############################################################################### ## PROJECT PARAMETERS ## ############################################################################### # 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]