diff --git a/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022.osim b/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022.osim new file mode 100644 index 0000000..613b694 --- /dev/null +++ b/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022.osim @@ -0,0 +1,13929 @@ + + + + + + + + + .. + + 0.20000000000000001 0.20000000000000001 0.20000000000000001 + + + + + + + + + + + 0 -9.8066499999999994 0 + + Rajagopal et al. (2016), Lai et al. (2017), Uhlrich et al. (2022) + + Rajagopal, A., Dembia, C.L., DeMers, M.S., Delp, D.D., Hicks, J.L., Delp, S.L. (2016) + Full-body musculoskeletal model for muscle-driven simulation of human gait. IEEE Transactions on Biomedical Engineering. + Lai, A.K.M., Arnold, A.S., Wakeling, J.M. (2017) + Why are antagonist muscles co-activated in my simulation? A musculoskeletal model for analysing human locomotor tasks. Annals of Biomedical Engineering + Uhlrich, S.D., Jackson, R.W., Seth, A., Kolesar, J.A., Delp, S.L. (2022) + Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force. 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addbrev_l addlong_l glmin1_l grac_l iliacus_l psoas_l recfem_l sart_l tfl_l + + + addlong_l addmagDist_l addmagIsch_l addmagMid_l addmagProx_l bflh_l glmax1_l glmax2_l glmax3_l glmed1_l glmed2_l glmed3_l glmin3_l semimem_l semiten_l + + + glmin3_l piri_l + + + glmed1_l glmed2_l glmed3_l glmin1_l iliacus_l psoas_l tfl_l + + + bflh_l bfsh_l gaslat_l gasmed_l grac_l sart_l semimem_l semiten_l + + + recfem_l vasint_l vaslat_l vasmed_l + + + edl_l ehl_l tibant_l + + + fdl_l fhl_l gaslat_l gasmed_l perbrev_l perlong_l soleus_l tibpost_l + + + edl_l perbrev_l perlong_l + + + ehl_l fdl_l fhl_l tibant_l tibpost_l + + + + + + + + + + + + + + + diff --git a/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022_shoulder.osim b/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022_shoulder.osim new file mode 100644 index 0000000..0c6a9bf --- /dev/null +++ b/Pose2Sim/Demo/OpenSim_Setup/LSTM/LaiUhlrich2022_shoulder.osim @@ -0,0 +1,14331 @@ + + + + + + + + + .. + + 0.20000000000000001 0.20000000000000001 0.20000000000000001 + + + + + + + + + + + 0 -9.8066499999999994 0 + + Rajagopal et al. (2016), Lai et al. (2017), Uhlrich et al. (2022) + + Rajagopal, A., Dembia, C.L., DeMers, M.S., Delp, D.D., Hicks, J.L., Delp, S.L. (2016) + Full-body musculoskeletal model for muscle-driven simulation of human gait. IEEE Transactions on Biomedical Engineering. + Lai, A.K.M., Arnold, A.S., Wakeling, J.M. (2017) + Why are antagonist muscles co-activated in my simulation? A musculoskeletal model for analysing human locomotor tasks. Annals of Biomedical Engineering + Uhlrich, S.D., Jackson, R.W., Seth, A., Kolesar, J.A., Delp, S.L. (2022) + Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force. 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frames exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! +## Only taken into account if want to use marker augmentation participant_height = 1.7 # m participant_mass = 70 # kg @@ -94,8 +94,7 @@ calibration_type = 'convert' # 'convert' or 'calculate' [pose] pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +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. diff --git a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/Config.toml b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/Config.toml index ef2d3d5..ce8eef7 100644 --- a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/Config.toml +++ b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/Config.toml @@ -27,7 +27,7 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. diff --git a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T00_StaticTrial/Config.toml b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T00_StaticTrial/Config.toml index 8aef4a7..ce8eef7 100644 --- a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T00_StaticTrial/Config.toml +++ b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T00_StaticTrial/Config.toml @@ -9,8 +9,8 @@ # 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, +# +# 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. @@ -27,7 +27,7 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. diff --git a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T01_BalancingTrial/Config.toml b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T01_BalancingTrial/Config.toml index eb23604..ce8eef7 100644 --- a/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T01_BalancingTrial/Config.toml +++ b/Pose2Sim/Demo/S00_Demo_Session/S00_P00_Participant/S00_P00_T01_BalancingTrial/Config.toml @@ -9,8 +9,8 @@ # 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, +# +# 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. @@ -27,7 +27,7 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -140,9 +139,9 @@ # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon! -[filtering] +# [filtering] # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed -display_figures = true # true or false (lowercase) +# display_figures = true # true or false (lowercase) # [filtering.butterworth] # order = 4 diff --git a/Pose2Sim/Demo/S01_Empty_Session/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/Config.toml index 27a08e7..089a89c 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/Config.toml @@ -27,7 +27,7 @@ frame_range = [] # For example [10,300], or [] for all frames exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! +## Only taken into account if want to use marker augmentation participant_height = 1.7 # m participant_mass = 70 # kg @@ -95,7 +95,6 @@ calibration_type = 'convert' # 'convert' or 'calculate' [pose] pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! #With mediapipe: BLAZEPOSE. #With alphapose: HALPE_26, HALPE_68, HALPE_136, COCO_133. #With deeplabcut: CUSTOM. See example at the end of the file. diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/Config.toml index e99bc70..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/Config.toml @@ -9,7 +9,7 @@ # 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 @@ -27,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -163,7 +162,7 @@ # [opensim] -# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T00_StaticTrial/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T00_StaticTrial/Config.toml index 96077d0..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T00_StaticTrial/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T00_StaticTrial/Config.toml @@ -9,6 +9,7 @@ # 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 @@ -26,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -94,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, -# BODY_25_AUGMENTED # Coming soon! +# 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. @@ -162,7 +162,7 @@ # [opensim] -# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T01_MotionTrial1/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T01_MotionTrial1/Config.toml index d4ff549..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T01_MotionTrial1/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T01_MotionTrial1/Config.toml @@ -9,6 +9,7 @@ # 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 @@ -26,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -94,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -139,9 +139,9 @@ # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon! -[filtering] +# [filtering] # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed -display_figures = true # true or false (lowercase) +# display_figures = true # true or false (lowercase) # [filtering.butterworth] # order = 4 @@ -162,7 +162,7 @@ display_figures = true # true or false (lowercase) # [opensim] -# static_trial = ['S01_P00_Participant/0S01_P00_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T02_MotionTrial2/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T02_MotionTrial2/Config.toml index 3e255e4..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T02_MotionTrial2/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P00_Participant0/S01_P00_T02_MotionTrial2/Config.toml @@ -9,6 +9,7 @@ # 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 @@ -26,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -94,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -139,9 +139,9 @@ # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon! -[filtering] +# [filtering] # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed -display_figures = true # true or false (lowercase) +# display_figures = true # true or false (lowercase) # [filtering.butterworth] # order = 4 @@ -162,7 +162,7 @@ display_figures = true # true or false (lowercase) # [opensim] -# static_trial = ['S01_P00_Participant0/S01_P00_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/Config.toml index e60bd75..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/Config.toml @@ -9,7 +9,7 @@ # 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 @@ -27,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -163,7 +162,7 @@ # [opensim] -# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T00_StaticTrial/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T00_StaticTrial/Config.toml index e60bd75..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T00_StaticTrial/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T00_StaticTrial/Config.toml @@ -9,7 +9,7 @@ # 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 @@ -27,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -163,7 +162,7 @@ # [opensim] -# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T01_MotionTrial1/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T01_MotionTrial1/Config.toml index eded427..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T01_MotionTrial1/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T01_MotionTrial1/Config.toml @@ -9,7 +9,7 @@ # 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 @@ -27,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -140,9 +139,9 @@ # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon! -[filtering] +# [filtering] # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed -display_figures = true # true or false (lowercase) +# display_figures = true # true or false (lowercase) # [filtering.butterworth] # order = 4 @@ -163,7 +162,7 @@ display_figures = true # true or false (lowercase) # [opensim] -# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T02_MotionTrial2/Config.toml b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T02_MotionTrial2/Config.toml index eded427..ce8eef7 100644 --- a/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T02_MotionTrial2/Config.toml +++ b/Pose2Sim/Demo/S01_Empty_Session/S01_P01_Participant1/S01_P01_T02_MotionTrial2/Config.toml @@ -9,7 +9,7 @@ # 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 @@ -27,9 +27,9 @@ # exclude_from_batch = [] # List of trials to be excluded from batch analysis, ['', 'etc']. # e.g. ['S00_P00_Participant/S00_P00_T00_StaticTrial', 'S00_P00_Participant/S00_P00_T01_BalancingTrial'] +## Only taken into account if want to use marker augmentation # participant_height = 1.7 # m # participant_mass = 70 # kg -## Only taken into account if pose_model is 'BODY_25_AUGMENTED' # Coming soon! ## Take heart, calibration is not that complicated once you get the hang of it! @@ -95,8 +95,7 @@ # [pose] # pose_framework = 'openpose' # 'openpose', 'mediapipe', 'alphapose', 'deeplabcut' -# pose_model = 'BODY_25B' #With openpose: BODY_25B, BODY_25, BODY_135, COCO, MPII, - # BODY_25_AUGMENTED # Coming soon! +# 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. @@ -140,9 +139,9 @@ # make_c3d = false # save triangulated data in c3d format in addition to trc # Coming soon! -[filtering] +# [filtering] # type = 'butterworth' # butterworth, kalman, gaussian, LOESS, median, butterworth_on_speed -display_figures = true # true or false (lowercase) +# display_figures = true # true or false (lowercase) # [filtering.butterworth] # order = 4 @@ -163,7 +162,7 @@ display_figures = true # true or false (lowercase) # [opensim] -# static_trial = ['S01_P01_Participant1/S01_P01_T00_StaticTrial'] +# 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'] diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/mean.npy b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/mean.npy new file mode 100644 index 0000000..c945e2c Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/mean.npy differ diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/metadata.json b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/metadata.json new file mode 100644 index 0000000..6d8aa2f --- /dev/null +++ b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/metadata.json @@ -0,0 +1 @@ +{"reference_marker": "midHip"} \ No newline at end of file diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/model.json b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/model.json new file mode 100644 index 0000000..14d244b --- /dev/null +++ b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/model.json @@ -0,0 +1 @@ +{"class_name": "Sequential", "config": {"name": "sequential_2", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, null, 47], "dtype": "float32", "sparse": false, "ragged": false, "name": "lstm_8_input"}}, {"class_name": "LSTM", "config": {"name": "lstm_8", "trainable": true, "dtype": "float32", "batch_input_shape": [null, null, 47], "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_9", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_10", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_11", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "TimeDistributed", "config": {"name": "time_distributed_2", "trainable": true, "dtype": "float32", "layer": {"class_name": "Dense", "config": {"name": "dense_2", "trainable": true, "dtype": "float32", "units": 105, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}}}]}, "keras_version": "2.12.0", "backend": "tensorflow"} \ No newline at end of file diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/std.npy b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/std.npy new file mode 100644 index 0000000..c8ad375 Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/std.npy differ diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/weights.h5 b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/weights.h5 new file mode 100644 index 0000000..9a974dc Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_lower/weights.h5 differ diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/mean.npy b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/mean.npy new file mode 100644 index 0000000..a4ddcbe Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/mean.npy differ diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/metadata.json b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/metadata.json new file mode 100644 index 0000000..6d8aa2f --- /dev/null +++ b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/metadata.json @@ -0,0 +1 @@ +{"reference_marker": "midHip"} \ No newline at end of file diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/model.json b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/model.json new file mode 100644 index 0000000..dd30ad6 --- /dev/null +++ b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/model.json @@ -0,0 +1 @@ +{"class_name": "Sequential", "config": {"name": "sequential", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, null, 23], "dtype": "float32", "sparse": false, "ragged": false, "name": "lstm_input"}}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "batch_input_shape": [null, null, 23], "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_1", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_2", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_3", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "LSTM", "config": {"name": "lstm_4", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "TimeDistributed", "config": {"name": "time_distributed", "trainable": true, "dtype": "float32", "layer": {"class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 24, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}}}]}, "keras_version": "2.12.0", "backend": "tensorflow"} \ No newline at end of file diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/std.npy b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/std.npy new file mode 100644 index 0000000..39897c5 Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/std.npy differ diff --git a/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/weights.h5 b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/weights.h5 new file mode 100644 index 0000000..20d507f Binary files /dev/null and b/Pose2Sim/MarkerAugmenter/LSTM/v0.3_upper/weights.h5 differ diff --git a/Pose2Sim/Pose2Sim.py b/Pose2Sim/Pose2Sim.py index 438677e..0581d41 100644 --- a/Pose2Sim/Pose2Sim.py +++ b/Pose2Sim/Pose2Sim.py @@ -371,12 +371,12 @@ def triangulation(config=None): logging.info(f"Triangulation of 2D points for {seq_name}, for {frames}.") logging.info("---------------------------------------------------------------------") logging.info(f"\nProject directory: {project_dir}") - + triangulate_all(config_dict) end = time.time() logging.info(f'Triangulation took {end-start:.2f} s.') - + def filtering(config=None): ''' @@ -420,6 +420,37 @@ def filtering(config=None): filter_all(config_dict) +def augmenter(config=None): + from Pose2Sim.augmenter import augmentTRC + level, config_dicts = read_config_files(config) + + if type(config) == dict: + config_dict = config_dicts[0] + if config_dict.get('project').get('project_dir') is None: + raise ValueError('Please specify the project directory in config_dict:\n \ + config_dict.get("project").update({"project_dir":""})') + + session_dir = os.path.realpath(os.path.join(config_dicts[0].get('project').get('project_dir'), '..', '..')) + setup_logging(session_dir) + + for config_dict in config_dicts: + start = time.time() + project_dir = os.path.realpath(config_dict.get('project').get('project_dir')) + seq_name = os.path.basename(project_dir) + frame_range = config_dict.get('project').get('frame_range') + frames = ["all frames" if frame_range == [] else f"frames {frame_range[0]} to {frame_range[1]}"][0] + + logging.info("\n\n---------------------------------------------------------------------") + logging.info(f"Augmentation process for {seq_name}, for {frames}.") + logging.info("---------------------------------------------------------------------") + logging.info(f"\nProject directory: {project_dir}") + + augmentTRC(config_dict) + + end = time.time() + logging.info(f'Augmentation took {end - start:.2f} s.') + + def opensimProcessing(config=None): ''' @@ -469,4 +500,4 @@ def opensimProcessing(config=None): # end = time.time() # logging.info(f'Model scaling took {end-start:.2f} s.') - \ No newline at end of file + diff --git a/Pose2Sim/augmenter.py b/Pose2Sim/augmenter.py new file mode 100644 index 0000000..7b83e8b --- /dev/null +++ b/Pose2Sim/augmenter.py @@ -0,0 +1,213 @@ +import os +import numpy as np +from . import utilsDataman +import copy +import tensorflow as tf +from .utils import TRC2numpy +import json +import os +import glob + + +# subject_height must be in meters +def get_midhip_data(trc_file): + try: + # Find MidHip data + midhip_data = trc_file.marker("CHip") + if midhip_data is None or len(midhip_data) == 0: + raise ValueError("MidHip data is empty") + except (KeyError, ValueError): + # If MidHip data is not found, calculate it from RHip and LHip + rhip_data = trc_file.marker("RHip") + lhip_data = trc_file.marker("LHip") + midhip_data = (rhip_data + lhip_data) / 2 + + return midhip_data + + +def augmentTRC(config_dict): + + # get parameters from Config.toml + project_dir = config_dict.get('project').get('project_dir') + session_dir = os.path.realpath(os.path.join(project_dir, '..', '..')) + pathInputTRCFile = os.path.realpath(os.path.join(project_dir, 'pose-3d')) + pathOutputTRCFile = os.path.realpath(os.path.join(project_dir, 'pose-3d')) + subject_height = config_dict.get('project').get('participant_height') + if subject_height is None or subject_height == 0: + raise ValueError("Subject height is not set or invalid in the config file.") + subject_mass = config_dict.get('project').get('participant_mass') + augmenterDir = os.path.join(session_dir, '..', '..', 'MarkerAugmenter') + augmenterModelName = 'LSTM' + augmenter_model = 'v0.3' + offset = True + + # Apply all trc files + trc_files = [f for f in glob.glob(os.path.join(pathInputTRCFile, '*.trc')) if '_LSTM' not in f] + for pathInputTRCFile in trc_files: + pathOutputTRCFile = os.path.splitext(pathInputTRCFile)[0] + "_LSTM.trc" + + # This is by default - might need to be adjusted in the future. + featureHeight = True + featureWeight = True + + # Augmenter types + if augmenter_model == 'v0.0': + from .utils import getOpenPoseMarkers_fullBody + feature_markers_full, response_markers_full = getOpenPoseMarkers_fullBody() + augmenterModelType_all = [augmenter_model] + feature_markers_all = [feature_markers_full] + response_markers_all = [response_markers_full] + elif augmenter_model == 'v0.1' or augmenter_model == 'v0.2': + # Lower body + augmenterModelType_lower = '{}_lower'.format(augmenter_model) + from .utils import getOpenPoseMarkers_lowerExtremity + feature_markers_lower, response_markers_lower = getOpenPoseMarkers_lowerExtremity() + # Upper body + augmenterModelType_upper = '{}_upper'.format(augmenter_model) + from .utils import getMarkers_upperExtremity_noPelvis + feature_markers_upper, response_markers_upper = getMarkers_upperExtremity_noPelvis() + augmenterModelType_all = [augmenterModelType_lower, augmenterModelType_upper] + feature_markers_all = [feature_markers_lower, feature_markers_upper] + response_markers_all = [response_markers_lower, response_markers_upper] + else: + # Lower body + augmenterModelType_lower = '{}_lower'.format(augmenter_model) + from .utils import getOpenPoseMarkers_lowerExtremity2 + feature_markers_lower, response_markers_lower = getOpenPoseMarkers_lowerExtremity2() + # Upper body + augmenterModelType_upper = '{}_upper'.format(augmenter_model) + from .utils import getMarkers_upperExtremity_noPelvis2 + feature_markers_upper, response_markers_upper = getMarkers_upperExtremity_noPelvis2() + augmenterModelType_all = [augmenterModelType_lower, augmenterModelType_upper] + feature_markers_all = [feature_markers_lower, feature_markers_upper] + response_markers_all = [response_markers_lower, response_markers_upper] + print('Using augmenter model: {}'.format(augmenter_model)) + + # %% Process data. + # Import TRC file + trc_file = utilsDataman.TRCFile(pathInputTRCFile) + + # Loop over augmenter types to handle separate augmenters for lower and + # upper bodies. + outputs_all = {} + n_response_markers_all = 0 + for idx_augm, augmenterModelType in enumerate(augmenterModelType_all): + outputs_all[idx_augm] = {} + feature_markers = feature_markers_all[idx_augm] + response_markers = response_markers_all[idx_augm] + + augmenterModelDir = os.path.join(augmenterDir, augmenterModelName, + augmenterModelType) + + # %% Pre-process inputs. + # Step 1: import .trc file with OpenPose marker trajectories. + trc_data = TRC2numpy(pathInputTRCFile, feature_markers) + + # # Add these lines to get RHip and LHip data and calculate midHip + # rhip_data = trc_file.marker("RHip") # Replace "RHip" with the actual name in your trc file + # lhip_data = trc_file.marker("LHip") # Replace "LHip" with the actual name in your trc file + + # Calculate the midHip marker as the average of RHip and LHip + midhip_data = get_midhip_data(trc_file) + + trc_data_data = trc_data[:,1:] + + # Step 2: Normalize with reference marker position. + with open(os.path.join(augmenterModelDir, "metadata.json"), 'r') as f: + metadata = json.load(f) + + # Use midhip_data as the reference marker data + referenceMarker_data = midhip_data # instead of trc_file.marker(referenceMarker) + + norm_trc_data_data = np.zeros((trc_data_data.shape[0], + trc_data_data.shape[1])) + for i in range(0,trc_data_data.shape[1],3): + norm_trc_data_data[:,i:i+3] = (trc_data_data[:,i:i+3] - + referenceMarker_data) + + + # Step 3: Normalize with subject's height. + norm2_trc_data_data = copy.deepcopy(norm_trc_data_data) + norm2_trc_data_data = norm2_trc_data_data / subject_height + + # Step 4: Add remaining features. + inputs = copy.deepcopy(norm2_trc_data_data) + if featureHeight: + inputs = np.concatenate( + (inputs, subject_height*np.ones((inputs.shape[0],1))), axis=1) + if featureWeight: + inputs = np.concatenate( + (inputs, subject_mass*np.ones((inputs.shape[0],1))), axis=1) + + # Step 5: Pre-process data + pathMean = os.path.join(augmenterModelDir, "mean.npy") + pathSTD = os.path.join(augmenterModelDir, "std.npy") + if os.path.isfile(pathMean): + trainFeatures_mean = np.load(pathMean, allow_pickle=True) + inputs -= trainFeatures_mean + if os.path.isfile(pathSTD): + trainFeatures_std = np.load(pathSTD, allow_pickle=True) + inputs /= trainFeatures_std + + # Step 6: Reshape inputs if necessary (eg, LSTM) + if augmenterModelName == "LSTM": + inputs = np.reshape(inputs, (1, inputs.shape[0], inputs.shape[1])) + + # %% Load model and weights, and predict outputs. + json_file = open(os.path.join(augmenterModelDir, "model.json"), 'r') + pretrainedModel_json = json_file.read() + json_file.close() + model = tf.keras.models.model_from_json(pretrainedModel_json) + model.load_weights(os.path.join(augmenterModelDir, "weights.h5")) + outputs = model.predict(inputs) + + # %% Post-process outputs. + # Step 1: Reshape if necessary (eg, LSTM) + if augmenterModelName == "LSTM": + outputs = np.reshape(outputs, (outputs.shape[1], outputs.shape[2])) + + # Step 2: Un-normalize with subject's height. + unnorm_outputs = outputs * subject_height + + # Step 2: Un-normalize with reference marker position. + unnorm2_outputs = np.zeros((unnorm_outputs.shape[0], + unnorm_outputs.shape[1])) + for i in range(0,unnorm_outputs.shape[1],3): + unnorm2_outputs[:,i:i+3] = (unnorm_outputs[:,i:i+3] + + referenceMarker_data) + + # %% Add markers to .trc file. + for c, marker in enumerate(response_markers): + x = unnorm2_outputs[:,c*3] + y = unnorm2_outputs[:,c*3+1] + z = unnorm2_outputs[:,c*3+2] + trc_file.add_marker(marker, x, y, z) + + # %% Gather data for computing minimum y-position. + outputs_all[idx_augm]['response_markers'] = response_markers + outputs_all[idx_augm]['response_data'] = unnorm2_outputs + n_response_markers_all += len(response_markers) + + # %% Extract minimum y-position across response markers. This is used + # to align feet and floor when visualizing. + responses_all_conc = np.zeros((unnorm2_outputs.shape[0], + n_response_markers_all*3)) + idx_acc_res = 0 + for idx_augm in outputs_all: + idx_acc_res_end = (idx_acc_res + + (len(outputs_all[idx_augm]['response_markers']))*3) + responses_all_conc[:,idx_acc_res:idx_acc_res_end] = ( + outputs_all[idx_augm]['response_data']) + idx_acc_res = idx_acc_res_end + # Minimum y-position across response markers. + min_y_pos = np.min(responses_all_conc[:,1::3]) + + # %% If offset + if offset: + trc_file.offset('y', -(min_y_pos-0.01)) + + # %% Return augmented .trc file + trc_file.write(pathOutputTRCFile) + + return min_y_pos + diff --git a/Pose2Sim/filtering.py b/Pose2Sim/filtering.py index 1917e20..7dd6a2e 100644 --- a/Pose2Sim/filtering.py +++ b/Pose2Sim/filtering.py @@ -464,9 +464,17 @@ def filter_all(config): # Trc paths trc_f_in = f'{seq_name}_{f_range[0]}-{f_range[1]}.trc' + trc_f_in_LSTM = f'{seq_name}_{f_range[0]}-{f_range[1]}_LSTM.trc' trc_f_out = f'{seq_name}_filt_{filter_type}_{f_range[0]}-{f_range[1]}.trc' - trc_path_in = os.path.join(pose3d_dir, trc_f_in) - trc_path_out = os.path.join(pose3d_dir, trc_f_out) + trc_f_out_LSTM = f'{seq_name}_filt_{filter_type}_{f_range[0]}-{f_range[1]}_LSTM.trc' + if os.path.exists(os.path.join(pose3d_dir, trc_f_in_LSTM)): + trc_path_in = os.path.join(pose3d_dir, trc_f_in_LSTM) + trc_path_out = os.path.join(pose3d_dir, trc_f_out_LSTM) + elif os.path.exists(os.path.join(pose3d_dir, trc_f_in)): + trc_path_in = os.path.join(pose3d_dir, trc_f_in) + trc_path_out = os.path.join(pose3d_dir, trc_f_out) + else: + raise FileNotFoundError("Not found .trc file.") # Read trc header with open(trc_path_in, 'r') as trc_file: diff --git a/Pose2Sim/skeletons.py b/Pose2Sim/skeletons.py index 6ec0244..233fa4f 100644 --- a/Pose2Sim/skeletons.py +++ b/Pose2Sim/skeletons.py @@ -116,7 +116,6 @@ BODY_25 = Node("CHip", id=8, children=[ ]), ]) - '''BODY_135 (full-body with hands and face, experimental, from OpenPose) https://github.com/CMU-Perceptual-Computing-Lab/openpose_train/blob/master/experimental_models/README.md)''' BODY_135 = Node("CHip", id=None, children=[ diff --git a/Pose2Sim/utils.py b/Pose2Sim/utils.py new file mode 100644 index 0000000..d91cbd0 --- /dev/null +++ b/Pose2Sim/utils.py @@ -0,0 +1,190 @@ +from . import utilsDataman +import numpy as np + +def TRC2numpy(pathFile, markers,rotation=None): + # rotation is a dict, eg. {'y':90} with axis, angle for rotation + + trc_file = utilsDataman.TRCFile(pathFile) + time = trc_file.time + num_frames = time.shape[0] + data = np.zeros((num_frames, len(markers)*3)) + + if rotation != None: + for axis,angle in rotation.items(): + trc_file.rotate(axis,angle) + for count, marker in enumerate(markers): + data[:,3*count:3*count+3] = trc_file.marker(marker) + this_dat = np.empty((num_frames, 1)) + this_dat[:, 0] = time + data_out = np.concatenate((this_dat, data), axis=1) + + return data_out + +def numpy2TRC(f, data, headers, fc=50.0, t_start=0.0, units="m"): + + header_mapping = {} + for count, header in enumerate(headers): + header_mapping[count+1] = header + + # Line 1. + f.write('PathFileType 4\t(X/Y/Z) %s\n' % os.getcwd()) + + # Line 2. + f.write('DataRate\tCameraRate\tNumFrames\tNumMarkers\t' + 'Units\tOrigDataRate\tOrigDataStartFrame\tOrigNumFrames\n') + + num_frames=data.shape[0] + num_markers=len(header_mapping.keys()) + + # Line 3. + f.write('%.1f\t%.1f\t%i\t%i\t%s\t%.1f\t%i\t%i\n' % ( + fc, fc, num_frames, + num_markers, units, fc, + 1, num_frames)) + + # Line 4. + f.write("Frame#\tTime\t") + for key in sorted(header_mapping.keys()): + f.write("%s\t\t\t" % format(header_mapping[key])) + + # Line 5. + f.write("\n\t\t") + for imark in np.arange(num_markers) + 1: + f.write('X%i\tY%s\tZ%s\t' % (imark, imark, imark)) + f.write('\n') + + # Line 6. + f.write('\n') + + for frame in range(data.shape[0]): + f.write("{}\t{:.8f}\t".format(frame+1,(frame)/fc+t_start)) # opensim frame labeling is 1 indexed + + for key in sorted(header_mapping.keys()): + f.write("{:.5f}\t{:.5f}\t{:.5f}\t".format(data[frame,0+(key-1)*3], data[frame,1+(key-1)*3], data[frame,2+(key-1)*3])) + f.write("\n") + +def getOpenPoseMarkerNames(): + + markerNames = ["Nose", "Neck", "RShoulder", "RElbow", "RWrist", + "LShoulder", "LElbow", "LWrist", "midHip", "RHip", + "RKnee", "RAnkle", "LHip", "LKnee", "LAnkle", "REye", + "LEye", "REar", "LEar", "LBigToe", "LSmallToe", + "LHeel", "RBigToe", "RSmallToe", "RHeel"] + + return markerNames + +def getOpenPoseFaceMarkers(): + + faceMarkerNames = ['Nose', 'REye', 'LEye', 'REar', 'LEar'] + markerNames = getOpenPoseMarkerNames() + idxFaceMarkers = [markerNames.index(i) for i in faceMarkerNames] + + return faceMarkerNames, idxFaceMarkers + +def getOpenPoseMarkers_fullBody(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee", + "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe", + "RBigToe", "LBigToe", "RElbow", "LElbow", "RWrist", "LWrist"] + + response_markers = ["C7_study", "r_shoulder_study", "L_shoulder_study", + "r.ASIS_study", "L.ASIS_study", "r.PSIS_study", + "L.PSIS_study", "r_knee_study", "L_knee_study", + "r_mknee_study", "L_mknee_study", "r_ankle_study", + "L_ankle_study", "r_mankle_study", "L_mankle_study", + "r_calc_study", "L_calc_study", "r_toe_study", + "L_toe_study", "r_5meta_study", "L_5meta_study", + "r_lelbow_study", "L_lelbow_study", "r_melbow_study", + "L_melbow_study", "r_lwrist_study", "L_lwrist_study", + "r_mwrist_study", "L_mwrist_study", + "r_thigh1_study", "r_thigh2_study", "r_thigh3_study", + "L_thigh1_study", "L_thigh2_study", "L_thigh3_study", + "r_sh1_study", "r_sh2_study", "r_sh3_study", + "L_sh1_study", "L_sh2_study", "L_sh3_study", + "RHJC_study", "LHJC_study"] + + return feature_markers, response_markers + +def getOpenPoseMarkers_lowerExtremity(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee", + "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe", + "RBigToe", "LBigToe"] + + response_markers = ["C7_study", "r_shoulder_study", "L_shoulder_study", + "r.ASIS_study", "L.ASIS_study", "r.PSIS_study", + "L.PSIS_study", "r_knee_study", "L_knee_study", + "r_mknee_study", "L_mknee_study", "r_ankle_study", + "L_ankle_study", "r_mankle_study", "L_mankle_study", + "r_calc_study", "L_calc_study", "r_toe_study", + "L_toe_study", "r_5meta_study", "L_5meta_study", + "r_thigh1_study", "r_thigh2_study", "r_thigh3_study", + "L_thigh1_study", "L_thigh2_study", "L_thigh3_study", + "r_sh1_study", "r_sh2_study", "r_sh3_study", + "L_sh1_study", "L_sh2_study", "L_sh3_study", + "RHJC_study", "LHJC_study"] + + return feature_markers, response_markers + +# Different order of markers compared to getOpenPoseMarkers_lowerExtremity +def getOpenPoseMarkers_lowerExtremity2(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RKnee", "LKnee", + "RAnkle", "LAnkle", "RHeel", "LHeel", "RSmallToe", "LSmallToe", + "RBigToe", "LBigToe"] + + response_markers = [ + 'r.ASIS_study', 'L.ASIS_study', 'r.PSIS_study', + 'L.PSIS_study', 'r_knee_study', 'r_mknee_study', + 'r_ankle_study', 'r_mankle_study', 'r_toe_study', + 'r_5meta_study', 'r_calc_study', 'L_knee_study', + 'L_mknee_study', 'L_ankle_study', 'L_mankle_study', + 'L_toe_study', 'L_calc_study', 'L_5meta_study', + 'r_shoulder_study', 'L_shoulder_study', 'C7_study', + 'r_thigh1_study', 'r_thigh2_study', 'r_thigh3_study', + 'L_thigh1_study', 'L_thigh2_study', 'L_thigh3_study', + 'r_sh1_study', 'r_sh2_study', 'r_sh3_study', 'L_sh1_study', + 'L_sh2_study', 'L_sh3_study', 'RHJC_study', 'LHJC_study'] + + return feature_markers, response_markers + + +def getMarkers_upperExtremity_pelvis(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RHip", "LHip", "RElbow", "LElbow", + "RWrist", "LWrist"] + + response_markers = ["r_lelbow_study", "L_lelbow_study", "r_melbow_study", + "L_melbow_study", "r_lwrist_study", "L_lwrist_study", + "r_mwrist_study", "L_mwrist_study"] + + return feature_markers, response_markers + +def getMarkers_upperExtremity_noPelvis(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RElbow", "LElbow", "RWrist", + "LWrist"] + + response_markers = ["r_lelbow_study", "L_lelbow_study", "r_melbow_study", + "L_melbow_study", "r_lwrist_study", "L_lwrist_study", + "r_mwrist_study", "L_mwrist_study"] + + return feature_markers, response_markers + +# Different order of markers compared to getMarkers_upperExtremity_noPelvis. +def getMarkers_upperExtremity_noPelvis2(): + + feature_markers = [ + "Neck", "RShoulder", "LShoulder", "RElbow", "LElbow", "RWrist", + "LWrist"] + + response_markers = ["r_lelbow_study", "r_melbow_study", "r_lwrist_study", + "r_mwrist_study", "L_lelbow_study", "L_melbow_study", + "L_lwrist_study", "L_mwrist_study"] + + return feature_markers, response_markers diff --git a/Pose2Sim/utilsDataman.py b/Pose2Sim/utilsDataman.py new file mode 100644 index 0000000..6b5f0fe --- /dev/null +++ b/Pose2Sim/utilsDataman.py @@ -0,0 +1,282 @@ +"""Manages the movement and use of data files.""" + +import os +import warnings +from scipy.spatial.transform import Rotation as R + +import numpy as np +from numpy.lib.recfunctions import append_fields + +class TRCFile(object): + """A plain-text file format for storing motion capture marker trajectories. + TRC stands for Track Row Column. + + The metadata for the file is stored in attributes of this object. + + See + http://simtk-confluence.stanford.edu:8080/display/OpenSim/Marker+(.trc)+Files + for more information. + + """ + def __init__(self, fpath=None, **kwargs): + #path=None, + #data_rate=None, + #camera_rate=None, + #num_frames=None, + #num_markers=None, + #units=None, + #orig_data_rate=None, + #orig_data_start_frame=None, + #orig_num_frames=None, + #marker_names=None, + #time=None, + #): + """ + Parameters + ---------- + fpath : str + Valid file path to a TRC (.trc) file. + + """ + self.marker_names = [] + if fpath != None: + self.read_from_file(fpath) + else: + for k, v in kwargs.items(): + setattr(self, k, v) + + def read_from_file(self, fpath): + # Read the header lines / metadata. + # --------------------------------- + # Split by any whitespace. + # TODO may cause issues with paths that have spaces in them. + f = open(fpath) + # These are lists of each entry on the first few lines. + first_line = f.readline().split() + # Skip the 2nd line. + f.readline() + third_line = f.readline().split() + fourth_line = f.readline().split() + f.close() + + # First line. + if len(first_line) > 3: + self.path = first_line[3] + else: + self.path = '' + + # Third line. + self.data_rate = float(third_line[0]) + self.camera_rate = float(third_line[1]) + self.num_frames = int(third_line[2]) + self.num_markers = int(third_line[3]) + self.units = third_line[4] + self.orig_data_rate = float(third_line[5]) + self.orig_data_start_frame = int(third_line[6]) + self.orig_num_frames = int(third_line[7]) + + # Marker names. + # The first and second column names are 'Frame#' and 'Time'. + self.marker_names = fourth_line[2:] + + len_marker_names = len(self.marker_names) + if len_marker_names != self.num_markers: + warnings.warn('Header entry NumMarkers, %i, does not ' + 'match actual number of markers, %i. Changing ' + 'NumMarkers to match actual number.' % ( + self.num_markers, len_marker_names)) + self.num_markers = len_marker_names + + # Load the actual data. + # --------------------- + col_names = ['frame_num', 'time'] + # This naming convention comes from OpenSim's Inverse Kinematics tool, + # when it writes model marker locations. + for mark in self.marker_names: + col_names += [mark + '_tx', mark + '_ty', mark + '_tz'] + dtype = {'names': col_names, + 'formats': ['int'] + ['float64'] * (3 * self.num_markers + 1)} + usecols = [i for i in range(3 * self.num_markers + 1 + 1)] + self.data = np.loadtxt(fpath, delimiter='\t', skiprows=5, dtype=dtype, + usecols=usecols) + self.time = self.data['time'] + + # Check the number of rows. + n_rows = self.time.shape[0] + if n_rows != self.num_frames: + warnings.warn('%s: Header entry NumFrames, %i, does not ' + 'match actual number of frames, %i, Changing ' + 'NumFrames to match actual number.' % (fpath, + self.num_frames, n_rows)) + self.num_frames = n_rows + + def __getitem__(self, key): + """See `marker()`. + + """ + return self.marker(key) + + def units(self): + return self.units + + def time(self): + this_dat = np.empty((self.num_frames, 1)) + this_dat[:, 0] = self.time + return this_dat + + def marker(self, name): + """The trajectory of marker `name`, given as a `self.num_frames` x 3 + array. The order of the columns is x, y, z. + + """ + this_dat = np.empty((self.num_frames, 3)) + this_dat[:, 0] = self.data[name + '_tx'] + this_dat[:, 1] = self.data[name + '_ty'] + this_dat[:, 2] = self.data[name + '_tz'] + return this_dat + + def add_marker(self, name, x, y, z): + """Add a marker, with name `name` to the TRCFile. + + Parameters + ---------- + name : str + Name of the marker; e.g., 'R.Hip'. + x, y, z: array_like + Coordinates of the marker trajectory. All 3 must have the same + length. + + """ + if (len(x) != self.num_frames or len(y) != self.num_frames or len(z) != + self.num_frames): + raise Exception('Length of data (%i, %i, %i) is not ' + 'NumFrames (%i).', len(x), len(y), len(z), self.num_frames) + self.marker_names += [name] + self.num_markers += 1 + if not hasattr(self, 'data'): + self.data = np.array(x, dtype=[('%s_tx' % name, 'float64')]) + self.data = append_fields(self.data, + ['%s_t%s' % (name, s) for s in 'yz'], + [y, z], usemask=False) + else: + self.data = append_fields(self.data, + ['%s_t%s' % (name, s) for s in 'xyz'], + [x, y, z], usemask=False) + + def marker_at(self, name, time): + x = np.interp(time, self.time, self.data[name + '_tx']) + y = np.interp(time, self.time, self.data[name + '_ty']) + z = np.interp(time, self.time, self.data[name + '_tz']) + return [x, y, z] + + def marker_exists(self, name): + """ + Returns + ------- + exists : bool + Is the marker in the TRCFile? + + """ + return name in self.marker_names + + def write(self, fpath): + """Write this TRCFile object to a TRC file. + + Parameters + ---------- + fpath : str + Valid file path to which this TRCFile is saved. + + """ + f = open(fpath, 'w') + + # Line 1. + f.write('PathFileType 4\t(X/Y/Z) %s\n' % os.path.split(fpath)[0]) + + # Line 2. + f.write('DataRate\tCameraRate\tNumFrames\tNumMarkers\t' + 'Units\tOrigDataRate\tOrigDataStartFrame\tOrigNumFrames\n') + + # Line 3. + f.write('%.1f\t%.1f\t%i\t%i\t%s\t%.1f\t%i\t%i\n' % ( + self.data_rate, self.camera_rate, self.num_frames, + self.num_markers, self.units, self.orig_data_rate, + self.orig_data_start_frame, self.orig_num_frames)) + + # Line 4. + f.write('Frame#\tTime\t') + for imark in range(self.num_markers): + f.write('%s\t\t\t' % self.marker_names[imark]) + f.write('\n') + + # Line 5. + f.write('\t\t') + for imark in np.arange(self.num_markers) + 1: + f.write('X%i\tY%s\tZ%s\t' % (imark, imark, imark)) + f.write('\n') + + # Line 6. + f.write('\n') + + # Data. + for iframe in range(self.num_frames): + f.write('%i' % (iframe + 1)) + f.write('\t%.7f' % self.time[iframe]) + for mark in self.marker_names: + idxs = [mark + '_tx', mark + '_ty', mark + '_tz'] + f.write('\t%.7f\t%.7f\t%.7f' % tuple( + self.data[coln][iframe] for coln in idxs)) + f.write('\n') + + f.close() + + def add_noise(self, noise_width): + """ add random noise to each component of the marker trajectory + The noise mean will be zero, with the noise_width being the + standard deviation. + + noise_width : int + """ + for imarker in range(self.num_markers): + components = ['_tx', '_ty', '_tz'] + for iComponent in range(3): + # generate noise + noise = np.random.normal(0, noise_width, self.num_frames) + # add noise to each component of marker data. + self.data[self.marker_names[imarker] + components[iComponent]] += noise + + def rotate(self, axis, value): + """ rotate the data. + + axis : rotation axis + value : angle in degree + """ + for imarker in range(self.num_markers): + + temp = np.zeros((self.num_frames, 3)) + temp[:,0] = self.data[self.marker_names[imarker] + '_tx'] + temp[:,1] = self.data[self.marker_names[imarker] + '_ty'] + temp[:,2] = self.data[self.marker_names[imarker] + '_tz'] + + r = R.from_euler(axis, value, degrees=True) + temp_rot = r.apply(temp) + + self.data[self.marker_names[imarker] + '_tx'] = temp_rot[:,0] + self.data[self.marker_names[imarker] + '_ty'] = temp_rot[:,1] + self.data[self.marker_names[imarker] + '_tz'] = temp_rot[:,2] + + def offset(self, axis, value): + """ offset the data. + + axis : rotation axis + value : offset in m + """ + for imarker in range(self.num_markers): + if axis.lower() == 'x': + self.data[self.marker_names[imarker] + '_tx'] += value + elif axis.lower() == 'y': + self.data[self.marker_names[imarker] + '_ty'] += value + elif axis.lower() == 'z': + self.data[self.marker_names[imarker] + '_tz'] += value + else: + raise ValueError("Axis not recognized") diff --git a/README.md b/README.md index 38ecb3a..dc691ff 100644 --- a/README.md +++ b/README.md @@ -415,6 +415,22 @@ Output:\
+### Marker Augmentation (Test) +Set parameters(height, mass) in [project] of Config.toml + +Open a terminal, enter `pip show pose2sim`, report package location. \ +Copy this path and go to the Demo folder with `cd \pose2sim\Demo\S00_Demo_Session`. \ +Type `ipython`, If you want to triangulate and marker augment without filtering, test the following code: +``` python +from Pose2Sim import Pose2Sim +Pose2Sim.augmenter() +``` +Recommand you augment markers after filtering.\ +The .trc file should be located in pose-3d folder.\ +If you enter inexact height, model'll be unstable.\ +If there is a Nan value in the .trc file, it will not work properly.\ +Should input Marker_add.xml in OpenSim when you scale your model. + ## OpenSim kinematics > _**Obtain 3D joint angles.**_\ > Your OpenSim .osim scaled model and .mot inverse kinematic results will be found in the OpenSim folder of your `Participant` directory.