def configure_main_par(self, editor, object):
experiment = editor.get_parent(object)
paramset = object
print('Total paramsets:', len(experiment.paramsets))
if paramset.m_params is None:
# TODO: is it possible that control reaches here? If not, probably the if should be removed.
paramset.m_params = par.PtvParams()
else:
paramset.m_params._reload()
paramset.m_params.edit_traits(kind='modal')
def __init__(self, path):
# load ptv_par
ptvParams = par.PtvParams(path=path)
ptvParams.read()
self.n_img = ptvParams.n_img
# load cal_ori
calOriParams = par.CalOriParams(self.n_img, path=path)
calOriParams.read()
for i in range(self.n_img):
self.oriEditors.append(oriEditor(get_path(
calOriParams.img_ori[i])))
def _reload(self):
# print("reloading")
# self.__init__(self)
# load ptv_par
ptvParams = par.PtvParams(path=self.par_path)
ptvParams.read()
# read picture size parameters
self.h_image_size = ptvParams.imx
self.v_image_size = ptvParams.imy
self.h_pixel_size = ptvParams.pix_x
self.v_pixel_size = ptvParams.pix_y
self.img_cal = ptvParams.img_cal
if ptvParams.allCam_flag:
self.pair_enable_flag = False
else:
self.pair_enable_flag = True
# unesed parameters
self.n_img = ptvParams.n_img
self.img_name = ptvParams.img_name
self.hp_flag = np.bool(ptvParams.hp_flag)
self.allCam_flag = np.bool(ptvParams.allCam_flag)
self.mmp_n1 = ptvParams.mmp_n1
self.mmp_n2 = ptvParams.mmp_n2
self.mmp_n3 = ptvParams.mmp_n3
self.mmp_d = ptvParams.mmp_d
# read_calibration parameters
calOriParams = par.CalOriParams(self.n_img, path=self.par_path)
calOriParams.read()
(fixp_name, img_cal_name, img_ori, tiff_flag, pair_flag, chfield) = \
(calOriParams.fixp_name, calOriParams.img_cal_name, calOriParams.img_ori,
calOriParams.tiff_flag, calOriParams.pair_flag, calOriParams.chfield)
for i in range(self.n_img):
exec("self.cam_{0} = calOriParams.img_cal_name[{1}]".format(
i + 1, i))
exec("self.ori_cam_{0} = calOriParams.img_ori[{1}]".format(
i + 1, i))
self.tiff_head = np.bool(tiff_flag)
self.pair_head = np.bool(pair_flag)
self.fixp_name = fixp_name
if chfield == 0:
self.chfield = "Frame"
elif chfield == 1:
self.chfield = "Field odd"
else:
self.chfield = "Field even"
# read detect plate parameters
detectPlateParams = par.DetectPlateParams(path=self.par_path)
detectPlateParams.read()
(gv_th1, gv_th2, gv_th3, gv_th4, tolerable_discontinuity, min_npix, max_npix, min_npix_x,
max_npix_x, min_npix_y, max_npix_y, sum_of_grey, size_of_crosses) = \
(detectPlateParams.gvth_1, detectPlateParams.gvth_2, detectPlateParams.gvth_3, detectPlateParams.gvth_4,
detectPlateParams.tol_dis, detectPlateParams.min_npix, detectPlateParams.max_npix, detectPlateParams.min_npix_x,
detectPlateParams.max_npix_x, detectPlateParams.min_npix_y, detectPlateParams.max_npix_y, detectPlateParams.sum_grey,
detectPlateParams.size_cross)
for i in range(self.n_img):
exec('self.grey_value_treshold_{0} = gv_th{0}'.format(i + 1))
self.tolerable_discontinuity = tolerable_discontinuity
self.min_npix = min_npix
self.min_npix_x = min_npix_x
self.min_npix_y = min_npix_y
self.max_npix = max_npix
self.max_npix_x = max_npix_x
self.max_npix_y = max_npix_y
self.sum_of_grey = sum_of_grey
self.size_of_crosses = size_of_crosses
# read manual orientaion parameters
manOriParams = par.ManOriParams(self.n_img, [], path=self.par_path)
manOriParams.read()
for i in range(self.n_img):
for j in range(4): # 4 points per image
exec(f"self.img_{i+1}_p{j+1} = manOriParams.nr[{i*4+j}]")
# examine arameters
examineParams = par.ExamineParams(path=self.par_path)
examineParams.read()
(self.Examine_Flag, self.Combine_Flag) = (examineParams.Examine_Flag,
examineParams.Combine_Flag)
# orientation parameters
orientParams = par.OrientParams(path=self.par_path)
orientParams.read()
(po_num_of_ori, cc, xh, yh, k1, k2, k3, p1, p2, scale, shear, interf) = \
(orientParams.pnfo, orientParams.cc, orientParams.xh, orientParams.yh, orientParams.k1, orientParams.k2, orientParams.k3,
orientParams.p1, orientParams.p2, orientParams.scale, orientParams.shear, orientParams.interf)
self.point_number_of_orientation = po_num_of_ori
self.cc = np.bool(cc)
self.xh = np.bool(xh)
self.yh = np.bool(yh)
self.k1 = np.bool(k1)
self.k2 = np.bool(k2)
self.k3 = np.bool(k3)
self.p1 = np.bool(p1)
self.p2 = np.bool(p2)
self.scale = np.bool(scale)
self.shear = np.bool(shear)
self.interf = np.bool(interf)
dumbbellParams = par.DumbbellParams(path=self.par_path)
dumbbellParams.read()
(self.dumbbell_eps, self.dumbbell_scale, self.dumbbell_gradient_descent,
self.dumbbell_penalty_weight, self.dumbbell_step, self.dumbbell_niter) = \
(dumbbellParams.dumbbell_eps, dumbbellParams.dumbbell_scale,
dumbbellParams.dumbbell_gradient_descent, dumbbellParams.dumbbell_penalty_weight,
dumbbellParams.dumbbell_step, dumbbellParams.dumbbell_niter)
shakingParams = par.ShakingParams(path=self.par_path)
shakingParams.read()
(self.shaking_first_frame, self.shaking_last_frame,
self.shaking_max_num_points,
self.shaking_max_num_frames) = (shakingParams.shaking_first_frame,
shakingParams.shaking_last_frame,
shakingParams.shaking_max_num_points,
shakingParams.shaking_max_num_frames)
def _reload(self):
# load ptv_par
ptvParams = par.PtvParams(path=self.par_path)
ptvParams.read()
for i in range(ptvParams.n_img):
exec('self.Name_%d_Image = ptvParams.img_name[%d]' % (i + 1, i))
exec('self.Cali_%d_Image = ptvParams.img_cal[%d]' % (i + 1, i))
self.Refr_Air = ptvParams.mmp_n1
self.Refr_Glass = ptvParams.mmp_n2
self.Refr_Water = ptvParams.mmp_n3
self.Thick_Glass = ptvParams.mmp_d
self.Accept_OnlyAllCameras = np.bool(ptvParams.allCam_flag)
self.Num_Cam = ptvParams.n_img
self.HighPass = np.bool(ptvParams.hp_flag)
# load unused
self.tiff_flag = np.bool(ptvParams.tiff_flag)
self.imx = ptvParams.imx
self.imy = ptvParams.imy
self.pix_x = ptvParams.pix_x
self.pix_y = ptvParams.pix_y
self.chfield = ptvParams.chfield
# read_calibration parameters
calOriParams = par.CalOriParams(ptvParams.n_img, path=self.par_path)
calOriParams.read()
self.pair_Flag = np.bool(calOriParams.pair_flag)
self.img_cal_name = calOriParams.img_cal_name
self.img_ori = calOriParams.img_ori
self.fixp_name = calOriParams.fixp_name
# load read_targ_rec
targRecParams = par.TargRecParams(ptvParams.n_img, path=self.par_path)
targRecParams.read()
for i in range(ptvParams.n_img):
exec("self.Gray_Tresh_{0} = targRecParams.gvthres[{1}]".format(
i + 1, i))
self.Min_Npix = targRecParams.nnmin
self.Max_Npix = targRecParams.nnmax
self.Min_Npix_x = targRecParams.nxmin
self.Max_Npix_x = targRecParams.nxmax
self.Min_Npix_y = targRecParams.nymin
self.Max_Npix_y = targRecParams.nymax
self.Sum_Grey = targRecParams.sumg_min
self.Tol_Disc = targRecParams.disco
self.Size_Cross = targRecParams.cr_sz
# load pft_version
pftVersionParams = par.PftVersionParams(path=self.par_path)
pftVersionParams.read()
self.Existing_Target = np.bool(pftVersionParams.Existing_Target)
# load sequence_par
sequenceParams = par.SequenceParams(ptvParams.n_img,
path=self.par_path)
sequenceParams.read()
for i in range(ptvParams.n_img):
exec(
"self.Basename_{0}_Seq = sequenceParams.base_name[{1}]".format(
i + 1, i))
self.Seq_First = sequenceParams.first
self.Seq_Last = sequenceParams.last
# load criteria_par
criteriaParams = par.CriteriaParams(path=self.par_path)
criteriaParams.read()
self.Xmin = criteriaParams.X_lay[0]
self.Xmax = criteriaParams.X_lay[1]
self.Zmin1 = criteriaParams.Zmin_lay[0]
self.Zmin2 = criteriaParams.Zmin_lay[1]
self.Zmax1 = criteriaParams.Zmax_lay[0]
self.Zmax2 = criteriaParams.Zmax_lay[1]
self.Min_Corr_nx = criteriaParams.cnx
self.Min_Corr_ny = criteriaParams.cny
self.Min_Corr_npix = criteriaParams.cn
self.Sum_gv = criteriaParams.csumg
self.Min_Weight_corr = criteriaParams.corrmin
self.Tol_Band = criteriaParams.eps0
def closed(self, info, is_ok):
mainParams = info.object
par_path = mainParams.par_path
Handler.closed(self, info, is_ok)
if is_ok:
img_name = [
mainParams.Name_1_Image, mainParams.Name_2_Image,
mainParams.Name_3_Image, mainParams.Name_4_Image
]
img_cal_name = [
mainParams.Cali_1_Image, mainParams.Cali_2_Image,
mainParams.Cali_3_Image, mainParams.Cali_4_Image
]
gvthres = [
mainParams.Gray_Tresh_1, mainParams.Gray_Tresh_2,
mainParams.Gray_Tresh_3, mainParams.Gray_Tresh_4
]
base_name = [
mainParams.Basename_1_Seq, mainParams.Basename_2_Seq,
mainParams.Basename_3_Seq, mainParams.Basename_4_Seq
]
X_lay = [mainParams.Xmin, mainParams.Xmax]
Zmin_lay = [mainParams.Zmin1, mainParams.Zmin2]
Zmax_lay = [mainParams.Zmax1, mainParams.Zmax2]
# write ptv_par
par.PtvParams(mainParams.Num_Cam,
img_name,
img_cal_name,
mainParams.HighPass,
mainParams.Accept_OnlyAllCameras,
mainParams.tiff_flag,
mainParams.imx,
mainParams.imy,
mainParams.pix_x,
mainParams.pix_y,
mainParams.chfield,
mainParams.Refr_Air,
mainParams.Refr_Glass,
mainParams.Refr_Water,
mainParams.Thick_Glass,
path=par_path).write()
# write calibration parameters
par.CalOriParams(mainParams.Num_Cam,
mainParams.fixp_name,
mainParams.img_cal_name,
mainParams.img_ori,
mainParams.tiff_flag,
mainParams.pair_Flag,
mainParams.chfield,
path=par_path).write()
# write targ_rec_par
par.TargRecParams(mainParams.Num_Cam,
gvthres,
mainParams.Tol_Disc,
mainParams.Min_Npix,
mainParams.Max_Npix,
mainParams.Min_Npix_x,
mainParams.Max_Npix_x,
mainParams.Min_Npix_y,
mainParams.Max_Npix_y,
mainParams.Sum_Grey,
mainParams.Size_Cross,
path=par_path).write()
# write pft_version_par
par.PftVersionParams(mainParams.Existing_Target,
path=par_path).write()
# write sequence_par
par.SequenceParams(mainParams.Num_Cam,
base_name,
mainParams.Seq_First,
mainParams.Seq_Last,
path=par_path).write()
# write criteria_par
par.CriteriaParams(X_lay,
Zmin_lay,
Zmax_lay,
mainParams.Min_Corr_nx,
mainParams.Min_Corr_ny,
mainParams.Min_Corr_npix,
mainParams.Sum_gv,
mainParams.Min_Weight_corr,
mainParams.Tol_Band,
path=par_path).write()
def closed(self, info, is_ok):
calibParams = info.object
par_path = calibParams.par_path
print("inside CalHandler ", par_path)
Handler.closed(self, info, is_ok)
if is_ok:
img_cal_name = [
calibParams.cam_1, calibParams.cam_2, calibParams.cam_3,
calibParams.cam_4
]
img_ori = [
calibParams.ori_cam_1, calibParams.ori_cam_2,
calibParams.ori_cam_3, calibParams.ori_cam_4
]
nr1 = [
calibParams.img_1_p1, calibParams.img_1_p2,
calibParams.img_1_p3, calibParams.img_1_p4
]
nr2 = [
calibParams.img_2_p1, calibParams.img_2_p2,
calibParams.img_2_p3, calibParams.img_2_p4
]
nr3 = [
calibParams.img_3_p1, calibParams.img_3_p2,
calibParams.img_3_p3, calibParams.img_3_p4
]
nr4 = [
calibParams.img_4_p1, calibParams.img_4_p2,
calibParams.img_4_p3, calibParams.img_4_p4
]
nr = [nr1, nr2, nr3, nr4]
if (calibParams.chfield == "Frame"):
chfield = 0
elif (calibParams.chfield == "Field odd"):
chfield = 1
else:
chfield = 2
par.PtvParams(calibParams.n_img,
calibParams.img_name,
calibParams.img_cal,
calibParams.hp_flag,
calibParams.allCam_flag,
calibParams.tiff_head,
calibParams.h_image_size,
calibParams.v_image_size,
calibParams.h_pixel_size,
calibParams.v_pixel_size,
chfield,
calibParams.mmp_n1,
calibParams.mmp_n2,
calibParams.mmp_n3,
calibParams.mmp_d,
path=par_path).write()
par.CalOriParams(calibParams.n_img,
calibParams.fixp_name,
img_cal_name,
img_ori,
calibParams.tiff_head,
calibParams.pair_head,
chfield,
path=par_path).write()
par.DetectPlateParams(calibParams.grey_value_treshold_1,
calibParams.grey_value_treshold_2,
calibParams.grey_value_treshold_3,
calibParams.grey_value_treshold_4,
calibParams.tolerable_discontinuity,
calibParams.min_npix,
calibParams.max_npix,
calibParams.min_npix_x,
calibParams.max_npix_x,
calibParams.min_npix_y,
calibParams.max_npix_y,
calibParams.sum_of_grey,
calibParams.size_of_crosses,
path=par_path).write()
par.ManOriParams(calibParams.n_img, nr, path=par_path).write()
par.ExamineParams(calibParams.Examine_Flag,
calibParams.Combine_Flag,
path=par_path).write()
par.OrientParams(calibParams.point_number_of_orientation,
calibParams.cc,
calibParams.xh,
calibParams.yh,
calibParams.k1,
calibParams.k2,
calibParams.k3,
calibParams.p1,
calibParams.p2,
calibParams.scale,
calibParams.shear,
calibParams.interf,
path=par_path).write()
par.ShakingParams(calibParams.shaking_first_frame,
calibParams.shaking_last_frame,
calibParams.shaking_max_num_points,
calibParams.shaking_max_num_frames,
path=par_path).write()
par.DumbbellParams(calibParams.dumbbell_eps,
calibParams.dumbbell_scale,
calibParams.dumbbell_gradient_descent,
calibParams.dumbbell_penalty_weight,
calibParams.dumbbell_step,
calibParams.dumbbell_niter,
path=par_path).write()