def paramsFactory(filename, n_img, n_pts=4):
if filename == "ptv.par":
return parameters.PtvParams()
if filename == "cal_ori.par":
return parameters.CalOriParams(n_img)
if filename == "sequence.par":
return parameters.SequenceParams(n_img)
if filename == "criteria.par":
return parameters.CriteriaParams()
if filename == "targ_rec.par":
return parameters.TargRecParams(n_img)
if filename == "man_ori.par":
return parameters.ManOriParams(n_img, n_pts)
if filename == "detect_plate.par":
return parameters.DetectPlateParams()
if filename == "orient.par":
return parameters.OrientParams()
if filename == "track.par":
return parameters.TrackingParams()
if filename == "pft_version.par":
return parameters.PftVersionParams()
if filename == "examine.par":
return parameters.ExamineParams()
if filename == "dumbbell.par":
return parameters.DumbbellParams()
if filename == "shaking.par":
return parameters.ShakingParams()
return None
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 py_detection_proc_c(list_of_images, cpar, tpar, cals):
""" Detection of targets """
pftVersionParams = par.PftVersionParams(path='./parameters')
pftVersionParams.read()
Existing_Target = np.bool(pftVersionParams.Existing_Target)
detections, corrected = [],[]
for i_cam, img in enumerate(list_of_images):
if Existing_Target:
targs = read_targets(cpar.get_img_base_name(i_cam),0)
else:
targs = target_recognition(img, tpar, i_cam, cpar)
targs.sort_y()
detections.append(targs)
mc = MatchedCoords(targs, cpar, cals[i_cam])
corrected.append(mc)
return detections, corrected
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 _reload(self):
# load ptv_par
ptvParams = par.PtvParams(path=self.par_path)
ptvParams.read()
(n_img, img_name, img_cal, hp_flag, allCam_flag, tiff_flag, imx, imy, pix_x, pix_y, chfield, mmp_n1, mmp_n2, mmp_n3, mmp_d) = \
(ptvParams.n_img, ptvParams.img_name, ptvParams.img_cal, ptvParams.hp_flag, ptvParams.allCam_flag, ptvParams.tiff_flag,
ptvParams.imx, ptvParams.imy, ptvParams.pix_x, ptvParams.pix_y, ptvParams.chfield, ptvParams.mmp_n1, ptvParams.mmp_n2, ptvParams.mmp_n3, ptvParams.mmp_d)
self.Name_1_Image = img_name[0]
self.Name_2_Image = img_name[1]
self.Name_3_Image = img_name[2]
self.Name_4_Image = img_name[3]
self.Cali_1_Image = img_cal[0]
self.Cali_2_Image = img_cal[1]
self.Cali_3_Image = img_cal[2]
self.Cali_4_Image = img_cal[3]
self.Refr_Air = mmp_n1
self.Refr_Glass = mmp_n2
self.Refr_Water = mmp_n3
self.Thick_Glass = mmp_d
self.Accept_OnlyAllCameras = n.bool(allCam_flag)
self.Num_Cam = n_img
self.HighPass = n.bool(hp_flag)
# load unused
self.tiff_flag = n.bool(tiff_flag)
self.imx = imx
self.imy = imy
self.pix_x = pix_x
self.pix_y = pix_y
self.chfield = chfield
# read_calibration parameters
calOriParams = par.CalOriParams(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)
self.pair_Flag = n.bool(pair_flag)
self.img_cal_name = img_cal_name
self.img_ori = img_ori
self.fixp_name = fixp_name
# load read_targ_rec
targRecParams = par.TargRecParams(n_img, path=self.par_path)
targRecParams.read()
(gvthres, disco, nnmin, nnmax, nxmin, nxmax, nymin, nymax, sumg_min, cr_sz) = \
(targRecParams.gvthres, targRecParams.disco, targRecParams.nnmin, targRecParams.nnmax, targRecParams.nxmin,
targRecParams.nxmax, targRecParams.nymin, targRecParams.nymax, targRecParams.sumg_min, targRecParams.cr_sz)
self.Gray_Tresh_1 = gvthres[0]
self.Gray_Tresh_2 = gvthres[1]
self.Gray_Tresh_3 = gvthres[2]
self.Gray_Tresh_4 = gvthres[3]
self.Min_Npix = nnmin
self.Max_Npix = nnmax
self.Min_Npix_x = nxmin
self.Max_Npix_x = nxmax
self.Min_Npix_y = nymin
self.Max_Npix_y = nymax
self.Sum_Grey = sumg_min
self.Tol_Disc = disco
self.Size_Cross = cr_sz
# load pft_version
pftVersionParams = par.PftVersionParams(path=self.par_path)
pftVersionParams.read()
self.Existing_Target = n.bool(pftVersionParams.Existing_Target)
# load sequence_par
sequenceParams = par.SequenceParams(n_img, path=self.par_path)
sequenceParams.read()
(base_name, first, last) = \
(sequenceParams.base_name, sequenceParams.first, sequenceParams.last)
self.Basename_1_Seq = base_name[0]
self.Basename_2_Seq = base_name[1]
self.Basename_3_Seq = base_name[2]
self.Basename_4_Seq = base_name[3]
self.Seq_First = first
self.Seq_Last = last
# load criteria_par
criteriaParams = par.CriteriaParams(path=self.par_path)
criteriaParams.read()
(X_lay, Zmin_lay, Zmax_lay, cnx, cny, cn, csumg, corrmin, eps0) = \
(criteriaParams.X_lay, criteriaParams.Zmin_lay, criteriaParams.Zmax_lay, criteriaParams.cnx,
criteriaParams.cny, criteriaParams.cn, criteriaParams.csumg, criteriaParams.corrmin, criteriaParams.eps0)
self.Xmin = X_lay[0]
self.Xmax = X_lay[1]
self.Zmin1 = Zmin_lay[0]
self.Zmin2 = Zmin_lay[1]
self.Zmax1 = Zmax_lay[0]
self.Zmax2 = Zmax_lay[1]
self.Min_Corr_nx = cnx
self.Min_Corr_ny = cny
self.Min_Corr_npix = cn
self.Sum_gv = csumg
self.Min_Weight_corr = corrmin
self.Tol_Band = eps0
def py_sequence_loop(exp):
""" Runs a sequence of detection, stereo-correspondence, determination and stores
the data in the cam#.XXX_targets (rewritten) and rt_is.XXX files. Basically
it is to run the batch as in pyptv_batch.py without tracking
"""
n_cams, cpar, spar, vpar, tpar, cals = \
exp.n_cams, exp.cpar, exp.spar, exp.vpar, exp.tpar, exp.cals
pftVersionParams = par.PftVersionParams(path='./parameters')
pftVersionParams.read()
Existing_Target = np.bool(pftVersionParams.Existing_Target)
# sequence loop for all frames
for frame in range(spar.get_first(), spar.get_last()+1):
print("processing frame %d" % frame)
detections = []
corrected = []
for i_cam in range(n_cams):
if Existing_Target:
targs = read_targets(spar.get_img_base_name(i_cam),frame)
else:
imname = spar.get_img_base_name(i_cam) + str(frame).encode()
print(imname)
if not os.path.exists(imname):
print(os.path.abspath(os.path.curdir))
print('{0} does not exist'.format(imname))
img = imread(imname.decode())
# time.sleep(.1) # I'm not sure we need it here
hp = simple_highpass(img, cpar)
targs = target_recognition(hp, tpar, i_cam, cpar)
targs.sort_y()
detections.append(targs)
mc = MatchedCoords(targs, cpar, cals[i_cam])
pos, pnr = mc.as_arrays()
corrected.append(mc)
# if any([len(det) == 0 for det in detections]):
# return False
# Corresp. + positions.
sorted_pos, sorted_corresp, num_targs = correspondences(
detections, corrected, cals, vpar, cpar)
# Save targets only after they've been modified:
for i_cam in range(n_cams):
detections[i_cam].write(spar.get_img_base_name(i_cam),frame)
print("Frame " + str(frame) + " had " \
+ repr([s.shape[1] for s in sorted_pos]) + " correspondences.")
# Distinction between quad/trip irrelevant here.
sorted_pos = np.concatenate(sorted_pos, axis=1)
sorted_corresp = np.concatenate(sorted_corresp, axis=1)
flat = np.array([corrected[i].get_by_pnrs(sorted_corresp[i]) \
for i in range(len(cals))])
pos, rcm = point_positions(
flat.transpose(1,0,2), cpar, cals, vpar)
# if len(cals) == 1: # single camera case
# sorted_corresp = np.tile(sorted_corresp,(4,1))
# sorted_corresp[1:,:] = -1
if len(cals) < 4:
print_corresp = -1*np.ones((4,sorted_corresp.shape[1]))
print_corresp[:len(cals),:] = sorted_corresp
else:
print_corresp = sorted_corresp
# Save rt_is
print(default_naming['corres'])
rt_is = open(default_naming['corres']+b'.'+ str(frame).encode(), 'w')
rt_is.write(str(pos.shape[0]) + '\n')
for pix, pt in enumerate(pos):
pt_args = (pix + 1,) + tuple(pt) + tuple(print_corresp[:,pix])
rt_is.write("%4d %9.3f %9.3f %9.3f %4d %4d %4d %4d\n" % pt_args)
rt_is.close()
