def meastype_name(i):
d = { 0: "boards",
1: "points",
2: "regularization" }
return d[i]
for test in tests:
try:
full = \
subprocess.check_output( [f"{testdir}/../test-gradients"] + test.split(),
shell = False,
encoding = 'ascii')
except Exception as e:
testutils.confirm(False, msg=f"failed to check gradients for '{test}'")
continue
varmap = get_variable_map(full)
measmap = get_measurement_map(full)
cut = subprocess.check_output( ("vnl-filter",
"gradient_reported || gradient_observed",
"--perl",
# I compute error_relative myself because I
# want to add an extra eps. This smoothes
# out reported relative gradient errors for
# tiny gradients. If they're tiny I could
# accidentally trigger an error otherwise
"-p", "error_relative=error/((abs(gradient_reported)+abs(gradient_observed))/2. + 1e-3)",
mrcal.apply_homography(H10, q0),
worstcase=True,
eps=0.1,
msg=f'out-of-bounds search_radius works ok')
templatesize_hw = np.array((templatesize[-1], templatesize[-2]))
testutils.confirm_equal(
diagnostics['matchoutput_image'].shape,
image1.shape - templatesize_hw + 1,
msg='out-of-bounds search radius looks at the whole image')
q1_matched, diagnostics = \
mrcal.match_feature( image*0, image1,
templatesize,
cv2.TM_CCOEFF_NORMED,
50,
q0,
H10_shifted)
testutils.confirm_equal(q1_matched,
None,
msg='failing correlation returns None')
try:
mrcal.match_feature(image * 0, image1, (5000, 5000), cv2.TM_CCOEFF_NORMED,
50, q0, H10_shifted)
except:
testutils.confirm(True, msg='Too-big template size throws an exception')
else:
testutils.confirm(False, msg='Too-big template size throws an exception')
testutils.finish()
az_fov_deg = 90
el_fov_deg = 50
models_rectified = \
mrcal.rectified_system( (model0, model1),
az_fov_deg = az_fov_deg,
el_fov_deg = el_fov_deg,
pixels_per_deg_az = -1./8.,
pixels_per_deg_el = -1./4.,
rectification_model = lensmodel)
az0 = 0.
el0 = 0.
try:
mrcal.stereo._validate_models_rectified(models_rectified)
testutils.confirm(True,
msg=f'Generated models pass validation ({lensmodel})')
except:
testutils.confirm(False,
msg=f'Generated models pass validation ({lensmodel})')
Rt_cam0_rect = mrcal.compose_Rt( model0.extrinsics_Rt_fromref(),
models_rectified[0].extrinsics_Rt_toref())
Rt01_rectified = mrcal.compose_Rt( models_rectified[0].extrinsics_Rt_fromref(),
models_rectified[1].extrinsics_Rt_toref())
testutils.confirm_equal(models_rectified[0].intrinsics()[0], lensmodel,
msg=f'model0 has the right lensmodel ({lensmodel})')
testutils.confirm_equal(models_rectified[1].intrinsics()[0], lensmodel,
msg=f'model1 has the right lensmodel ({lensmodel})')
testutils.confirm_equal(Rt_cam0_rect, mrcal.identity_Rt(),
any(on_bottom_edge) ):
return ": No points lie on the edge"
# all good
return ''
err_msg = \
fit_check( mrcal.scale_focal__best_pinhole_fit(m, 'corners'),
intrinsics_core,
mrcal.unproject( np.array((( 0 , 0),
(W-1, 0),
( 0, H-1),
(W-1, H-1)), dtype=float),
*m.intrinsics()),)
testutils.confirm( err_msg == '',
msg = 'scale_focal__best_pinhole_fit' + err_msg)
err_msg = \
fit_check( mrcal.scale_focal__best_pinhole_fit(m, 'centers-horizontal'),
intrinsics_core,
mrcal.unproject( np.array((( 0, (H-1.)/2.),
(W-1, (H-1.)/2.)), dtype=float),
*m.intrinsics()),)
testutils.confirm( err_msg == '',
msg = 'scale_focal__best_pinhole_fit' + err_msg)
err_msg = \
fit_check( mrcal.scale_focal__best_pinhole_fit(m, 'centers-vertical'),
intrinsics_core,
mrcal.unproject( np.array((((W-1.)/2., 0.),
((W-1.)/2., H-1.)), dtype=float),
observations_true, \
Nframes = \
calibration_baseline(model,
Ncameras,
Nframes,
None,
object_width_n,
object_height_n,
object_spacing,
extrinsics_rt_fromref_true,
calobject_warp_true,
fixedframes,
testdir)
for i in range(len(models_baseline)):
testutils.confirm(
not models_baseline[i]._extrinsics_moved_since_calibration(),
msg=f"Camera {i} unmoved")
extrinsics_rt_fromref = extrinsics_rt_fromref_true.copy()
extrinsics_rt_fromref[:, -1] += 1e-3
for i in range(len(models_baseline)):
models_baseline[i].extrinsics_rt_fromref(extrinsics_rt_fromref[i])
for i in range(len(models_baseline)):
testutils.confirm(models_baseline[i]._extrinsics_moved_since_calibration(),
msg=f"Camera {i} moved")
testutils.finish()
# I create geometries to test. First off, a vanilla geometry for left-right stereo
rt01 = np.array((0,0,0, 3.0, 0, 0))
model1.extrinsics_rt_toref( mrcal.compose_rt(model0.extrinsics_rt_toref(),
rt01))
az_fov_deg = 90
el_fov_deg = 50
models_rectified = \
mrcal.rectified_system( (model0, model1),
az_fov_deg = az_fov_deg,
el_fov_deg = el_fov_deg,
pixels_per_deg_az = -1./8.,
pixels_per_deg_el = -1./4.)
try:
mrcal.stereo._validate_models_rectified(models_rectified)
testutils.confirm(True,
msg='Generated models pass validation')
except:
testutils.confirm(False,
msg='Generated models pass validation')
Rt_cam0_stereo = mrcal.compose_Rt( model0.extrinsics_Rt_fromref(),
models_rectified[0].extrinsics_Rt_toref())
Rt01_rectified = mrcal.compose_Rt( models_rectified[0].extrinsics_Rt_fromref(),
models_rectified[1].extrinsics_Rt_toref())
fxycxy = models_rectified[0].intrinsics()[1]
testutils.confirm_equal(Rt_cam0_stereo, mrcal.identity_Rt(),
msg='vanilla stereo has a vanilla geometry')
testutils.confirm_equal( Rt01_rectified[3,0],
nps.mag(rt01[3:]),