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small minor edits

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This commit is contained in:
davidpagnon 2024-06-24 17:21:56 +02:00
parent d277f13e99
commit 21a5e7742b
2 changed files with 21 additions and 10 deletions
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28
Pose2Sim/calibration.py
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@ -122,19 +122,23 @@ def read_qca(qca_path, binning_factor):
root = etree.parse(qca_path).getroot()
ret, C, S, D, K, R, T = [], [], [], [], [], [], []
res = []
vid_id = []
# Camera name
for i, tag in enumerate(root.findall('cameras/camera')):
ret += [float(tag.attrib.get('avg-residual'))]
C += [tag.attrib.get('serial')]
res += [int(tag.attrib.get('video_resolution')[:-1]) if tag.attrib.get('video_resolution') is not None else 1080]
if tag.attrib.get('model') in ('Miqus Video', 'Miqus Video UnderWater', 'none'):
vid_id += [i]
# Image size
for tag in root.findall('cameras/camera/fov_video'):
w = (float(tag.attrib.get('right')) - float(tag.attrib.get('left')) +1) /binning_factor
h = (float(tag.attrib.get('bottom')) - float(tag.attrib.get('top')) +1) /binning_factor
for i, tag in enumerate(root.findall('cameras/camera/fov_video')):
w = (float(tag.attrib.get('right')) - float(tag.attrib.get('left')) +1) /binning_factor \
/ (1080/res[i])
h = (float(tag.attrib.get('bottom')) - float(tag.attrib.get('top')) +1) /binning_factor \
/ (1080/res[i])
S += [[w, h]]
# Intrinsic parameters: distorsion and intrinsic matrix
@ -145,12 +149,16 @@ def read_qca(qca_path, binning_factor):
p2 = float(tag.get('tangentalDistortion2'))/64/binning_factor
D+= [np.array([k1, k2, p1, p2])]
fu = float(tag.get('focalLengthU'))/64/binning_factor
fv = float(tag.get('focalLengthV'))/64/binning_factor
cu = float(tag.get('centerPointU'))/64/binning_factor \
- float(root.findall('cameras/camera/fov_video')[i].attrib.get('left'))
cv = float(tag.get('centerPointV'))/64/binning_factor \
- float(root.findall('cameras/camera/fov_video')[i].attrib.get('top'))
fu = float(tag.get('focalLengthU'))/64/binning_factor \
/ (1080/res[i])
fv = float(tag.get('focalLengthV'))/64/binning_factor \
/ (1080/res[i])
cu = (float(tag.get('centerPointU'))/64/binning_factor \
- float(root.findall('cameras/camera/fov_video')[i].attrib.get('left'))) \
/ (1080/res[i])
cv = (float(tag.get('centerPointV'))/64/binning_factor \
- float(root.findall('cameras/camera/fov_video')[i].attrib.get('top'))) \
/ (1080/res[i])
K += [np.array([fu, 0., cu, 0., fv, cv, 0., 0., 1.]).reshape(3,3)]
# Extrinsic parameters: rotation matrix and translation vector
@ -696,7 +704,7 @@ def calibrate_extrinsics(calib_dir, extrinsics_config_dict, C, S, K, D):
logging.exception('No points clicked (or fewer than 6). Press \'C\' when the image is displayed, and then click on the image points corresponding to the \'object_coords_3d\' you measured and wrote down in the Config.toml file.')
raise ValueError('No points clicked (or fewer than 6). Press \'C\' when the image is displayed, and then click on the image points corresponding to the \'object_coords_3d\' you measured and wrote down in the Config.toml file.')
if len(objp) < 10:
logging.info(f'Only {len(objp)} reference points for camera {cam}. Calibration of extrinsic parameters may not be accurate with fewer than 10 reference points, as spread out as possible.')
logging.info(f'Only {len(objp)} reference points for camera {cam}. Calibration of extrinsic parameters may not be accurate with fewer than 10 reference points, as spread out in the captured volume as possible.')
elif extrinsics_method == 'keypoints':
logging.info('Calibration based on keypoints is not available yet.')

3
Pose2Sim/triangulation.py
View File

@ -886,6 +886,9 @@ def triangulate_all(config):
id_excluded_cams_tot = [id_excluded_cams_tot[n] for n in range(len(id_excluded_cams_tot)) if n not in deleted_person_id]
nb_persons_to_detect = len(Q_tot)
if nb_persons_to_detect ==0:
raise Exception('No persons have been triangulated. Please check your calibration and your synchronization, or the triangulation parameters in Config.toml.')
# IDs of excluded cameras
# id_excluded_cams_tot = [np.concatenate([id_excluded_cams_tot[f][k] for f in range(frames_nb)]) for k in range(keypoints_nb)]
id_excluded_cams_tot = [np.hstack(np.hstack(np.array(id_excluded_cams_tot[n]))) for n in range(nb_persons_to_detect)]