pose2sim/Pose2Sim/Demo/User/Config.toml

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## PROJECT PARAMETERS                                                        ##
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# Configure your project parameters here

[project]
project_dir = '' # BETWEEN SINGLE QUOTES! # If empty, project dir is current dir
frame_range = [] #For example [10,300], or [] for all frames
frame_rate = 60 #Hz

rawImg_folder_name = 'raw'
calib_folder_name = 'calibration'
pose_folder_name = 'pose'
pose_json_folder_extension = 'json'
pose_img_folder_extension = 'img'
poseAssociated_folder_name = 'pose-associated'
pose3d_folder_name = 'pose-3d'
opensim_folder_name = 'opensim'


[pose]
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 Pose2Sim\skeleton.py for their skeleton hierarchy
# What follows has not been implemented yet
pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' 
overwrite_pose = false
openpose_path = '' # only checked if OpenPose is used


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

   [calibration.convert]
   convert_from = 'qualisys' # 'qualisys', 'optitrack', vicon', 'opencap', 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 parameters needed
      [calibration.convert.opencap]    # No parameters needed
      [calibration.convert.biocv]      # No parameters needed
  

   [calibration.calculate] 
   calculate_method = 'board' # 'board' or 'points'
      
      [calibration.calculate.board.intrinsics] # camera properties, only needs to be done once
      intrinsics_board_type = 'checkerboard' # 'checkerboard' ('charucoboard' not supported yet)
      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
      intrinsics_marker_size = 40 # mm # only checked if charucoboard
      intrinsics_aruco_dict = 'DICT_6X6_250' # only checked if charucoboard # see https://docs.opencv.org/3.4/dc/df7/dictionary_8hpp.html
   
      [calibration.calculate.board.extrinsics] # camera placement, needs to be done every time
      extrinsics_board_type = 'scene' # 'checkerboard', 'scene'  ('charucoboard' not supported yet)
      # 'board' should be large enough to be detected when laid on the floor. 
      # 'scene' involves manually clicking any point of know coordinates on scene. Usually more accurate if points are spread out
      moving_camera = false # Not implemented yet
      calculate_extrinsics = true # true or false (lowercase) 
      show_reprojection_error = true # true or false (lowercase)
      extrinsics_extension = 'png' # any video or image extension
      
      # if extrinsics_board_type = 'checkerboard' or 'charucoboard'
      extrinsics_corners_nb = [4,7] # [H,W] rather than [w,h]
      extrinsics_square_size = 60 # mm # [h,w] if square is actually a rectangle
      extrinsics_marker_size = 40 # mm # only checked if 'charucoboard' (not supported yet)
      extrinsics_aruco_dict = 'DICT_6X6_250' # only checked if 'charucoboard' # see https://docs.opencv.org/3.4/dc/df7/dictionary_8hpp.html
      
      # if extrinsics_board_type = 'scene'
      # list of 3D coordinates to be manually labelled on images. Can also be a 2 dimensional plane. # in m
      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]] # in meters -> Not in mm! <-
      
  
      [calibration.calculate.points]
      calibration_points = 'wand' # 'wand' or 'keypoints'
      # Not supported yet.

	  
[personAssociation]
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


[triangulation]
reproj_error_threshold_triangulation = 15 # px
likelihood_threshold = 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


[filtering]
type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed
display_figures = true # 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

[opensim]