option to fill large gaps with nan, last valid value, or zeros

Pose2Sim/Demo_MultiPerson/Config.toml

@@ -143,6 +143,7 @@ min_cameras_for_triangulation = 2
 interpolation = 'cubic' #linear, slinear, quadratic, cubic, or none
                         # 'none' if you don't want to interpolate missing points
 interp_if_gap_smaller_than = 10 # do not interpolate bigger gaps
+fill_large_gaps_with = 'last_value' # 'last_value', 'nan', or 'zeros' 
 show_interp_indices = true # true or false (lowercase). For each keypoint, return the frames that need to be interpolated
 handle_LR_swap = false # Better if few cameras (eg less than 4) with risk of limb swapping (eg camera facing sagittal plane), otherwise slightly less accurate and slower
 undistort_points = false # Better if distorted image (parallel lines curvy on the edge or at least one param > 10^-2), but unnecessary (and slightly slower) if distortions are low

Pose2Sim/Demo_SinglePerson/Config.toml

@@ -144,6 +144,7 @@ interpolation = 'cubic' #linear, slinear, quadratic, cubic, or none
                         # 'none' if you don't want to interpolate missing points
 interp_if_gap_smaller_than = 10 # do not interpolate bigger gaps
 show_interp_indices = true # true or false (lowercase). For each keypoint, return the frames that need to be interpolated
+fill_large_gaps_with = 'last_value' # 'last_value', 'nan', or 'zeros' 
 handle_LR_swap = false # Better if few cameras (eg less than 4) with risk of limb swapping (eg camera facing sagittal plane), otherwise slightly less accurate and slower
 undistort_points = false # Better if distorted image (parallel lines curvy on the edge or at least one param > 10^-2), but unnecessary (and slightly slower) if distortions are low
 make_c3d = true # save triangulated data in c3d format in addition to trc

Pose2Sim/Pose2Sim.py

@@ -68,7 +68,7 @@ def setup_logging(session_dir):
     '''
     Create logging file and stream handlers
     '''
-    with open(os.path.join(session_dir, 'logs.txt'), 'a+') as log_f: pass
+
     logging.basicConfig(format='%(message)s', level=logging.INFO, 
         handlers = [logging.handlers.TimedRotatingFileHandler(os.path.join(session_dir, 'logs.txt'), when='D', interval=7), logging.StreamHandler()])
 
@@ -220,6 +220,7 @@ def calibration(config=None):
     
     end = time.time()
     logging.info(f'\nCalibration took {end-start:.2f} s.')
+    logging.handlers.close()
 
 
 def poseEstimation(config=None):

Pose2Sim/triangulation.py

@@ -343,6 +343,7 @@ def recap_triangulate(config_dict, error, nb_cams_excluded, keypoints_names, cam
     show_interp_indices = config_dict.get('triangulation').get('show_interp_indices')
     interpolation_kind = config_dict.get('triangulation').get('interpolation')
     interp_gap_smaller_than = config_dict.get('triangulation').get('interp_if_gap_smaller_than')
+    fill_large_gaps_with = config_dict.get('triangulation').get('fill_large_gaps_with')
     make_c3d = config_dict.get('triangulation').get('make_c3d')
     handle_LR_swap = config_dict.get('triangulation').get('handle_LR_swap')
     undistort_points = config_dict.get('triangulation').get('undistort_points')
@@ -383,7 +384,7 @@ def recap_triangulate(config_dict, error, nb_cams_excluded, keypoints_names, cam
         logging.info(f'\n--> Mean reprojection error for all points on all frames is {mean_error_px} px, which roughly corresponds to {mean_error_mm} mm. ')
         logging.info(f'Cameras were excluded if likelihood was below {likelihood_threshold} and if the reprojection error was above {error_threshold_triangulation} px.') 
         if interpolation_kind != 'none':
-            logging.info(f'Gaps were interpolated with {interpolation_kind} method if smaller than {interp_gap_smaller_than} frames.') 
+            logging.info(f'Gaps were interpolated with {interpolation_kind} method if smaller than {interp_gap_smaller_than} frames. Larger gaps were filled with {["the last valid value" if fill_large_gaps_with == "last_value" else "zeros" if fill_large_gaps_with == "zeros" else "NaNs"][0]}.') 
         logging.info(f'In average, {mean_cam_excluded} cameras had to be excluded to reach these thresholds.')
         
         cam_excluded_count[n] = {i: v for i, v in zip(cam_names, cam_excluded_count[n].values())}
@@ -733,6 +734,7 @@ def triangulate_all(config_dict):
     likelihood_threshold = config_dict.get('triangulation').get('likelihood_threshold_triangulation')
     interpolation_kind = config_dict.get('triangulation').get('interpolation')
     interp_gap_smaller_than = config_dict.get('triangulation').get('interp_if_gap_smaller_than')
+    fill_large_gaps_with = config_dict.get('triangulation').get('fill_large_gaps_with')
     show_interp_indices = config_dict.get('triangulation').get('show_interp_indices')
     undistort_points = config_dict.get('triangulation').get('undistort_points')
     make_c3d = config_dict.get('triangulation').get('make_c3d')
@@ -961,9 +963,12 @@ def triangulate_all(config_dict):
             except:
                 logging.info(f'Interpolation was not possible for person {n}. This means that not enough points are available, which is often due to a bad calibration.')
     # Fill non-interpolated values with last valid one
-    for n in range(nb_persons_to_detect): 
+    if fill_large_gaps_with == 'last_value':
-        Q_tot[n] = Q_tot[n].ffill(axis=0).bfill(axis=0)
+        for n in range(nb_persons_to_detect): 
-        # Q_tot[n].replace(np.nan, 0, inplace=True)
+            Q_tot[n] = Q_tot[n].ffill(axis=0).bfill(axis=0)
+    elif fill_large_gaps_with == 'zeros':
+        for n in range(nb_persons_to_detect): 
+            Q_tot[n].replace(np.nan, 0, inplace=True)
     
     # Create TRC file
     trc_paths = [make_trc(config_dict, Q_tot[n], keypoints_names, f_range, id_person=n) for n in range(len(Q_tot))]

setup.cfg

@@ -49,7 +49,7 @@ install_requires =
     tensorflow
     torch
     #rtmlib
-    rtmlib@git+ssh://git@github.com/Tau-J/rtmlib
+    rtmlib@git+https://github.com/Tau-J/rtmlib.git
     onnxruntime
     openvino
     opencv-python