=distorted )
#v3 = R4.find2d( cam_id, lookat, distorted=distorted )
v4 = mvg3b.find2d( cam_id, lookat, distorted=distorted )
assert np.allclose(v1,v2)
#assert np.allclose(v1,v3)
assert np.allclose(v1,v4)