pose2sim/Pose2Sim/S00_Demo_Session/S00_P01_MultiParticipants/Config.toml

###############################################################################
## PROJECT PARAMETERS                                                        ##
###############################################################################


# Configure your project parameters here. 
# 
# IMPORTANT:
# If a parameter is not found here, Pose2Sim will look for its value in the 
# Config.toml file of the level above. This way, you can set global 
# instructions for the Session and alter them for specific Participants or Trials.
# 
# If you wish to overwrite a parameter for a specific trial or participant, 
# edit its Config.toml file by uncommenting its key (e.g., [project])
# and editing its value (e.g., frame_range = [10,300]). Or else, uncomment 
# [filtering.butterworth] and set cut_off_frequency = 10, etc.



# [project]
# multi_person = false # true for trials with multiple participants. If false, only the main person in scene is analyzed. 
# frame_rate = 60 # FPS
# frame_range = [] # For example [10,300], or [] for all frames
## N.B.: If you want a time range instead, use frame_range = time_range * frame_rate
## For example if you want to analyze from 0.1 to 2 seconds with a 60 fps frame rate, 
## frame_range = [0.1, 2.0]*frame_rate = [6, 120]

# exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['<participant_dir/trial_dir>', 'etc'].
# e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial']
## Take heart, calibration is not that complicated once you get the hang of it!


# [calibration]
# calibration_type = 'convert' # 'convert' or 'calculate'

   # [calibration.convert]
   # convert_from = 'qualisys' # 'qualisys', 'optitrack', vicon', 'opencap', 'easymocap', or 'biocv'
      # [calibration.convert.qualisys]
      # binning_factor = 1 # Usually 1, except when filming in 540p where it usually is 2
      # [calibration.convert.optitrack]  # See readme for instructions
      # [calibration.convert.vicon]      # No parameter needed
      # [calibration.convert.opencap]    # No parameter needed
      # [calibration.convert.easymocap]  # No parameter needed
      # [calibration.convert.biocv]      # No parameter needed
      # [calibration.convert.anipose]    # No parameter needed
      # [calibration.convert.freemocap]  # No parameter needed
  

   # [calibration.calculate] 
      ## Camera properties, theoretically need to be calculated only once in a camera lifetime
      # [calibration.calculate.intrinsics]
      # overwrite_intrinsics = false # overwrite (or not) if they have already been calculated?
      # show_detection_intrinsics = true # true or false (lowercase)
      # intrinsics_extension = 'jpg' # any video or image extension
      # extract_every_N_sec = 1 # if video, extract frames every N seconds (can be <1 )
      # intrinsics_corners_nb = [4,7] 
      # intrinsics_square_size = 60 # mm

      ## Camera placements, need to be done before every session
      # [calibration.calculate.extrinsics]
      # extrinsics_method = 'scene' # 'board', 'scene', 'keypoints'
      ## 'board' should be large enough to be detected when laid on the floor. Not recommended.
      ## 'scene' involves manually clicking any point of know coordinates on scene. Usually more accurate if points are spread out.
      ## 'keypoints' uses automatic pose estimation of a person freely walking and waving arms in the scene. Slighlty less accurate, requires synchronized cameras.

      # moving_cameras = false # Not implemented yet
      # calculate_extrinsics = true # true or false (lowercase) 

         # [calibration.calculate.extrinsics.board]
         # show_reprojection_error = true # true or false (lowercase)
         # extrinsics_extension = 'png' # any video or image extension
         # extrinsics_corners_nb = [4,7] # [H,W] rather than [w,h]
         # extrinsics_square_size = 60 # mm # [h,w] if square is actually a rectangle

         # [calibration.calculate.extrinsics.scene]
         # show_reprojection_error = true # true or false (lowercase)
         # extrinsics_extension = 'png' # any video or image extension
         ## list of 3D coordinates to be manually labelled on images. Can also be a 2 dimensional plane. 
         ## in m -> unlike for intrinsics, NOT in mm!
         # object_coords_3d =   [[-2.0,  0.3,  0.0], 
         #                      [-2.0 , 0.0,  0.0], 
         #                      [-2.0, 0.0,  0.05], 
         #                      [-2.0, -0.3 ,  0.0], 
         #                      [0.0,  0.3,  0.0], 
         #                      [0.0, 0.0,  0.0], 
         #                      [0.0, 0.0,  0.05], 
         #                      [0.0, -0.3,  0.0]]
        
         # [calibration.calculate.extrinsics.keypoints]
         ## Coming soon!


# [pose]
# pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII,
# 						      #With mediapipe: BLAZEPOSE. 
# 						      #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. 
# 						      #With deeplabcut: CUSTOM. See example at the end of the file.
## What follows has not been implemented yet
# overwrite_pose = false
# openpose_path = '' # only checked if OpenPose is used


# [synchronization]
## COMING SOON! 
# reset_sync = true # Recalculate synchronization even if already done
# frames = [2850,3490] # Frames to use for synchronization, should point to a moment with fast motion.
# cut_off_frequency = 10 # cut-off frequency for a 4th order low-pass Butterworth filter
## Vertical speeds (on X, Y, or Z axis, or 2D speeds)
# speed_kind = 'y' # 'x', 'y', 'z', or '2D'
# vmax = 20 # px/s
# cam1_nb = 4
# cam2_nb = 3
# id_kpt = [9,10] # Pour plus tard aller chercher numéro depuis keypoint name dans skeleton.py. 'RWrist' BLAZEPOSE 16, BODY_25B 10, BODY_25 4 ; 'LWrist' BLAZEPOSE 15, BODY_25B 9, BODY_25 7
# weights_kpt = [1,1] # Pris en compte uniquement si on a plusieurs keypoints


# [personAssociation]
# single_person = true # false for multi-person analysis (not supported yet), true for only triangulating the main person in scene. 
# tracked_keypoint = 'Neck' # If the neck is not detected by the pose_model, check skeleton.py 
## and choose a stable point for tracking the person of interest (e.g., 'right_shoulder' with BLAZEPOSE)
# reproj_error_threshold_association = 20 # px
# likelihood_threshold_association = 0.2


# [triangulation]
# reorder_trc = false # only checked if multi_person analysis
# reproj_error_threshold_triangulation = 15 # px
# likelihood_threshold_triangulation = 0.3
# 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
# 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
# make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon!


# [filtering]
# type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
# display_figures = false # true or false (lowercase)

   # [filtering.butterworth]
   # order = 4 
   # cut_off_frequency = 6 # Hz
   # [filtering.kalman]
   ## How much more do you trust triangulation results (measurements), than previous data (process assuming constant acceleration)?
   # trust_ratio = 100 # = measurement_trust/process_trust ~= process_noise/measurement_noise
   # smooth = true # should be true, unless you need real-time filtering
   # [filtering.butterworth_on_speed]
   # order = 4 
   # cut_off_frequency = 10 # Hz
   # [filtering.gaussian]
   # sigma_kernel = 2 #px
   # [filtering.LOESS]
   # nb_values_used = 30 # = fraction of data used * nb frames
   # [filtering.median]
   # kernel_size = 9


# [markerAugmentation] 
# ## Only works on BODY_25 and BODY_25B models
# participant_height = [1.21, 1.72] # m # float if single person, list of float if multi-person (same order as the Static trials)
# participant_mass = [25.0, 70.0] # kg


# [opensim]
# static_trial = ['S00_P00_Participant/S00_P00_T00_StaticTrial']
#              # If this Config.toml file is at the Trial level, set to true or false (lowercase);
#              # At the Participant level, specify the name of the static trial folder name, e.g. ['S00_P00_T00_StaticTrial'];
#              # At the Session level, add participant subdirectory, e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P01_Participant/S00_P00_T00_StaticTrial']
# opensim_bin_path = 'C:\OpenSim 4.4\bin'


## CUSTOM skeleton, if you trained your own DeepLabCut model for example. 
## Make sure the node ids correspond to the column numbers of the 2D pose file, starting from zero.
## 
## If you want to perform inverse kinematics, you will also need to create an OpenSim model
## and add to its markerset the location where you expect the triangulated keypoints to be detected.
## 
## In this example, CUSTOM reproduces the BODY_25B skeleton  (default skeletons are stored in skeletons.py).
## You can create as many custom skeletons as you want, just add them further down and rename them.
## 
## Check your model hierarchy with:  for pre, _, node in RenderTree(model): 
##                                      print(f'{pre}{node.name} id={node.id}')
# [pose.CUSTOM]
# name = "CHip"
# id = "None"
#   [[pose.CUSTOM.children]]
#   id = 12
#   name = "RHip"
#      [[pose.CUSTOM.children.children]]
#      id = 14
#      name = "RKnee"
#         [[pose.CUSTOM.children.children.children]]
#         id = 16
#         name = "RAnkle"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 22
#            name = "RBigToe"
#               [[pose.CUSTOM.children.children.children.children.children]]
#               id = 23
#               name = "RSmallToe"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 24
#            name = "RHeel"
#   [[pose.CUSTOM.children]]
#   id = 11
#   name = "LHip"
#      [[pose.CUSTOM.children.children]]
#      id = 13
#      name = "LKnee"
#         [[pose.CUSTOM.children.children.children]]
#         id = 15
#         name = "LAnkle"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 19
#            name = "LBigToe"
#               [[pose.CUSTOM.children.children.children.children.children]]
#               id = 20
#               name = "LSmallToe"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 21
#            name = "LHeel"
#   [[pose.CUSTOM.children]]
#   id = 17
#   name = "Neck"
#      [[pose.CUSTOM.children.children]]
#      id = 18
#      name = "Head"
#         [[pose.CUSTOM.children.children.children]]
#         id = 0
#         name = "Nose"
#      [[pose.CUSTOM.children.children]]
#      id = 6
#      name = "RShoulder"
#         [[pose.CUSTOM.children.children.children]]
#         id = 8
#         name = "RElbow"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 10
#            name = "RWrist"
#      [[pose.CUSTOM.children.children]]
#      id = 5
#      name = "LShoulder"
#         [[pose.CUSTOM.children.children.children]]
#         id = 7
#         name = "LElbow"
#            [[pose.CUSTOM.children.children.children.children]]
#            id = 9
#            name = "LWrist"