updated accompanying tools

LICENSE

@@ -0,0 +1,400 @@
+
+Attribution-NonCommercial 4.0 International
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+=======================================================================
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+Creative Commons may be contacted at creativecommons.org.

data/participants_metadata.csv

@@ -0,0 +1,289 @@
+# All names are fake. They are not related to participants. They cannot be used to infer gender. 
+date,session_id,name,underlayer_size,xsens_suit_size,height_cm,foot_length_cm,shoulder_height_cm,shoulder_width_cm,elbow_span_cm,wrist_span_cm,arm_span_cm,hip_height_cm,hip_widtd_cm,knee_height_cm,ankle_height_cm,extra_shoe_thickness_cm,gender,ethnicity,bmi,weight_kg,weight_bucket,age_group,note
+20230601,s0,paul_weaver,S,M,160,26,129,39,78,128,161,88,32,42,10,5,Female,caucasian,18.8,48,45-50,36-40,
+20230601,s1,jennifer_kennedy,L,L,158,27,130,38,74,124,163,85,35,42,9,4,Female,south asian,23.6,59,50-60,41-45,
+20230602,s0,gregory_herman,M,L,154,26,126,38,73,125,157,86,33,48,10,5,Female,south asian,23.6,56,60-70,41-45,
+20230602,s1,timothy_english,L,XL,165,26,137,38,81,129,163,91,29,48,10,4,Female,caucasian,22.4,61,60-70,36-40,
+20230605,s0,amber_cruz,XL,XXL,196,31,165,43,94,156,198,111,29,61,10,5,Male,caucasian,23.7,91,90-100,41-45,
+20230605,s1,kayla_dillon,XL,XXL,168,26,140,33,84,130,171,88,33,49,10,3,Male,african american,28,79,70-80,36-40,
+20230606,s0,marcus_jordan,L,XL,181,31,148,44,84,137,178,103,34,56,11,3,Male,caucasian,25,82,80-90,18-24,
+20230606,s1,taylor_walton,M,L,170,29,139,34,88,138,178,93,34,53,11,4,Male,east asian,24.9,72,70-80,36-40,
+20230607,s0,james_johnson,S,M,158,25,129,34,69,106,152,87,31,45,9,1,Female,east asian,20.1,49,45-50,25-30,
+20230607,s1,barbara_wheeler,XL,XXL,195,34,158,36,102,154,194,100,36,56,10,3,Male,african american,25.2,96,90-100,18-24,
+20230608,s0,shelby_arroyo,S,XL,153,24,129,34,74,121,147,89,32,43,9,1,Female,caucasian,19.2,45,45-50,46-50,
+20230608,s1,donna_gonzales,M,L,166,25,139,39,84,134,170,101,34,46,13,3,Female,south asian,18.5,49,45-50,18-24,
+20230609,s0,angela_harrell,L,XL,162,28,137,41,84,132,169,95,33,53,15,4,Female,african american,21,55,50-60,31-35,
+20230609,s1,heather_becker,L,XL,178,30,148,38,90,144,184,94,33,55,10,3,Male,south asian,24,76,70-80,25-30,
+20230612,s0,jason_smith,L,XL,186,31,159,34,86,139,179,106,30,59,10,3,Male,caucasian,26.1,81,80-90,31-35,
+20230612,s1,christina_jones,L,XXL,169,27,142,35,85,135,175,95,34,54,11,5,Male,south asian,27.7,79,70-80,46-50,
+20230613,s0,virginia_rivera,L,XL,166,27,138,43,91,144,183,93,36,49,12,1,Female,african american,22.5,62,60-70,46-50,
+20230613,s1,kristopher_mata,M,L,165,30,135,39,83,128,163,90,30,50,10,3,Male,caucasian,24.2,66,60-70,18-24,skipped
+20230614,s0,elizabeth_sandoval,XL,XXL,181,29,148,37,93,137,183,100,35,56,10,5,Male,caucasian,22.9,75,70-80,18-24,
+20230614,s1,matthew_harper,M,L,165,30,135,39,83,128,163,90,30,50,10,3,Male,caucasian,24.2,66,60-70,18-24,remap 0613/s0
+20230615,s0,dawn_heath,L,XL,169,30,140,46,93,136,173,94,33,46,10,4,Male,hispanic,28.4,81,80-90,25-30,
+20230615,s1,vincent_bell,L,XL,167,29,139,49,84,141,181,95,33,50,11,5,Male,african american,29.4,82,80-90,46-50,
+20230616,s0,kristen_thomas,M,L,175,29,142,46,88,144,182,97,32,52,10,4,Male,caucasian,27.8,85,80-90,31-35,
+20230616,s1,michael_griffin,XL,XXL,167,28,141,44,82,137,174,92,36,49,9,1,Female,african american,34.8,97,95-100,31-35,
+20230619,s0,jeremiah_odonnell,S,M,156,27,126,36,72,121,153,90,35,45,9,5,Female,south asian,21.4,52,50-60,18-24,
+20230619,s1,eric_martin,S,M,163,25,133,37,80,129,163,88,31,51,13,1,Female,east asian,18.4,49,45-50,31-35,
+20230620,s0,marie_vasquez,M,L,178,29,145,46,86,137,173,92,33,50,11,3,Male,african american,18.6,59,50-60,36-40,
+20230620,s1,alison_carter,M,L,174,29,146,44,77,136,170,98,30,52,11,4,Male,south asian,22.5,68,60-70,36-40,
+20230621,s0,sergio_howard,L,XL,185,29,152,45,87,143,185,104,36,56,10,3,Male,caucasian,24.8,85,80-90,36-40,
+20230621,s1,kevin_davis,S,M,171,27,141,44,87,136,171,95,35,49,10,4,Female,east asian,21.5,63,60-70,25-30,
+20230622,s0,john_solomon,M,L,170,30,141,41,89,140,175,89,33,49,9,4,Male,south asian,22.1,64,60-70,31-35,
+20230622,s1,sherri_scott,S,M,161,27,136,37,93,128,163,93,37,47,12,5,Female,african american,27.4,71,70-80,31-35,
+20230623,s0,erin_mccormick,XL,4XL,189,30,159,47,95,151,192,112,36,57,11,5,Male,south asian,23.8,85,80-90,36-40,
+20230623,s1,joshua_thompson,M,L,172,30,147,44,82,140,176,101,31,52,12,4,Male,south asian,24.3,72,70-80,36-40,
+20230626,s0,gilbert_simmons,M,L,186,29,156,39,87,149,187,104,34,54,10,5,Female,other/mixed,24,83,80-90,31-35,
+20230626,s1,albert_chapman,S,M,173,27,147,36,84,140,176,100,29,53,11,3,Female,african american,21.4,64,60-70,25-30,
+20230627,s0,kenneth_hicks,S,M,159,28,132,35,74,121,152,85,30,49,10,5,Female,east asian,21,53,50-60,18-24,
+20230627,s1,robert_reynolds,M,L,165,25,134,40,81,124,162,96,33,45,7,3,Female,other/mixed,26.4,72,70-80,18-24,
+20230628,s0,adriana_gonzalez,L,XL,177,25,143,36,92,143,180,102,33,56,7,4,Male,caucasian,25.9,81,80-90,25-30,
+20230628,s1,hayley_little,L,XL,172,30,144,44,85,136,170,96,33,49,8,2,Male,caucasian,28.4,84,80-90,31-35,
+20230629,s0,nancy_mahoney,S,M,155,24,129,36,74,117,151,88,28,42,8,1,Female,south asian,22.1,53,50-60,31-35,
+20230629,s1,laurie_webb,L,XL,178,32,147,40,84,143,194,98,33,55,11,4,Male,east asian,23.7,75,70-80,36-40,
+20230630,s0,gloria_carr,L,XL,180,31,148,33,79,142,181,94,33,55,11,3,Male,east asian,26.5,86,80-90,41-45,
+20230630,s1,linda_coleman,M,L,155,27,128,42,77,123,157,88,38,43,9,6,Female,south asian,30.8,74,70-80,25-30,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20230703,s0,tommy_ayala,L,XL,160,26,135,42,77,130,166,94,39,44,10,3,Female,south asian,28.5,73,70-80,18-24,
+20230703,s1,joshua_burke,S,M,158,25,137,37,80,134,169,94,36,48,9,3,Female,african american,19.1,64,60-70,31-35,
+20230705,s0,william_davis,L,XL,165,30,136,39,85,136,170,95,33,44,8,4,Male,east asian,26.8,73,70-80,31-35,
+20230705,s1,april_harris,L,XL,190,31,157,32,89,149,187,93,34,56,11,4,Male,south asian,26,94,90-100,18-24,
+20230706,s0,breanna_reese,L,XL,188,31,149,32,89,148,186,107,32,58,11,4,Male,south asian,20.7,73,70-80,25-30,
+20230706,s1,morgan_terrell,S,M,154,25,130,36,77,123,150,88,34,43,8,3,Female,caucasian,23.2,55,50-60,36-40,
+20230707,s0,anthony_perez,XXL,4XL,155,29,136,43,82,128,165,89,44,41,7,3,Female,caucasian,37.9,91,90-100,36-40,
+20230707,s1,elizabeth_tucker,L,XL,182,31,155,39,92,148,188,102,30,51,10,4,Male,caucasian,23.2,77,70-80,25-30,
+20230710,s0,barbara_norman,XL,XXL,185,31,156,45,91,149,188,104,33,52,11,4,Male,east asian,28,96,90-100,46-50,
+20230710,s1,jennifer_torres,S,M,176,30,145,39,80,140,178,98,27,51,11,4,Female,caucasian,20.7,64,60-70,25-30,
+20230711,s0,frederick_young,M,M,153,26,126,37,72,120,153,89,27,44,9,3,Female,african american,28.2,66,60-70,31-35,
+20230711,s1,maria_duran,M,L,183,30,152,33,94,149,188,98,33,55,10,3,Male,caucasian,20.3,68,60-70,31-35,
+20230712,s0,laura_wilson,M,M,170,28,138,30,71,129,166,89,30,45,9,3,Female,caucasian,22.5,65,60-70,25-30,
+20230712,s1,stacy_cook,S,M,170,31,139,33,92,142,182,98,32,49,9,3,Male,south asian,23.5,68,60-70,36-40,
+20230713,s0,brian_wheeler,M,M,175,28,147,30,84,146,182,106,29,45,9,2,Female,african american,20.9,64,60-70,25-30,
+20230713,s1,amy_crawford,L,XL,176,31,149,35,86,141,179,98,33,49,11,4,Female,caucasian,24.5,76,70-80,36-40,
+20230714,s0,christopher_rush,S,M,151,26,125,34,76,128,162,90,37,40,7,2,Female,south asian,25.4,58,50-60,25-30,
+20230714,s1,jacob_webb,M,L,165,30,132,36,85,135,170,89,31,44,7,1,Male,southeast asian,23.5,64,60-70,25-30,
+20230717,s0,danielle_ortiz,M,L,174,30,143,35,80,141,178,95,33,48,11,3,Male,southeast asian,21.8,66,60-70,25-30,
+20230717,s1,janice_lopez,M,L,179,30,144,35,94,150,190,94,31,51,10,3,Male,caucasian,21.2,68,60-70,31-35,
+20230718,s0,timothy_velasquez,M,L,180,26,148,35,89,144,181,97,33,49,8,1,Male,caucasian,20.4,66,60-70,25-30,
+20230718,s1,john_williams,S,M,153,25,127,29,77,124,160,91,34,42,9,2,Female,caucasian,28.6,67,60-70,36-40,
+20230719,s0,shane_smith,S,M,163,26,135,29,79,125,158,91,29,43,11,4,Female,east asian,18.1,48,40-50,25-30,
+20230719,s1,patrick_diaz,L,L,154,26,124,32,73,118,151,87,34,40,10,3,Female,southeast asian,24.5,58,50-60,46-50,
+20230720,s0,robert_ballard,L,L,180,29,147,36,88,142,181,102,32,50,9,3,Male,other/mixed,21,68,60-70,31-35,
+20230721,s0,mitchell_mcdonald,XL,XXL,199,35,159,36,97,153,199,103,29,55,11,4,Male,caucasian,18.5,65,60-70,25-30,
+20230721,s1,david_ramirez,S,M,164,29,135,34,85,133,173,89,31,47,9,1,Male,south asian,21.6,58,50-60,25-30,
+20230724,s0,tyler_ayers,S,M,163,28,137,29,79,129,162,91,31,45,11,3,Female,caucasian,25.2,67,60-70,41-45,
+20230724,s1,justin_heath,S,M,164,27,136,29,79,132,164,91,30,43,8,3,Female,east asian,18.2,49,40-50,36-40,
+20230725,s0,stephanie_moses,S,M,164,25,134,29,86,135,165,93,29,41,9,3,Female,caucasian,21.2,57,50-60,36-40,
+20230725,s1,julie_taylor,S,M,161,25,132,26,76,127,165,89,28,45,9,1,Female,african american,18.5,48,40-50,36-40,
+20230726,s0,mark_richardson,S,M,155,24,129,27,73,123,157,91,27,40,8,1,Female,east asian,18.3,44,40-50,36-40,
+20230726,s1,thomas_nixon,M,L,168,26,140,31,79,129,167,98,31,43,11,3,Female,caucasian,20.9,59,50-60,36-40,
+20230727,s0,joanne_white,M,L,166,26,139,30,81,131,167,89,29,43,10,3,Female,other/mixed,19.2,53,50-60,41-45,
+20230727,s1,jeremy_gill,S,M,156,24,129,30,76,118,156,86,30,40,9,2,Female,east asian,19.7,48,40-50,41-45,
+20230728,s0,lauren_mayer,S,M,158,24,131,27,82,127,165,94,27,44,9,3,Female,southeast asian,19.2,48,40-50,18-24,
+20230728,s1,bradley_herman,S,M,160,24,132,29,78,130,158,92,30,43,9,3,Female,east asian,18.8,48,40-50,18-24,
+20230731,s0,tammy_campos,S,M,165,27,136,32,78,130,166,95,30,45,8,3,Male,caucasian,18,49,40-50,46-50,
+20230731,s1,angela_mclean,S,M,158,25,132,29,72,121,156,89,29,40,10,3,Female,south asian,18.4,46,40-50,46-50,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20230801,s0,aimee_davis,S,M,155,26,127,28,75,119,155,89,30,41,10,2,Female,caucasian,22.5,54,50-60,46-50,
+20230801,s1,alexis_hernandez,S,M,165,26,138,30,80,127,163,92,29,44,10,3,Female,other/mixed,21.3,58,50-60,18-24,
+20230802,s0,kelly_golden,M,L,178,30,147,43,80,141,187,99,32,57,10,3,Male,south asian,20.2,64,60-70,18-24,
+20230802,s1,scott_mcbride,L,XL,167,29,140,34,86,139,179,95,34,47,10,3,Male,south asian,25.8,72,70-80,46-50,
+20230803,s0,robert_howard,M,L,173,30,145,30,80,133,171,98,30,47,12,4,Female,caucasian,18.7,56,50-60,31-35,
+20230803,s1,jennifer_sexton,S,M,155,25,126,30,79,120,157,85,28,39,8,1,Female,southeast asian,20.4,49,45-50,18-24,
+20230807,s0,dominique_frye,XL,XXL,183,30,154,49,90,150,187,100,33,49,10,3,Male,hispanic,24.5,82,80-90,18-24,
+20230807,s1,vanessa_chavez,S,M,158,27,128,33,73,127,163,86,30,45,9,3,Female,east asian,19.6,49,45-50,25-30,
+20230808,s0,timothy_taylor,S,M,154,26,131,31,74,120,154,94,31,42,11,4,Female,south asian,18.6,44,45-50,18-24,
+20230808,s1,erin_jones,S,M,166,27,142,32,85,142,182,103,28,49,12,3,Female,south asian,17.1,47,45-50,18-24,
+20230809,s1,laura_smith,S,M,158,25,130,27,72,108,147,95,30,45,10,3,Female,caucasian,22,55,50-60,36-40,
+20230811,s1,paul_phillips,L,XXL,173,31,148,38,84,132,175,93,37,45,9,3,Male,caucasian,32.4,97,90-100,25-30,
+20230814,s0,leah_gaines,XL,XXL,190,33,165,40,96,153,196,104,35,54,12,3,Male,other/mixed,26.87,99,90-100,36-40,
+20230814,s1,david_hall,XL,XXL,181,30,153,40,91,142,182,94,35,50,11,4,Male,caucasian,30.22,99,90-100,46-50,
+20230815,s0,samantha_lester,S,M,167,27,139,27,84,130,165,91,28,41,8,1,Female,south asian,19.4,54,50-60,18-24,
+20230815,s1,lisa_colon,S,M,165,25,141,27,77,119,162,96,27,43,8,2,Female,east asian,20.8,56.7,50-60,36-40,
+20230816,s0,mary_ortiz,XL,XXL,181,30,155,41,92,141,181,104,34,51,10,3,Male,caucasian,29.91,98,90-100,46-50,
+20230816,s1,jeffery_bryant,L,XL,182,29,161,30,90,144,182,102,30,47,11,3,Male,caucasian,24.15,80,80-90,31-35,
+20230817,s0,brittney_powell,L,XL,183,28,158,33,97,150,189,100,33,50,10,2,Female,caucasian,23.97,80.3,80-90,36-40,
+20230817,s1,rebecca_ward,L,XL,182,30,157,37,90,147,189,106,35,52,9,3,Male,east asian,21.91,72.6,70-80,46-50,
+20230818,s0,amy_padilla,L,XL,182,32,152,36,91,143,183,95,32,49,13,5,Male,caucasian,24.65,81.7,80-90,46-50,
+20230818,s1,daniel_gregory,M,L,168,27,141,29,85,135,174,94,29,46,9,2,Female,caucasian,20.89,59,50-60,41-45,
+20230821,s1,william_wilson,L,XL,170,28,143,36,77,127,165,98,36,47,10,4,Male,southeast asian,32.96,95.3,80-90,25-30,
+20230822,s0,kyle_parker,S,M,160,27,133,29,83,127,164,96,27,46,10,3,Female,african american,19.14,49,45-50,18-24,
+20230822,s1,joshua_rice,M,L,171,29,144,35,79,133,171,103,30,50,9,3,Male,southeast asian,20.18,59,50-60,18-24,
+20230823,s0,evelyn_moody,L,XL,169,29,142,32,87,136,172,100,32,47,10,3,Female,caucasian,22.76,65,60-70,25-30,
+20230823,s1,alison_riddle,XL,XXL,183,32,156,33,92,149,188,111,33,55,11,4,Male,caucasian,24.49,82,80-90,36-40,
+20230824,s0,kim_wilkins,XL,XXL,177,27,150,32,87,144,185,101,37,48,11,2,Female,caucasian,30.12,94.4,90-100,46-50,
+20230824,s1,jenna_farmer,XL,XXL,172,28,143,33,85,132,172,100,34,46,11,3,Female,other/mixed,31.43,93,90-100,18-24,
+20230825,s0,carrie_robinson,XL,XXL,170,30,143,37,81,138,174,98,35,51,11,4,Male,caucasian,31.39,90.7,90-100,41-45,
+20230825,s1,alejandra_reynolds,XL,XXL,186,33,161,35,85,147,188,104,33,49,11,4,Male,caucasian,24.25,83.9,80-90,31-35,
+20230828,s0,kaylee_johnson,XL,XXL,192,32,164,37,96,155,194,113,33,50,10,3,Male,caucasian,19.69,72.6,80-90,18-24,
+20230828,s1,omar_patterson,XL,XXL,184,31,157,34,89,148,188,106,34,54,11,4,Male,african american,28.14,95.3,90-100,18-24,
+20230829,s0,ray_humphrey,XL,XXL,175,31,150,37,88,138,179,99,37,50,10,4,Male,east asian,32.22,99,90-100,18-24,
+20230829,s1,angel_roberts,S,M,158,26,132,28,77,121,156,96,28,43,10,4,Female,east asian,21.8,54.4,50-60,25-30,
+20230830,s0,jason_vaughn,L,L,153,24,126,28,76,116,152,94,28,40,9,2,Female,hispanic,31.1,73.0,60-70,46-50,
+20230830,s1,christy_ramirez,S,M,154,24,127,28,76,125,161,90,29,42,10,2,Female,southeast asian,22.9,54.4,50-60,25-30,
+20230831,s1,ronald_harris,L,XL,162,25,137,29,82,124,158,89,33,47,9,1,Female,caucasian,32,84,80-90,36-40,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20230901,s0,thomas_marks,M,M,164,25,133,31,77,128,161,88,33,45,9,3,Female,caucasian,26,70,70-80,36-40,
+20230901,s1,hannah_brown,XL,XXL,172,27,147,34,88,139,173,91,32,50,12,4,Female,caucasian,33.1,98,90-100,46-50,
+20230905,s1,elizabeth_morgan,M,L,163,28,134,30,87,132,167,98,30,46,11,3,Female,southeast asian,25.9,69,60-70,36-40,
+20230906,s0,pam_nelson,L,XL,184,30,154,35,85,141,180,101,33,49,8,4,Male,east asian,20.9,71,70-80,36-40,
+20230906,s1,ashley_owens,M,L,172,27,145,30,85,141,180,102,30,47,11,3,Female,african american,23.3,69,60-70,25-30,
+20230907,s0,margaret_mccormick,M,L,170,30,140,33,82,138,174,104,30,51,10,4,Male,south asian,21.8,63,60-70,18-24,
+20230907,s1,mary_cook,XL,XXL,196,33,170,34,96,157,201,115,30,58,8,2,Male,african american,20.5,79,70-80,36-40,
+20230908,s0,joel_anderson,L,XL,178,30,147,33,86,139,179,102,31,50,10,4,Male,southeast asian,23.6,75,70-80,25-30,
+20230908,s1,danielle_pierce,M,L,174,28,143,34,81,128,164,98,30,48,9,2,Male,south asian,22.7,69,60-70,31-35,
+20230911,s0,angela_gomez,M,L,168,26,138,30,82,130,164,96,29,49,10,3,Female,south asian,20.9,59,50-60,31-35,
+20230911,s1,ethan_jacobson,L,XL,175,30,146,33,88,148,182,92,32,47,8,4,Male,south asian,22.5,69,60-70,25-30,
+20230912,s0,jeffrey_barnes,L,XL,181,30,150,34,90,140,180,100,31,51,9,3,Male,caucasian,23.1,76,70-80,31-35,
+20230912,s1,peter_henderson,M,L,171,27,144,32,85,138,175,92,32,48,9,1,Female,caucasian,24.6,72,70-80,41-45,
+20230913,s0,stacey_lamb,L,XL,183,30,149,38,89,146,185,98,35,48,9,1,Male,caucasian,24.8,83,80-90,41-45,
+20230913,s1,austin_lopez,L,XL,166,28,139,31,77,123,161,102,37,42,11,3,Female,caucasian,32.3,89,80-90,36-40,
+20230914,s0,tamara_gibbs,M,M,162,29,134,29,79,128,166,96,29,44,10,2,Female,east asian,22.5,59,50-60,18-24,
+20230914,s1,stephanie_arnold,M,M,156,25,131,30,74,124,156,86,29,43,9,3,Female,east asian,22.6,55,50-60,36-40,
+20230915,s0,richard_gallegos,L,XL,174,29,147,32,85,139,176,102,32,49,12,4,Female,caucasian,24.7,75,70-80,25-30,
+20230915,s1,colleen_drake,L,XL,182,32,152,36,90,151,192,102,32,51,9,3,Male,african american,24.8,82,80-90,36-40,
+20230918,s0,kevin_shaw,L,XL,176,31,145,35,89,133,177,102,30,51,10,3,Male,caucasian,21.9,68,60-70,36-40,
+20230918,s1,bobby_griffith,L,XL,161,25,133,33,77,130,162,97,34,42,9,2,Female,caucasian,38.2,99,90-100,25-30,
+20230919,s0,andrew_taylor,XL,XXL,159,26,128,32,77,122,157,92,31,41,9,2,Female,caucasian,35.2,89,80-90,36-40,
+20230919,s1,jessica_webster,M,L,167,24,142,32,81,131,166,96,31,44,9,1,Female,caucasian,24.7,69,70-80,25-30,
+20230920,s0,jeremy_lewis,M,L,166,28,138,33,82,129,166,95,31,43,8,3,Male,east asian,25,69,60-70,36-40,
+20230920,s1,william_hansen,M,M,159,26,130,29,74,126,157,92,29,43,10,3,Female,east asian,21.8,55,50-60,25-30,
+20230921,s0,justin_martin,M,L,162,26,134,30,73,122,158,94,30,48,11,4,Female,east asian,22.5,59,50-60,36-40,
+20230921,s1,alec_meza,M,L,155,24,127,30,74,123,157,92,29,43,9,3,Female,east asian,24.6,59,50-60,25-30,
+20230922,s0,philip_morales,M,L,165,26,139,33,82,134,167,94,29,44,9,2,Female,caucasian,24.6,67,60-70,31-35,
+20230922,s1,steve_douglas,M,L,167,29,139,32,79,130,165,97,29,49,12,3,Female,caucasian,22.9,64,60-70,36-40,
+20230925,s0,suzanne_romero,L,XL,188,31,155,33,90,149,189,104,33,51,9,3,Male,caucasian,23.5,83,80-90,18-24,
+20230925,s1,xavier_norris,M,M,155,24,127,32,76,124,160,92,28,39,9,3,Female,southeast asian,26.6,64,60-70,41-45,
+20230926,s0,tasha_lee,M,M,162,25,135,30,78,128,163,98,30,46,10,4,Female,caucasian,19.8,52,50-60,31-35,
+20230926,s1,megan_mejia,L,L,180,32,147,35,91,143,183,101,30,54,10,3,Male,hispanic,23.1,75,70-80,18-24,
+20230927,s0,zachary_price,XL,XL,185,32,155,30,88,146,186,109,32,51,10,4,Male,southeast asian,19.9,68,60-70,18-24,
+20230927,s1,samantha_may,M,L,153,26,127,31,73,115,151,89,35,45,10,3,Female,caucasian,32.5,67,60-70,46-50,
+20230928,s0,grace_randolph,L,L,175,27,146,32,90,142,180,107,31,51,7,2,Female,caucasian,18.6,57,50-60,31-35,
+20230928,s1,barbara_sandoval,M,M,163,29,134,30,82,132,172,95,30,46,9,3,Male,african american,23.3,62,60-70,31-35,
+20230929,s0,samuel_campos,L,L,177,28,149,30,82,127,170,101,30,49,12,4,Female,caucasian,18.8,59,50-60,25-30,
+20230929,s1,alan_burns,L,XL,151,26,126,29,72,113,151,92,30,41,11,3,Female,hispanic,35.5,81,80-90,25-30,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20231002,s0,benjamin_bailey,L,L,170,29,137,34,88,138,178,93,34,53,11,4,Male,southeast asian,23.9,69,60-70,36-40,
+20231002,s1,larry_thompson,L,L,163,25,133,28,77,125,158,94,26,44,9,3,Female,caucasian,22.2,59,50-60,25-30,
+20231003,s0,thomas_tanner,L,L,165,28,136,32,83,135,172,93,32,47,7,2,Male,east asian,24.2,66,60-70,41-45,
+20231003,s1,allen_evans,L,L,173,30,143,33,83,137,177,103,34,48,9,3,Male,east asian,24,72,70-80,41-45,
+20231004,s0,corey_coleman,M,M,157,26,128,28,75,125,160,91,28,42,10,3,Female,south asian,24.7,61,60-70,25-30,
+20231004,s1,ashley_reyes,L,L,169,30,140,33,89,139,181,98,33,49,11,3,Male,south asian,24.2,69,60-70,41-45,
+20231005,s0,glenn_richardson,M,L,170,30,137,31,84,132,172,96,31,46,10,3,Male,southeast asian,24.2,70,60-70,25-30,
+20231005,s1,sheri_white,M,M,159,25,132,31,76,127,162,94,29,45,9,3,Female,other/mixed,23.7,60,60-70,31-35,
+20231006,s0,david_vega,L,XL,181,27,151,33,84,133,172,102,33,52,10,5,Female,caucasian,20.1,66,60-70,36-40,
+20231006,s1,kirk_flowers,M,L,168,28,138,31,85,138,177,99,32,46,8,1,Male,hispanic,24.8,70,60-70,18-24,
+20231009,s0,clayton_bradley,L,XL,178,28,148,32,92,140,180,104,32,50,10,3,Male,african american,20.1,64,60-70,25-30,
+20231009,s1,patrick_hall,M,M,162,24,135,28,79,125,160,91,26,46,9,2,Female,east asian,18.8,49,45-50,25-30,
+20231010,s0,albert_hammond,XL,XXL,175,28,148,32,87,142,180,109,31,53,12,3,Female,hispanic,26.7,82,80-90,25-30,
+20231010,s1,cheryl_johnson,M,M,149,25,122,29,75,121,153,91,29,43,9,4,Female,south asian,24.7,55,50-60,31-35,
+20231011,s0,devon_norris,L,XL,181,31,148,44,84,137,178,103,34,56,11,3,Male,caucasian,21.3,68,60-70,18-24,
+20231011,s1,daniel_kim,M,XL,167,26,141,27,80,131,163,99,31,48,10,3,Female,caucasian,24.7,69,60-70,31-35,
+20231012,s0,michael_lee,L,XL,183,30,153,49,90,150,187,100,33,49,10,3,Male,hispanic,23.5,79,79-80,18-24,
+20231012,s1,johnathan_good,L,L,171,25,142,31,82,133,165,101,29,46,8,1,Female,caucasian,22.2,65,60-70,31-35,
+20231013,s0,shelley_jones,L,L,158,25,131,32,81,128,163,91,31,42,9,3,Female,caucasian,24.8,62,60-70,36-40,
+20231013,s1,lucas_flores,L,L,170,28,142,28,81,133,170,98,30,51,11,3,Female,caucasian,21.2,67,60-70,31-35,
+20231016,s0,holly_keller,L,XL,181,30,146,33,81,143,181,103,33,46,10,1,Male,caucasian,24.7,81,80-90,18-24,
+20231016,s1,diane_williams,L,XL,176,28,147,30,76,129,171,108,28,54,9,3,Female,other/mixed,19.1,59,50-60,31-35,
+20231017,s0,emily_farmer,L,XL,183,31,150,35,95,152,195,110,34,56,12,3,Male,african american,24.4,82,80-90,18-24,
+20231017,s1,shawn_smith,M,M,149,24,124,29,74,114,149,88,27,45,8,2,Female,caucasian,22.5,50,50-60,41-45,
+20231018,s0,scott_hutchinson,L,L,174,30,143,35,80,141,178,95,33,48,11,3,Male,southeast asian,24.1,73,70-80,18-24,
+20231018,s1,debra_melton,M,M,155,27,129,30,82,135,170,91,28,46,10,3,Male,african american,24.6,59,50-60,31-35,
+20231019,s0,douglas_martin,M,L,175,28,144,33,90,137,180,102,30,47,8,3,Male,caucasian,22.2,68,60-70,41-45,
+20231019,s1,brady_pearson,M,L,163,25,138,27,74,121,157,99,30,46,9,3,Female,caucasian,24.1,64,60-70,36-40,
+20231020,s0,anthony_chen,M,M,163,27,132,30,79,127,161,95,29,49,11,4,Female,east asian,18.8,50,45-50,18-24,
+20231020,s1,steven_jackson,L,L,172,27,145,35,85,135,171,102,28,47,11,3,Female,african american,23.3,69,60-70,25-30,
+20231023,s0,christopher_green,M,M,149,20,124,33,72,119,149,93,29,42,8,4,Female,south asian,22.5,50,45-50,18-24,
+20231023,s1,shannon_burns,XL,XXL,180,30,152,38,88,147,184,100,33,49,10,3,Male,caucasian,24.7,80,80-90,31-35,
+20231024,s0,john_barr,M,M,159,25,131,30,73,118,155,94,26,44,9,3,Female,caucasian,22.9,58,50-60,31-35,
+20231024,s1,william_mendoza,M,M,159,25,134,27,78,127,160,91,29,42,10,2,Female,caucasian,23.7,60,50-60,36-40,
+20231025,s0,logan_santos,XL,XL,170,28,141,36,77,127,165,98,36,47,10,4,Male,southeast asian,32.9,95,90-100,31-35,
+20231025,s1,alicia_drake,L,L,180,29,147,38,89,141,177,102,28,52,11,3,Male,african american,18.5,60,50-60,31-35,
+20231026,s0,arthur_byrd,XL,XL,164,28,138,35,78,125,165,91,34,47,8,3,Male,southeast asian,32.7,88.2,80-90,46-50,
+20231026,s1,amy_rosales,M,L,160,29,135,39,86,134,171,97,30,45,10,2,Male,african american,24.2,62,60-70,31-35,
+20231027,s0,george_james,M,M,159,29,129,29,85,132,165,91,28,43,9,3,Male,southeast asian,19.8,50,45-50,18-24,
+20231027,s1,stacie_cross,L,XL,159,29,134,33,82,132,168,96,32,48,9,3,Male,caucasian,24.5,62,60-70,41-45,
+20231030,s0,angela_garcia,M,L,149,26,124,29,74,121,155,89,28,43,9,3,Female,south asian,20.7,46,45-50,18-24,
+20231030,s1,allison_harris,L,XL,173,30,145,30,88,134,174,100,32,51,10,3,Male,east asian,21.3,64,60-70,41-45,
+20231031,s0,jason_brown,L,L,165,27,136,32,80,129,166,9t5,30,50,11,4,Female,east asian,24.6,67,60-70,41-45,
+20231031,s1,eric_dickerson,L,XL,172,29,140,38,86,138,177,103,31,47,8,3,Male,southeast asian,23.9,71,70-80,41-45,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20231101,s0,joshua_smith,L,L,156,24,131,36,80,124,158,95,30,46,8,2,Female,southeast asian,24.7,57,50-60,36-40,
+20231101,s1,dean_krause,XL,XXL,172,30,143,35,86,134,173,99,32,50,10,2,Male,caucasian,24.7,73,70-80,41-45,
+20231102,s0,samuel_rogers,L,XL,173,30,141,35,87,142,179,100,34,47,7,2,Male,southeast asian,23.4,70,70-80,46-50,
+20231102,s1,trevor_riley,XL,XXL,183,32,153,40,90,145,188,110,32,53,8,3,Male,caucasian,24.8,83,80-90,18-24,
+20231103,s0,allison_house,L,XL,169,27,138,29,78,128,164,99,30,47,10,3,Female,hispanic,24.5,70,70-80,36-40,
+20231103,s1,erica_sims,M,L,169,30,143,34,94,137,176,96,31,48,10,3,Male,south asian,24.5,70,70-80,31-35,
+20231106,s0,nancy_david,M,M,162,25,133,30,78,127,164,93,29,46,10,3,Female,east asian,22.5,59,50-60,18-24,
+20231106,s1,amanda_rodgers,XL,XXL,176,31,145,32,74,134,174,101,31,50,9,3,Male,caucasian,24.8,77,70-80,46-50,
+20231107,s0,amy_snow,M,M,157,23,127,36,76,118,153,88,30,44,9,3,Female,east asian,21.5,53,50-60,18-24,
+20231107,s1,gregory_townsend,XL,XXL,179,31,148,45,89,140,177,99,30,48,9,3,Male,caucasian,24.7,79,80-90,36-40,
+20231108,s0,nicholas_hicks,M,L,170,28,142,40,85,138,174,91,33,44,8,3,Male,hispanic,24.6,71,70-80,31-35,
+20231108,s1,kurt_young,M,L,175,29,149,40,84,139,180,100,31,50,8,3,Male,african american,23.8,73,70-80,46-50,
+20231109,s0,janet_walsh,L,XL,180,31,151,40,86,141,180,101,32,54,8,3,Male,caucasian,24,78,70-80,36-40,
+20231110,s0,thomas_brown,M,XL,180,30,147,42,88,140,182,98,31,48,7,2,Male,caucasian,24,78,70-80,36-40,
+20231110,s1,jerry_shaffer,M,L,170,27,140,40,82,135,174,96,30,48,7,2,Male,southeast asian,24.6,69,60-70,41-45,
+20231113,s0,patricia_gutierrez,L,XXL,174,31,147,41,88,140,177,100,35,51,9,3,Male,caucasian,32.4,97,90-100,25-30,
+20231113,s1,greg_clark,XL,XL,164,28,138,35,78,125,165,91,34,47,8,3,Male,southeast asian,32.7,88,80-90,46-50,
+20231114,s0,autumn_garcia,L,XXL,174,31,147,41,88,140,177,100,35,51,9,3,Male,caucasian,32.4,97,90-100,25-30,
+20231114,s1,logan_walton,XL,XL,164,28,138,35,78,125,165,91,34,47,8,3,Male,southeast asian,32.7,88,80-90,46-50,
+20231115,s0,carly_patterson,XL,XXL,180,30,148,40,91,136,176,101,31,49,9,3,Male,caucasian,20.7,67,60-70,25-30,
+20231115,s1,andrew_johnson,XL,XL,180,26,147,38,81,140,178,107,33,51,9,5,Female,caucasian,20.4,66,60-70,18-24,
+20231116,s0,kimberly_williams,XL,XL,181,28,147,35,87,144,188,108,32,49,11,3,Male,african american,24.7,81,80-90,25-30,
+20231116,s1,justin_ramirez,M,L,157,24,129,32,75,119,152,94,32,45,9,5,Female,southeast asian,23.5,58,50-60,46-50,
+20231117,s0,randy_martin,M,L,158,26,133,30,77,124,157,97,31,45,9,3,Female,southeast asian,23.2,58,50-60,31-35,
+20231117,s1,brooke_butler,L,XL,181,28,147,40,86,138,173,92,35,49,8,3,Male,caucasian,24.7,81,80-90,36-40,
+20231120,s0,sarah_miller,L,L,169,25,140,34,85,136,174,102,32,48,10,3,Female,african american,24.2,69,60-70,46-50,
+20231120,s1,anna_chambers,XL,XXL,191,28,154,40,93,153,193,103,31,51,10,3,Male,african american,18.6,68,60-70,31-35,
+20231121,s0,alexandria_griffith,L,L,168,27,142,33,80,129,164,104,33,53,11,4,Female,caucasian,21.5,59,50-60,36-40,
+20231121,s1,christopher_martinez,M,L,182,27,150,32,89,139,177,109,32,57,10,5,Female,south asian,19.3,64,60-70,18-24,
+20231122,s0,frank_hayden,M,M,155,26,124,36,74,119,152,94,31,42,7,2,Female,east asian,24.6,59,50-60,25-30,
+20231122,s1,harold_copeland,L,XL,181,31,148,44,84,137,178,103,34,56,11,3,Male,caucasian,21.3,68,60-70,18-24,
+20231127,s0,steven_vang,M,M,167,27,139,27,84,130,165,90,27,41,8,1,Female,other/mixed,19.4,49,40-50,18-24,
+20231127,s1,robyn_blackburn,M,L,169,29,137,42,85,131,165,93,32,46,8,3,Male,southeast asian,20.8,59.5,50-60,25-30,
+20231128,s0,paul_nguyen,M,M,164,30,131,40,81,132,168,94,31,45,8,3,Male,southeast asian,21.6,58,50-60,18-24,
+20231128,s1,michael_vargas,M,M,168,26,139,30,83,135,167,101,30,48,9,3,Female,south asian,20.9,59,50-60,36-40,
+20231129,s0,brittney_goodwin,M,M,157,26,131,32,77,117,152,92,30,48,8,3,Female,east asian,19.9,49,40-50,25-30,
+20231129,s1,dylan_jones,M,L,169,27,139,37,80,132,169,95,30,49,7,1,Male,african american,19.2,55,50-60,31-35,
+20231130,s0,danielle_wu,XL,XXL,183,30,153,49,90,150,187,100,33,49,10,3,Male,hispanic,24.5,82,80-90,18-24,
+20231130,s1,mary_barker,XL,XXL,186,29,153,38,92,151,190,109,32,51,8,2,Male,southeast asian,18.7,65,60-70,25-30,
+,,,,,,,,,,,,,,,,,,,,,,,
+,,,,,,,,,,,,,,,,,,,,,,,
+20231201,s0,walter_park,M,L,167,27,135,36,78,129,164,93,28,47,8,3,Male,south asian,19.7,55,50-60,31-35,
+20231201,s1,daniel_wiley,L,XL,166,25,137,35,88,133,169,95,33,47,10,2,Male,south asian,24.7,68,60-70,31-35,
+20231204,s0,jacqueline_brewer,M,M,159,23,128,30,78,121,153,91,28,40,9,2,Female,east asian,19.2,49,45-50,25-30,
+20231204,s1,sylvia_joseph,L,L,171,29,137,34,88,138,178,93,34,53,10,4,Male,southeast asian,24.3,71,70-80,36-40,
+20231205,s0,sarah_roberts,L,L,174,28,142,37,86,144,182,100,33,51,8,2,Male,south asian,24.1,73,70-80,18-24,
+20231205,s1,alexis_wyatt,M,M,159,24,131,31,76,125,158,92,29,45,9,3,Female,south asian,19.4,49,45-50,25-30,
+20231206,s0,david_morgan,M,M,158,29,129,29,85,132,165,91,28,43,9,3,Male,southeast asian,19.6,49,45-50,18-24,
+20231206,s1,virginia_perez,L,L,174,25,146,31,87,132,169,103,31,52,9,3,Female,caucasian,19.2,58,50-60,25-30,
+20231207,s0,jodi_morrison,M,M,167,27,137,33,87,138,174,99,31,50,12,4,Female,african american,20,56,50-60,31-35,
+20231207,s1,katie_white,M,L,163,24,133,32,81,127,166,94,31,48,10,3,Female,african american,20.3,54,50-60,25-30,
+20231208,s0,ronald_guerra,L,L,164,27,136,35,75,130,165,97,34,47,10,4,Female,south asian,24.5,66,60-70,31-35,
+20231208,s1,courtney_ross,L,L,167,30,138,34,80,130,166,98,33,49,10,3,Male,south asian,24.7,69,60-70,25-30,
+20231211,s0,rebecca_brennan,M,M,159,25,134,29,76,125,161,101,27,51,9,4,Female,caucasian,19.4,49,40-50,18-24,
+20231211,s1,seth_bowman,L,L,175,30,145,38,86,139,177,103,30,51,10,3,Male,caucasian,21.5,66,60-70,18-24,
+20231212,s0,paul_arellano,L,L,176,29,144,40,83,142,182,103,31,49,7,2,Male,caucasian,19,59,50-60,25-30,
+20231212,s1,justin_jackson,M,M,159,25,134,31,76,123,158,96,29,47,9,5,Female,caucasian,19,48,40-50,25-30,
+20231213,s0,shawn_wright,L,L,174,29,143,32,83,139,175,103,32,47,10,4,Female,caucasian,18.8,57,50-60,25-30,
+20231213,s1,brenda_jacobs,M,M,164,24,135,30,82,125,158,90,29,46,9,2,Female,hispanic,22.6,61,60-70,31-35,
+20231214,s0,jeremy_allen,L,XL,174,32,145,37,87,145,184,102,30,55,10,5,Male,african american,23.1,70,70-80,18-24,
+20231214,s1,douglas_hoffman,M,L,168,27,140,29,80,121,156,102,29,51,10,4,Female,caucasian,21.6,61,60-70,36-40,
+20231215,s0,jeffrey_king,L,XL,186,29,148,40,94,150,190,104,34,51,10,3,Male,caucasian,21.4,74,70-80,19-25,
+20231215,s1,dylan_lambert,M,M,159,25,132,35,79,128,162,95,31,46,10,5,Female,southeast asian,24.5,62,60-70,25-30,
+20231218,s0,roger_mcguire,XL,L,182,30,150,40,90,142,183,104,33,51,10,3,Male,caucasian,22.3,74,70-80,18-24,
+20231218,s1,kathryn_pruitt,L,XXL,188,30,158,41,98,153,194,117,34,52,10,2,Male,caucasian,20.9,74,70-80,18-24,
+20231219,s0,randall_love,L,XL,180,28,149,34,86,144,183,112,34,54,10,5,Female,caucasian,23.1,75,70-80,31-35,
+20231219,s1,erica_lee,L,L,172,27,145,30,85,141,180,102,30,47,11,3,Female,african american,23.3,71,70-80,25-30,
+20231220,s0,victor_sloan,L,XL,185,30,150,43,96,148,190,104,34,50,8,3,Male,caucasian,24.2,83,80-90,18-24,
+20231220,s1,amanda_wong,XL,XXL,191,30,154,43,91,146,187,106,34,51,9,3,Male,caucasian,24.6,90,90-100,31-35,
+20231221,s0,sara_wilson,L,L,180,28,145,42,88,144,178,108,33,48,8,3,Male,east asian,24.6,80,70-80,25-30,
+20231221,s1,edward_contreras,M,M,169,27,143,31,83,137,173,108,30,57,10,5,Female,south asian,24.9,71,70-80,25-30,
+20231222,s0,denise_carter,M,M,163,25,135,35,81,132,167,95,28,45,9,3,Female,east asian,18.4,49,45-50,25-30,
+20231222,s1,kenneth_fischer,M,L,172,27,139,37,85,139,173,94,30,47,8,3,Male,caucasian,19.6,58,50-60,31-35,

download.py

@@ -0,0 +1,76 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import sys
+from pathlib import Path
+
+import click
+from loguru import logger
+from nymeria.definitions import DataGroups
+from nymeria.download_utils import DownloadManager
+
+
+def get_groups(full: bool = False) -> list[DataGroups]:
+    """
+    By default all data present in nymeria_download_urls.json will be downloaded.
+    For selective download, comment out lines to disable certain groups.
+    See nymeria/definitions.py GroupDefs for the files included by each group.
+    """
+    return [
+        DataGroups.LICENSE,
+        DataGroups.metadata_json,
+        DataGroups.body,
+        DataGroups.recording_head,
+        DataGroups.recording_head_data_data_vrs,
+        DataGroups.recording_lwrist,
+        DataGroups.recording_rwrist,
+        DataGroups.recording_observer,
+        DataGroups.recording_observer_data_data_vrs,
+        DataGroups.narration_motion_narration_csv,
+        DataGroups.narration_atomic_action_csv,
+        DataGroups.narration_activity_summarization_csv,
+        DataGroups.semidense_observations,
+    ]
+
+
+@click.command()
+@click.option(
+    "-i",
+    "url_json",
+    type=click.Path(file_okay=True, dir_okay=False, path_type=Path),
+    default=None,
+    required=True,
+    help="The json file contains download urls. Follow README.md instructions to access this file.",
+)
+@click.option(
+    "-o",
+    "rootdir",
+    type=click.Path(file_okay=False, dir_okay=True, writable=True, path_type=Path),
+    default=None,
+    help="The root directory to hold the downloaded dataset",
+)
+@click.option(
+    "-k",
+    "match_key",
+    default="2023",
+    help="Partial key used to filter sequences for downloading"
+    "Default key value = 2023, which include all available sequences",
+)
+def main(url_json: Path, rootdir: Path, match_key: str = "2023") -> None:
+    logger.remove()
+    logger.add(
+        sys.stdout,
+        colorize=True,
+        format="<level>{level: <7}</level> <blue>{name}.py:</blue><green>{function}</green><yellow>:{line}</yellow> {message}",
+        level="INFO",
+    )
+
+    dl = DownloadManager(url_json, out_rootdir=rootdir)
+    dl.download(match_key=match_key, selected_groups=get_groups(), ignore_existing=True)
+
+
+if __name__ == "__main__":
+    main()

environment.yml

@@ -0,0 +1,17 @@
+name: pymeria
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - python=3.10
+  - numpy
+  - pillow
+  - click
+  - requests
+  - pymomentum
+  - tqdm
+  - pip
+  - pip:
+    - loguru
+    - projectaria-tools==1.5.5
+    - -e .

nymeria/__init__.py

@@ -0,0 +1,5 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.

nymeria/body_motion_provider.py

@@ -0,0 +1,227 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from pathlib import Path
+
+import numpy as np
+import pymomentum as pym
+import torch
+from loguru import logger
+from nymeria.xsens_constants import XSensConstants
+from projectaria_tools.core.sophus import SE3
+from pymomentum.geometry import Character, Mesh
+
+
+class BodyDataProvider:
+    _dt_norminal: float = 1.0e6 / 240.0
+    _dt_tolerance: int = 1000  # 1ms
+    _tcorrect_tolerance: int = 10_1000  # 10ms
+
+    # coordinates tranform between momentum and xsens
+    _A_Wx_Wm = torch.tensor([0.01, 0, 0, 0, 0, -0.01, 0, 0.01, 0]).reshape([3, 3])
+
+    def __init__(self, npzfile: str, glbfile: str) -> None:
+        if not Path(npzfile).is_file():
+            logger.error(f"{npzfile=} not found")
+            return
+
+        logger.info(f"loading xsens from {npzfile=}")
+        self.xsens_data: dict[str, np.ndarray] = dict(np.load(npzfile))
+        for k, v in self.xsens_data.items():
+            logger.info(f"{k=}, {v.shape=}")
+
+        self.__correct_timestamps()
+        self.__correct_quaternion()
+
+        # load glb if exist
+        self.character: Character = None
+        self.motion: np.ndarray = None
+        if Path(glbfile).is_file():
+            self.character, self.motion, _, fps = Character.load_gltf_with_motion(
+                glbfile
+            )
+            assert fps == self.xsens_data[XSensConstants.k_framerate]
+            assert self.motion.shape[0] == self.xsens_data[XSensConstants.k_frame_count]
+            assert self.character.has_mesh
+
+    @property
+    def momentum_template_mesh(self) -> Mesh | None:
+        if self.character is not None:
+            return self.character.mesh
+        else:
+            return None
+
+    def __correct_timestamps(self) -> None:
+        t_original = self.xsens_data[XSensConstants.k_timestamps_us]
+        dt_original = t_original[1:] - t_original[:-1]
+        invalid = np.abs(dt_original - self._dt_norminal) > self._dt_tolerance
+        num_invalid = invalid.sum()
+        percentage = num_invalid / t_original.size * 100.0
+        if num_invalid == 0:
+            return
+        logger.warning(f"number of invalid timestamps {num_invalid}, {percentage=}%")
+        dt_corrected = dt_original
+        dt_corrected[invalid] = int(self._dt_norminal)
+        dt_corrected = np.insert(dt_corrected, 0, 0)
+        t_corrected = t_original[0] + np.cumsum(dt_corrected)
+
+        t_diff = np.abs(t_corrected - t_original)
+        logger.info(f"after correct {t_diff[-1]= }us")
+        if t_diff[-1] > self._tcorrect_tolerance:
+            raise RuntimeError(f"corrected timestamps exceed tolerance {t_diff[-1]=}")
+
+        self.xsens_data[XSensConstants.k_timestamps_us] = t_corrected
+
+    def __correct_quaternion(self) -> None:
+        qWXYZ = self.xsens_data[XSensConstants.k_part_qWXYZ].reshape(
+            -1, XSensConstants.num_parts, 4
+        )
+        qn = np.linalg.norm(qWXYZ, axis=-1, keepdims=False)
+        invalid = qn < 0.1
+        if invalid.sum() == 0:
+            return
+        else:
+            logger.error(f"number of invalid quaternions {invalid.sum()}")
+
+        for p in range(XSensConstants.num_parts):
+            if qn[0, p] < 0.5:
+                qWXYZ[0, p] = np.array([1, 0, 0, 0])
+        for f in range(1, qn.shape[0]):
+            for p in range(XSensConstants.num_parts):
+                if qn[f, p] < 0.5:
+                    qWXYZ[f, p] = qWXYZ[f - 1, p]
+        self.xsens_data[XSensConstants.k_part_qWXYZ] = qWXYZ.reshape(
+            -1, XSensConstants.num_parts * 4
+        )
+
+    def get_global_timespan_us(self) -> tuple[int, int]:
+        t_us = self.xsens_data[XSensConstants.k_timestamps_us]
+        return t_us[0], t_us[-1]
+
+    def get_T_w_h(self, timespan_ns: tuple[int, int] = None) -> tuple[list, list]:
+        head_idx = XSensConstants.part_names.index("Head")
+        num_parts = XSensConstants.num_parts
+        timestamps_ns = self.xsens_data[XSensConstants.k_timestamps_us] * 1e3
+        if timespan_ns is not None:
+            t_start, t_end = timespan_ns
+            i_start = np.searchsorted(timestamps_ns, t_start) + 240
+            i_end = np.searchsorted(timestamps_ns, t_end) - 240
+            assert i_start < i_end
+        else:
+            i_start = 0
+            i_end = None
+
+        head_q = self.xsens_data[XSensConstants.k_part_qWXYZ].reshape(-1, num_parts, 4)[
+            i_start:i_end, head_idx, :
+        ]
+        head_t = self.xsens_data[XSensConstants.k_part_tXYZ].reshape(-1, num_parts, 3)[
+            i_start:i_end, head_idx, :
+        ]
+        T_w_h: list[SE3] = SE3.from_quat_and_translation(
+            head_q[:, 0], head_q[:, 1:], head_t
+        )
+        t_ns: list[int] = timestamps_ns[i_start:i_end].tolist()
+        logger.info(f"get {len(T_w_h)} samples for computing alignment")
+        return T_w_h, t_ns
+
+    def __get_closest_timestamp_idx(self, t_us: int) -> int:
+        if t_us <= self.get_global_timespan_us()[0]:
+            return 0
+        if t_us >= self.get_global_timespan_us()[-1]:
+            return -1
+
+        timestamps = self.xsens_data[XSensConstants.k_timestamps_us]
+        idx_rr = np.searchsorted(timestamps, t_us)
+        idx_ll = idx_rr - 1
+        if abs(timestamps[idx_ll] - t_us) < abs(timestamps[idx_rr] - t_us):
+            return idx_ll
+        else:
+            return idx_rr
+
+    def get_posed_skeleton_and_skin(
+        self, t_us: int, T_W_Hx: SE3 = None
+    ) -> tuple[np.ndarray, np.ndarray | None]:
+        """
+        \brief Given a query timestamp, return the closest body motion.
+        \arg t_us: query timestamp in microsecond.
+        \arg T_W_Hx: optional SE3 alignment from XSens head to world coordinates,
+             computed from XSens to Aria world coordinaes alignment.
+        \return First element is XSens posed skeleton. Second element is posed vertices
+                of momentum mesh if the momentum retargetted results are loaded.
+                We only return the posed mesh vertices, since the triangles and normals stay the same.
+        """
+        # find closest timestamp
+        idx: int = self.__get_closest_timestamp_idx(t_us)
+
+        # get XSens posed skeleton
+        q = self.xsens_data[XSensConstants.k_part_qWXYZ][idx]
+        t = self.xsens_data[XSensConstants.k_part_tXYZ][idx]
+        T_Wx_Px = BodyDataProvider.qt_to_se3(q, t)
+        T_W_Wx: SE3 = None
+        if T_W_Hx is not None:
+            head_idx = XSensConstants.part_names.index("Head")
+            T_Hx_Wx = T_Wx_Px[head_idx].inverse()
+            T_W_Wx = T_W_Hx @ T_Hx_Wx
+            T_W_Px = [T_W_Wx @ T_wx_px for T_wx_px in T_Wx_Px]
+            skel_xsens = BodyDataProvider.se3_to_skeleton(T_W_Px)
+        else:
+            skel_xsens = BodyDataProvider.se3_to_skeleton(T_Wx_Px)
+
+        # get Momentum posed mesh vertices
+        if self.character is not None:
+            motion = torch.tensor(self.motion[idx])
+            skel_state: torch.Tensor = pym.geometry.model_parameters_to_skeleton_state(
+                self.character, motion
+            )
+            skin_momentum: torch.Tensor = self.character.skin_points(skel_state)
+
+            if T_W_Wx is not None:
+                t_W_Wx = (
+                    torch.tensor(T_W_Wx.translation()).to(torch.float32).reshape([3, 1])
+                )
+                R_W_Wx = torch.tensor(T_W_Wx.rotation().to_matrix()).to(torch.float32)
+
+                R_W_Wm = R_W_Wx @ self._A_Wx_Wm
+                skin_momentum = (R_W_Wm @ skin_momentum.T + t_W_Wx).T
+            else:
+                skin_momentum = (self._A_Wx_Wm @ skin_momentum.T).T
+
+        return skel_xsens, skin_momentum
+
+    @staticmethod
+    def qt_to_se3(part_qWXYZ: np.ndarray, part_tXYZ: np.ndarray) -> list[SE3]:
+        """
+        \brief Helper function to convert a frame of skeleton representation from
+               list of quaternion + translation to SE3.
+        """
+        q_WXYZ = part_qWXYZ.reshape(XSensConstants.num_parts, 4)
+        t_XYZ = part_tXYZ.reshape(XSensConstants.num_parts, 3)
+        return SE3.from_quat_and_translation(q_WXYZ[:, 0], q_WXYZ[:, 1:], t_XYZ)
+
+    @staticmethod
+    def se3_to_skeleton(part_se3: list[SE3]) -> np.ndarray:
+        """
+        \brief Helper function to convert a frame of skeleton parameters to 3D wireframe
+               for visualization purposes.
+        """
+        assert len(part_se3) == XSensConstants.num_parts
+        children = np.concatenate([b.translation() for b in part_se3[1:]], axis=0)
+        parents = np.concatenate(
+            [part_se3[p].translation() for p in XSensConstants.kintree_parents[1:]],
+            axis=0,
+        )
+        skeleton_cp = np.stack([children, parents], axis=1)
+        assert skeleton_cp.shape == (XSensConstants.num_bones, 2, 3)
+        return skeleton_cp.astype(np.float32)
+
+
+def create_body_data_provider(
+    xdata_npz: str, xdata_glb: str
+) -> BodyDataProvider | None:
+    if Path(xdata_npz).is_file():
+        return BodyDataProvider(npzfile=xdata_npz, glbfile=xdata_glb)
+    else:
+        return None

nymeria/data_provider.py

@@ -0,0 +1,257 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from dataclasses import dataclass
+from pathlib import Path
+
+import numpy as np
+from loguru import logger
+from nymeria.body_motion_provider import create_body_data_provider
+from nymeria.handeye import HandEyeSolver
+from nymeria.path_provider import SequencePathProvider
+from nymeria.recording_data_provider import (
+    create_recording_data_provider,
+    RecordingDataProvider,
+)
+from projectaria_tools.core.mps import ClosedLoopTrajectoryPose
+from projectaria_tools.core.sensor_data import TimeDomain
+from projectaria_tools.core.sophus import SE3
+
+
+@dataclass(frozen=True)
+class NymeriaDataProviderConfig:
+    sequence_rootdir: Path
+    load_head: bool = True
+    load_observer: bool = True
+    load_wrist: bool = True
+    load_body: bool = True
+
+    # If true, the filtered semidense points are exported into a npz file at the first loading
+    view_cached_points: bool = True
+    # Parameters for filtering semidense points
+    th_invdep: float = 0.0004
+    th_dep: float = 0.02
+    max_point_count: int = 100_000
+
+    trajectory_sample_fps: float = 1
+
+    # Parameters for solving XSens to Aria world coordinates alignment
+    handeye_smooth: bool = False
+    handeye_window: int = 240 * 120
+    handeye_skip: int = 240 * 5
+    handeye_stride: int = 2
+
+
+class NymeriaDataProvider(NymeriaDataProviderConfig):
+    def __init__(self, **kwargs) -> None:
+        super().__init__(**kwargs)
+
+        seq_pd = SequencePathProvider(self.sequence_rootdir)
+
+        # create data provider for Aria recordings and MPS output
+        self.recording_head = (
+            create_recording_data_provider(seq_pd.recording_head)
+            if self.load_head
+            else None
+        )
+        self.recording_lwrist = (
+            create_recording_data_provider(seq_pd.recording_lwrist)
+            if self.load_wrist
+            else None
+        )
+        self.recording_rwrist = (
+            create_recording_data_provider(seq_pd.recording_rwrist)
+            if self.load_wrist
+            else None
+        )
+        self.recording_observer = (
+            create_recording_data_provider(seq_pd.recording_observer)
+            if self.load_observer
+            else None
+        )
+
+        # create data provider for body motion
+        self.body_dp = (
+            create_body_data_provider(
+                xdata_npz=seq_pd.body_paths.xsens_processed,
+                xdata_glb=seq_pd.body_paths.momentum_model,
+            )
+            if self.load_body
+            else None
+        )
+
+        if self.body_dp is None and len(self.get_existing_recordings()) == 0:
+            raise RuntimeError(
+                "data provider is empty. "
+                "Make sure there is at least 1 recording or body motion"
+            )
+
+        # get overlapping timeline
+        self.timespan_ns: tuple[int, int] = self.__get_timespan_ns()
+
+        # compute xsens to aria world alignment
+        self.__compute_xsens_to_aria_alignment()
+
+    def get_existing_recordings(self) -> list[RecordingDataProvider]:
+        return [
+            x
+            for x in [
+                self.recording_head,
+                self.recording_observer,
+                self.recording_lwrist,
+                self.recording_rwrist,
+            ]
+            if x is not None
+        ]
+
+    def __get_timespan_ns(self, ignore_ns: int = 1e9) -> tuple[int, int]:
+        """
+        \brief Compute overlapping timeline across all loaded data
+        """
+        t_start = 0
+        t_end = None
+        if self.body_dp is not None:
+            t0, t1 = self.body_dp.get_global_timespan_us()
+            t_start = t0 * 1e3
+            t_end = t1 * 1e3
+
+        for rec in self.get_existing_recordings():
+            t0, t1 = rec.get_global_timespan_ns()
+            t_start = t_start if t_start > t0 else t0
+            t_end = t_end if t_end is None or t_end < t1 else t1
+
+        t_start += ignore_ns
+        t_end -= ignore_ns
+        assert t_start < t_end, f"invalid time span {t_start= }us, {t_end= }us"
+
+        t_start = int(t_start)
+        t_end = int(t_end)
+        duration = (t_end - t_start) / 1.0e9
+        logger.info(f"time span: {t_start= }us {t_end= }us {duration= }s")
+        return t_start, t_end
+
+    def get_synced_rgb_videos(self, t_ns_global: int) -> dict[str, any]:
+        data = {}
+        for rec in [self.recording_head, self.recording_observer]:
+            if rec is None and not rec.has_rgb:
+                continue
+
+            result = rec.get_rgb_image(t_ns_global, time_domain=TimeDomain.TIME_CODE)
+            if abs(result[-1] / 1e6) > 33:  # 33ms
+                logger.warning(f"time difference for image query: {result[-1]} ms")
+            data[rec.tag] = result
+        return data
+
+    def get_all_pointclouds(self) -> dict[str, np.ndarray]:
+        data = {}
+        for rec in self.get_existing_recordings():
+            if not rec.has_pointcloud:
+                continue
+
+            if self.view_cached_points:
+                data[rec.tag] = rec.get_pointcloud_cached(
+                    th_dep=self.th_dep,
+                    th_invdep=self.th_invdep,
+                    max_point_count=self.max_point_count,
+                )
+            else:
+                data[rec.tag] = rec.get_pointcloud(
+                    th_dep=self.th_dep,
+                    th_invdep=self.th_invdep,
+                    max_point_count=self.max_point_count,
+                )
+        return data
+
+    def get_all_trajectories(self) -> dict[str, np.ndarray]:
+        data = {}
+        for rec in self.get_existing_recordings():
+            if rec.has_vrs and rec.has_pose:
+                data[rec.tag] = rec.sample_trajectory_world_device(
+                    sample_fps=self.trajectory_sample_fps
+                )
+        return data
+
+    def get_synced_poses(self, t_ns_global: int) -> dict[str, any]:
+        data = {}
+        T_Wd_Hd = None
+        for rec in self.get_existing_recordings():
+            if rec is None or not rec.has_pose:
+                continue
+
+            pose: ClosedLoopTrajectoryPose = None
+            tdiff: int = None
+            pose, tdiff = rec.get_pose(t_ns_global, time_domain=TimeDomain.TIME_CODE)
+            if abs(tdiff / 1e6) > 2:  # 2ms
+                logger.warning(f"time difference for pose query {tdiff/1e6} ms")
+
+            data[rec.tag] = pose
+            if rec.tag == "recording_head":
+                T_Wd_Hd: SE3 = pose.transform_world_device
+
+        if (
+            self.body_dp is not None
+            and self.recording_head is not None
+            and T_Wd_Hd is not None
+        ):
+            T_Wd_Hx = T_Wd_Hd @ self.T_Hd_Hx(t_ns_global)
+            t_us = t_ns_global / 1e3
+            skel, skin = self.body_dp.get_posed_skeleton_and_skin(t_us, T_W_Hx=T_Wd_Hx)
+            data["xsens"] = skel
+            if skin is not None:
+                data["momentum"] = skin
+        return data
+
+    def __compute_xsens_to_aria_alignment(self) -> None:
+        """
+        \brief Compute se3 transform from xsens head to aria head
+               This function will set self.Ts_Hd_Hx and self.t_ns_align
+        """
+        if self.recording_head is None or self.body_dp is None:
+            self.Ts_Hd_Hx = [SE3.from_matrix(np.eye(4))]
+            self.t_ns_align = None
+            return
+        else:
+            logger.info("compute alignment from xsens head to aria headset")
+            assert self.body_dp is not None
+            assert self.recording_head is not None
+
+        # get synchronized trajectory
+        xsens_traj = self.body_dp.get_T_w_h(self.timespan_ns)
+        T_Wx_Hx: list[SE3] = xsens_traj[0]
+        t_ns: list[int] = xsens_traj[-1]
+        T_Wd_Hd: list[SE3] = []
+        for t in t_ns:
+            pose, _ = self.recording_head.get_pose(t, TimeDomain.TIME_CODE)
+            T_Wd_Hd.append(pose.transform_world_device)
+
+        # solve handeye
+        handeye = HandEyeSolver(
+            stride=self.handeye_stride,
+            smooth=self.handeye_smooth,
+            skip=self.handeye_skip,
+            window=self.handeye_window,
+        )
+        self.Ts_Hd_Hx: list[SE3] = handeye(
+            T_Wa_A=T_Wd_Hd,
+            T_Wb_B=T_Wx_Hx,
+        )
+        if len(self.Ts_Hd_Hx) > 1:
+            self.t_ns_align = t_ns[0 :: self.handeye_skip]
+        else:
+            self.t_ns_align = None
+
+    def T_Hd_Hx(self, t_ns: int) -> SE3:
+        if self.t_ns_align is None:
+            return self.Ts_Hd_Hx[0]
+
+        if t_ns <= self.t_ns_align[0]:
+            return self.Ts_Hd_Hx[0]
+
+        if t_ns >= self.t_ns_align[-1]:
+            return self.Ts_Hd_Hx[-1]
+
+        idx = np.searchsorted(self.t_ns_align, t_ns)
+        return self.Ts_Hd_Hx[idx]

nymeria/data_viewer.py

@@ -0,0 +1,237 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from collections import deque
+from dataclasses import dataclass
+from pathlib import Path
+from uuid import uuid4
+
+import numpy as np
+import rerun as rr
+import rerun.blueprint as rrb
+from loguru import logger
+from nymeria.data_provider import NymeriaDataProvider
+from PIL import Image
+from projectaria_tools.core.sensor_data import ImageData
+from projectaria_tools.core.sophus import SE3
+from tqdm import tqdm
+
+
+@dataclass(frozen=True)
+class ViewerConfig:
+    output_rrd: Path = None
+    sample_fps: float = 10
+    rotate_rgb: bool = True
+    downsample_rgb: bool = True
+    jpeg_quality: int = 90
+    traj_tail_length: int = 100
+
+    ep_recording_head: str = "recording_head/2d"
+    ep_recording_observer: str = "recording_observer/2d"
+
+    point_radii: float = 0.008
+    line_radii: float = 0.008
+    skel_radii: float = 0.01
+
+
+class NymeriaViewer(ViewerConfig):
+    palette: dict[str, list] = {
+        "recording_head": [255, 0, 0],
+        "recording_lwrist": [0, 255, 0],
+        "recording_rwrist": [0, 0, 255],
+        "recording_observer": [61, 0, 118],
+        "pointcloud": [128, 128, 128, 128],
+        "momentum": [218, 234, 134],
+    }
+    color_skeleton = np.array(
+        [
+            [127, 0, 255],
+            [105, 34, 254],
+            [81, 71, 252],
+            [59, 103, 249],
+            [35, 136, 244],
+            [11, 167, 238],
+            [10, 191, 232],
+            [34, 214, 223],
+            [58, 232, 214],
+            [80, 244, 204],
+            [104, 252, 192],
+            [128, 254, 179],
+            [150, 252, 167],
+            [174, 244, 152],
+            [196, 232, 138],
+            [220, 214, 122],
+            [244, 191, 105],
+            [255, 167, 89],
+            [255, 136, 71],
+            [255, 103, 53],
+            [255, 71, 36],
+            [255, 34, 17],
+        ]
+    )
+
+    def __init__(self, **kwargs) -> None:
+        super().__init__(**kwargs)
+
+        blueprint = rrb.Horizontal(
+            rrb.Spatial3DView(name="3d"),
+            rrb.Vertical(
+                rrb.Spatial2DView(name="2d participant", origin=self.ep_recording_head),
+                rrb.Spatial2DView(
+                    name="2d observer", origin=self.ep_recording_observer
+                ),
+            ),
+        )
+
+        rr.init(
+            "nymeria data viewer",
+            spawn=(self.output_rrd is None),
+            recording_id=uuid4(),
+            default_blueprint=blueprint,
+        )
+        if self.output_rrd is not None:
+            rr.save(self.output_rrd)
+
+        rr.log("world", rr.ViewCoordinates.RIGHT_HAND_Z_UP, static=True)
+
+        self._init_mesh: bool = False
+        self._epaths_3d: set[str] = set()
+        self._traj_deques: dict[str, deque] = {}
+
+    def __call__(self, nymeria_dp: NymeriaDataProvider):
+        # add static scene
+        self.__log_pointcloud(nymeria_dp)
+        self.__log_trajectory(nymeria_dp)
+
+        # add dynamic scene
+        t_ns_start, t_ns_end = nymeria_dp.timespan_ns
+        dt: int = int(1e9 / self.sample_fps)
+        for idx, t_ns in tqdm(enumerate(range(t_ns_start, t_ns_end, dt))):
+            rr.set_time_sequence("frames", idx)
+            rr.set_time_nanos("timestamps_ns", t_ns)
+
+            self.__log_synced_video(t_ns, nymeria_dp)
+            self.__log_synced_poses(t_ns, nymeria_dp)
+
+            self.__set_viewpoint()
+
+    def __log_pointcloud(self, nymeria_dp: NymeriaDataProvider) -> None:
+        pointclouds = nymeria_dp.get_all_pointclouds()
+        for tag, pts in pointclouds.items():
+            logger.info(f"add point cloud {tag}")
+            cc = self.palette.get("pointcloud")
+            ep = f"world/semidense_pts/{tag}"
+            rr.log(
+                entity_path=ep,
+                entity=rr.Points3D(pts, colors=cc, radii=self.point_radii),
+                static=True,
+            )
+            self._epaths_3d.add(ep)
+
+    def __log_trajectory(self, nymeria_dp: NymeriaDataProvider) -> None:
+        trajs: dict[str, np.ndarray] = nymeria_dp.get_all_trajectories()
+        for tag, traj in trajs.items():
+            logger.info(f"add trajectory {tag}, {traj.shape=}")
+            ep = f"world/traj_full/{tag}"
+            rr.log(
+                ep,
+                rr.LineStrips3D(
+                    traj[:, :3, 3], colors=self.palette.get(tag), radii=self.line_radii
+                ),
+                static=True,
+            )
+            self._epaths_3d.add(ep)
+
+    def __log_synced_video(self, t_ns: int, nymeria_dp: NymeriaDataProvider) -> None:
+        images: dict[str, tuple] = nymeria_dp.get_synced_rgb_videos(t_ns)
+        for tag, data in images.items():
+            rgb: ImageData = data[0]
+
+            if self.downsample_rgb:
+                rgb = rgb.to_numpy_array()[::2, ::2, :]
+            rgb = Image.fromarray(rgb.astype(np.uint8))
+            if self.rotate_rgb:
+                rgb = rgb.rotate(-90)
+
+            if tag in self.ep_recording_head:
+                ep = self.ep_recording_head
+            elif tag in self.ep_recording_observer:
+                ep = self.ep_recording_observer
+            rr.log(
+                f"{ep}/214-1", rr.Image(rgb).compress(jpeg_quality=self.jpeg_quality)
+            )
+
+    def __log_synced_poses(self, t_ns: int, nymeria_dp: NymeriaDataProvider) -> None:
+        poses: dict[str, any] = nymeria_dp.get_synced_poses(t_ns)
+
+        self._T_mv: SE3 = None
+        for tag, val in poses.items():
+            if "recording" in tag and self.traj_tail_length > 0:
+                traj = self._traj_deques.setdefault(tag, deque())
+                if self.traj_tail_length > 0 and len(traj) == self.traj_tail_length:
+                    traj.popleft()
+                t = val.transform_world_device.translation()
+                traj.append(t.squeeze().tolist())
+                ep = f"world/traj_tail/{tag}"
+                rr.log(
+                    ep,
+                    rr.LineStrips3D(
+                        traj, colors=self.palette.get(tag), radii=self.line_radii
+                    ),
+                )
+                self._epaths_3d.add(ep)
+
+            if tag == "xsens":
+                ep = "world/body/xsens_skel"
+                logger.debug(f"xsens skeleton {val.shape = }")
+                rr.log(
+                    ep,
+                    rr.LineStrips3D(
+                        val, colors=self.color_skeleton, radii=self.skel_radii
+                    ),
+                    static=False,
+                )
+                self._epaths_3d.add(ep)
+            if tag == "momentum":
+                ep = "world/body/momentum_mesh"
+                if self._init_mesh:
+                    rr.log_components(ep, [rr.components.Position3DBatch(val)])
+                else:
+                    faces = nymeria_dp.body_dp.momentum_template_mesh.faces
+                    normals = nymeria_dp.body_dp.momentum_template_mesh.normals
+                    rr.log(
+                        ep,
+                        rr.Mesh3D(
+                            triangle_indices=faces,
+                            vertex_positions=val,
+                            vertex_normals=normals,
+                            vertex_colors=self.palette.get(tag),
+                        ),
+                    )
+                    self._init_mesh = True
+                self._epaths_3d.add(ep)
+
+            if tag == "recording_head":
+                self._T_mv = val.transform_world_device
+
+    def __set_viewpoint(self, add_rotation: bool = False):
+        if self._T_mv is None:
+            return
+        t = self._T_mv.translation() * -1.0
+        Rz = np.eye(3)
+        if add_rotation:
+            R = self._T_mv.rotation().to_matrix()
+            psi = np.arctan2(R[1, 0], R[0, 0])
+            Rz[0:2, 0:2] = np.array(
+                [np.cos(psi), -np.sin(psi), np.sin(psi), np.cos(psi)]
+            ).reshape(2, 2)
+
+        for ep in self._epaths_3d:
+            rr.log(
+                ep,
+                rr.Transform3D(translation=t, mat3x3=Rz),
+                static=False,
+            )

nymeria/definitions.py

@@ -0,0 +1,182 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import json
+from dataclasses import dataclass, fields
+from enum import Enum
+
+"""
+Each sequence folder follows the following structure.
+Files might be missing if not downloaded. 
+  ├── LICENSE 
+  ├── metadata.json
+  ├── body
+  │   ├── xdata_blueman.glb
+  │   ├── xdata.healthcheck
+  │   ├── xdata.mvnx
+  │   └── xdata.npz
+  ├── narration
+  │   ├── activity_summarization.csv
+  │   ├── atomic_action.csv
+  │   └── motion_narration.csv
+  ├── recording_head / recording_observer
+  │   ├── data
+  │   │   ├── data.vrs
+  │   │   ├── et.vrs
+  │   │   └── motion.vrs
+  │   └── mps
+  │       ├── eye_gaze
+  │       │   ├── general_eye_gaze.csv
+  │       │   └── personalized_eye_gaze.csv
+  │       └── slam
+  │           ├── closed_loop_trajectory.csv
+  │           ├── online_calibration.jsonl
+  │           ├── open_loop_trajectory.csv
+  │           ├── semidense_observations.csv.gz
+  │           ├── semidense_points.csv.gz
+  │           └── summary.json
+  └── recording_rwrist / recording_lwrist
+      ├── data
+      │   ├── data.vrs
+      │   └── motion.vrs
+      └── mps
+          └── slam
+              ├── closed_loop_trajectory.csv
+              ├── online_calibration.jsonl
+              ├── open_loop_trajectory.csv
+              ├── semidense_observations.csv.gz
+              ├── semidense_points.csv.gz
+              └── summary.json
+
+"""
+
+NYMERIA_VERSION: str = "v0.0"
+
+
+@dataclass(frozen=True)
+class MetaFiles:
+    license: str = "LICENSE"
+    metadata_json: str = "metadata.json"
+
+
+@dataclass(frozen=True)
+class Subpaths(MetaFiles):
+    body: str = "body"
+    text: str = "narration"
+
+    recording_head: str = "recording_head"
+    recording_lwrist: str = "recording_lwrist"
+    recording_rwrist: str = "recording_rwrist"
+    recording_observer: str = "recording_observer"
+
+    vrs: str = "data"
+    mps: str = "mps"
+    mps_slam: str = "mps/slam"
+    mps_gaze: str = "mps/eye_gaze"
+
+
+@dataclass(frozen=True)
+class BodyFiles:
+    xsens_processed: str = f"{Subpaths.body}/xdata.npz"
+    xsens_raw: str = f"{Subpaths.body}/xdata.mvnx"
+    momentum_model: str = f"{Subpaths.body}/xdata_blueman.glb"
+
+
+@dataclass(frozen=True)
+class TextFiles:
+    motion_narration: str = f"{Subpaths.text}/motion_narration.csv"
+    atomic_action: str = f"{Subpaths.text}/atomic_action.csv"
+    activity_summarization: str = f"{Subpaths.text}/activity_summarization.csv"
+
+
+@dataclass(frozen=True)
+class VrsFiles:
+    data: str = f"{Subpaths.vrs}/data.vrs"
+    motion: str = f"{Subpaths.vrs}/motion.vrs"
+    et: str = f"{Subpaths.vrs}/et.vrs"
+
+
+@dataclass(frozen=True)
+class SlamFiles:
+    closed_loop_trajectory: str = f"{Subpaths.mps_slam}/closed_loop_trajectory.csv"
+    online_calibration: str = f"{Subpaths.mps_slam}/online_calibration.jsonl"
+    open_loop_trajectory: str = f"{Subpaths.mps_slam}/open_loop_trajectory.csv"
+    semidense_points: str = f"{Subpaths.mps_slam}/semidense_points.csv.gz"
+    semidense_observations: str = f"{Subpaths.mps_slam}/semidense_observations.csv.gz"
+    location_summary: str = f"{Subpaths.mps_slam}/summary.json"
+
+
+@dataclass(frozen=True)
+class GazeFiles:
+    general_gaze: str = f"{Subpaths.mps_gaze}/general_eye_gaze.csv"
+    personalized_gaze: str = f"{Subpaths.mps_gaze}/personalized_eye_gaze.csv"
+
+
+class DataGroups(Enum):
+    """
+    \brief Each variable defines one atomic downloadable element
+    """
+
+    LICENSE = Subpaths.license
+    metadata_json = Subpaths.metadata_json
+
+    body = Subpaths.body
+
+    recording_head = Subpaths.recording_head
+    recording_head_data_data_vrs = f"{Subpaths.recording_head}/{VrsFiles.data}"
+    recording_lwrist = Subpaths.recording_lwrist
+    recording_rwrist = Subpaths.recording_rwrist
+    recording_observer = Subpaths.recording_observer
+    recording_observer_data_data_vrs = f"{Subpaths.recording_observer}/{VrsFiles.data}"
+
+    narration_motion_narration_csv = TextFiles.motion_narration
+    narration_atomic_action_csv = TextFiles.atomic_action
+    narration_activity_summarization_csv = TextFiles.activity_summarization
+
+    semidense_observations = "semidense_observations"
+
+
+def get_group_definitions() -> dict[str, list]:
+    """
+    \brief Definition of DataGroups
+           File paths are relative with respect to each sequence folder.
+           Some sequences might missing certain files/data groups
+           due to errors occured from data collection or processing.
+           There is one url per data group per sequence.
+           Data groups with multiple files are packed into zip files.
+    """
+    AriaFiles = (
+        [f.default for f in fields(VrsFiles) if "data" not in f.name]
+        + [f.default for f in fields(SlamFiles) if "observations" not in f.name]
+        + [f.default for f in fields(GazeFiles)]
+    )
+    miniAriaFiles = [f.default for f in fields(VrsFiles) if "et" not in f.name] + [
+        f.default for f in fields(SlamFiles) if "observerations" not in f.name
+    ]
+
+    g_defs = {x.name: [x.value] for x in DataGroups}
+    g_defs[DataGroups.body.name] = [x.default for x in fields(BodyFiles)]
+
+    for x in [DataGroups.recording_head, DataGroups.recording_observer]:
+        g_defs[x.name] = [f"{x.name}/{f}" for f in AriaFiles]
+
+    for x in [DataGroups.recording_rwrist, DataGroups.recording_lwrist]:
+        g_defs[x.name] = [f"{x.name}/{f}" for f in miniAriaFiles]
+
+    g_defs[DataGroups.semidense_observations.name] = []
+    for x in fields(Subpaths):
+        if "recording" in x.name:
+            g_defs[DataGroups.semidense_observations.name].append(
+                f"{x.default}/{SlamFiles.semidense_observations}"
+            )
+
+    print("=== group definitions (group_name: [group_files]) ===")
+    print(json.dumps(g_defs, indent=2))
+
+    return g_defs
+
+
+# get_group_definitions()

nymeria/download_utils.py

@@ -0,0 +1,289 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import hashlib
+import json
+import shutil
+import tempfile
+from dataclasses import dataclass
+from enum import Enum
+from pathlib import Path
+from zipfile import is_zipfile, ZipFile
+
+import requests
+from loguru import logger
+from requests.adapters import HTTPAdapter
+from requests.packages.urllib3.util.retry import Retry
+from tqdm import tqdm
+
+from .definitions import DataGroups, NYMERIA_VERSION
+
+
+class DlConfig(Enum):
+    CHUCK_SIZE_BYTE = 8192
+    READ_BYTE = 4096
+    RETRY = 5
+    BACKOFF_FACTOR = 3
+
+
+class DlStatus(Enum):
+    UNKNOWN = None
+    SUCCESS = "success"
+    IGNORED = "ignored, file already downloaded"
+    WARN_NOTFOUND = "warning, missing download link"
+    ERR_SHA1SUM = "error, sha1sum mismatch"
+    ERR_MEMORY = "error, insufficient disk space"
+    ERR_NETWORK = "error, network"
+
+
+@dataclass
+class DlLink:
+    filename: str
+    sha1sum: str
+    file_size_bytes: int
+    download_url: str
+
+    data_group: DataGroups
+    status: DlStatus = DlStatus.UNKNOWN
+
+    def __post_init__(self) -> None:
+        prefix = f"Nymeria_{NYMERIA_VERSION}_"
+        if prefix not in self.filename:
+            self.status = (
+                f"Version mismatch with the release {NYMERIA_VERSION}. "
+                f"Please download the latest url json"
+            )
+            raise ValueError(self.status)
+        self.filename = self.filename.replace(prefix, "")
+
+    @property
+    def seq_name(self) -> str:
+        return "_".join(self.filename.split("_")[0:6])
+
+    @property
+    def logdir(self) -> str:
+        return "logs"
+
+    def __check_outdir(self, outdir: Path) -> None:
+        assert (
+            outdir.name == self.seq_name
+        ), f"Output directory name ({outdir.name}) mismatch with sequence {self.seq_name}"
+        outdir.mkdir(exist_ok=True)
+
+    def get(self, outdir: Path, ignore_existing: bool = True) -> None:
+        """This function throws error if not successful"""
+        flag = outdir / self.logdir / self.data_group.name
+        if flag.is_file() and ignore_existing:
+            self.status = DlStatus.IGNORED
+            return
+
+        self.__check_outdir(outdir)
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            tmp_filename = Path(tmpdir) / self.filename
+            logger.info(f"Download {self.filename} -> {tmp_filename}")
+
+            session = requests.Session()
+            """
+            Retry will be triggered for the following cases
+            (429) Too Many Requests
+            (500) Internal Server Error
+            (502) Bad Gateway
+            (503) Service Unavailable
+            (504) Gateway Timeout
+            """
+            retries = Retry(
+                total=DlConfig.RETRY.value,
+                backoff_factor=DlConfig.BACKOFF_FACTOR.value,
+                status_forcelist=[429, 500, 502, 503, 504],
+            )
+
+            session.mount("https://", HTTPAdapter(max_retries=retries))
+            with session.get(self.download_url, stream=True) as r:
+
+                free_outdir = shutil.disk_usage(outdir).free
+                free_tmpdir = shutil.disk_usage(tmpdir).free
+                if (
+                    free_outdir < self.file_size_bytes
+                    or free_tmpdir < self.file_size_bytes
+                ):
+                    self.status = DlStatus.ERR_MEMORY
+                    raise RuntimeError(
+                        "Insufficient disk space. "
+                        f"Require {self.file_size_bytes}B, "
+                        f"tmpdir availabel {free_tmpdir}B, outdir available {free_outdir}B"
+                    )
+
+                with open(tmp_filename, "wb") as f:
+                    sha1 = hashlib.sha1()
+                    progress_bar = tqdm(
+                        total=self.file_size_bytes, unit="iB", unit_scale=True
+                    )
+                    for chunk in r.iter_content(
+                        chunk_size=DlConfig.CHUCK_SIZE_BYTE.value
+                    ):
+                        progress_bar.update(len(chunk))
+                        f.write(chunk)
+                        sha1.update(chunk)
+                    computed = sha1.hexdigest()
+                    if self.sha1sum != computed:
+                        self.status = DlStatus.ERR_SHA1SUM
+                        raise RuntimeError(
+                            f"sha1sum mismatch, computed {computed}, expected {self.sha1sum}"
+                        )
+                    progress_bar.close()
+
+                try:
+                    r.raise_for_status()
+                except Exception as e:
+                    self.status = DlStatus.ERR_NETWORK
+                    raise RuntimeError(e)
+
+            # move from tmp -> dst
+            if is_zipfile(tmp_filename):
+                logger.info("unzip")
+                with ZipFile(tmp_filename) as zf:
+                    zf.extractall(outdir)
+            else:
+                dst_file = outdir / self.data_group.value
+                dst_file.parent.mkdir(exist_ok=True, parents=True)
+                shutil.move(src=tmp_filename, dst=dst_file)
+
+        logger.info(f"Download {self.filename} -> {outdir}")
+        self.status = DlStatus.SUCCESS
+
+        # create a flag
+        flag.parent.mkdir(exist_ok=True)
+        flag.touch()
+
+
+class DownloadManager:
+    def __init__(self, url_json: Path, out_rootdir: Path) -> None:
+        self.url_json = url_json
+        assert self.url_json.is_file(), f"{self.url_json} not found"
+
+        self.out_rootdir = out_rootdir
+        self.out_rootdir.mkdir(exist_ok=True)
+
+        with open(self.url_json, "r") as f:
+            data = json.load(f)
+            self._sequences = data.get("sequences", {})
+            assert len(
+                self._sequences
+            ), "No sequence found. Please check the json file is correct."
+        self.__get_data_summary()
+        self._logs = {}
+
+    @property
+    def sequences(self) -> dict[str, any]:
+        return self._sequences
+
+    @property
+    def logfile(self) -> Path:
+        return self.out_rootdir / "download_summary.json"
+
+    def __get_data_summary(self):
+        missing = {x.name: {"count": 0, "sequences": []} for x in DataGroups}
+        for seq, dgs in self.sequences.items():
+            for dg in DataGroups:
+                if dg.name not in dgs:
+                    missing[dg.name]["count"] += 1
+                    missing[dg.name]["sequences"].append(seq)
+        fname = self.logfile.with_name("data_summary.json")
+        with open(fname, "w") as f:
+            json.dump(
+                {
+                    "missing_files": missing,
+                    "available_sequences": list(self.sequences.keys()),
+                },
+                f,
+                indent=2,
+            )
+        logger.info(f"save data summary to {fname}")
+
+    def __prepare(
+        self,
+        match_key: str,
+        selected_groups: list["DataGroups"],
+    ) -> set["DataGroups"]:
+        selected_groups += [DataGroups.LICENSE, DataGroups.metadata_json]
+        selected_groups = set(selected_groups)
+
+        num_seqs = 0
+        total_gb = 0
+        self._logs = {}
+
+        for seq, dgs in self.sequences.items():
+            if match_key not in seq:
+                continue
+
+            num_seqs += 1
+            self._logs[seq] = {}
+            for dg in selected_groups:
+                if dg.name not in dgs:
+                    self._logs[seq][dg.name] = DlStatus.WARN_NOTFOUND.value
+                else:
+                    self._logs[seq][dg.name] = None
+                    dl = DlLink(**{**dgs.get(dg.name, {}), "data_group": dg})
+                    total_gb += dl.file_size_bytes / (2**30)
+
+        # populate confirmation msg
+        msg = "\t" + "\n\t".join([x.value for x in selected_groups])
+        free_disk_gb = shutil.disk_usage(self.out_rootdir).free / (2**30)
+        confirm = (
+            input(
+                f"Download summary\n"
+                f"  Output rootdir: {self.out_rootdir}\n"
+                f"  Number sequences: {num_seqs}\n"
+                f"  Total memory (GB): {total_gb}\n"
+                f"  Available free disk space (GB): {free_disk_gb}\n"
+                f"  Selected data groups:\n{msg}\n"
+                f"Proceed: [y/n] "
+            ).lower()
+            == "y"
+        )
+        if not confirm:
+            exit(1)
+        return selected_groups
+
+    def __logging(self, **kwargs) -> None:
+        self._logs.update(**kwargs)
+
+        with open(self.logfile, "w") as f:
+            json.dump(self._logs, f, indent=2)
+
+    def download(
+        self,
+        match_key: str,
+        selected_groups: list["DataGroups"],
+        ignore_existing: bool = True,
+    ) -> None:
+        selected_groups = self.__prepare(match_key, selected_groups)
+
+        summary = {x.name: 0 for x in DlStatus}
+        for seq_name, dgs in self.sequences.items():
+            if match_key not in seq_name:
+                continue
+
+            outdir = self.out_rootdir / seq_name
+            for dg in selected_groups:
+                if dg.name not in dgs:
+                    continue
+
+                dl = DlLink(**{**dgs[dg.name], "data_group": dg})
+                try:
+                    dl.get(outdir, ignore_existing=ignore_existing)
+                except Exception as e:
+                    logger.error(f"downloading failure:, {e}")
+
+                summary[dl.status.name] += 1
+                self._logs[dl.seq_name][dl.data_group.name] = dl.status.value
+                self.__logging()
+
+        self.__logging(download_summary=summary)
+        logger.info(f"Dataset download to {self.out_rootdir}")
+        logger.info(f"Brief download summary: {json.dumps(summary, indent=2)}")
+        logger.info(f"Detailed summary saved to {self.logfile}")

nymeria/handeye.py

@@ -0,0 +1,91 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import numpy as np
+from loguru import logger
+from projectaria_tools.core.sophus import SE3
+
+
+class HandEyeSolver:
+    def __init__(self, smooth: bool, window: int, skip: int = 240, stride: int = 1):
+        self.stride = int(stride)
+        self.smooth = smooth
+        self.skip = int(skip)
+        self.window = int(window)
+        if self.window < 240:
+            self.smooth = False
+
+    def so3xR3(self, T_Wa_A: list[SE3], T_Wb_B: list[SE3]) -> SE3:
+        """
+        \return T_A_B using so3xR3 SVD decomposition.
+        """
+        assert len(T_Wa_A) == len(T_Wb_B)
+
+        N = len(T_Wa_A) - self.stride
+        se3_A1_A2 = [T_Wa_A[i].inverse() @ T_Wa_A[i + self.stride] for i in range(N)]
+        se3_B1_B2 = [T_Wb_B[i].inverse() @ T_Wb_B[i + self.stride] for i in range(N)]
+
+        # solve for R
+        log_A1_A2 = [x.rotation().log() for x in se3_A1_A2]
+        log_B1_B2 = [x.rotation().log() for x in se3_B1_B2]
+        A = np.stack(log_A1_A2, axis=-1).squeeze()
+        B = np.stack(log_B1_B2, axis=-1).squeeze()
+        logger.debug(f"{A.shape=}, {B.shape=}")
+
+        matrixU, S, matrixVh = np.linalg.svd(
+            B @ A.transpose(), full_matrices=True, compute_uv=True
+        )
+        logger.debug(f"{matrixU.shape=}, {S.shape=}, {matrixVh.shape=}")
+
+        RX = matrixVh @ matrixU.transpose()
+        if np.linalg.det(RX) < 0:
+            RX[2, :] = RX[2, :] * -1.0
+
+        # solve for t
+        jacobian = [x.rotation().to_matrix() - np.eye(3) for x in se3_A1_A2]
+        jacobian = np.concatenate(jacobian, axis=0)
+        assert jacobian.shape == (N * 3, 3)
+        logger.debug(f"{jacobian.shape=}")
+        residual = [
+            RX @ b.translation().reshape(3, 1) - a.translation().reshape(3, 1)
+            for a, b in zip(se3_A1_A2, se3_B1_B2)
+        ]
+        residual = np.concatenate(residual, axis=0)
+        assert residual.shape == (N * 3, 1)
+        logger.debug(f"{residual.shape=}")
+        JTJ = jacobian.T @ jacobian
+        JTr = jacobian.T @ residual
+        tX = np.linalg.lstsq(JTJ, JTr, rcond=None)[0]
+
+        T_A_B = np.ndarray([3, 4])
+        T_A_B[:3, :3] = RX
+        T_A_B[:3, 3] = tX.squeeze()
+        logger.debug(f"{T_A_B=}\n")
+        T_A_B = SE3.from_matrix3x4(T_A_B)
+        return T_A_B
+
+    def __call__(self, T_Wa_A: list[SE3], T_Wb_B: list[SE3]) -> list[SE3]:
+        N = len(T_Wa_A)
+        assert N == len(T_Wb_B)
+        if self.window >= N or not self.smooth:
+            T_A_B = self.so3xR3(T_Wa_A, T_Wb_B)
+            return [T_A_B]
+
+        Ts_A_B = []
+        for i in range(0, N, self.skip):
+            istart = int(i - self.window / 2)
+            if istart < 0:
+                istart = 0
+            iend = istart + self.window
+            if iend >= N:
+                iend = -1
+                istart = N - self.window
+
+            t_wa_a = T_Wa_A[istart:iend]
+            t_wb_b = T_Wb_B[istart:iend]
+            T_A_B = self.so3xR3(t_wa_a, t_wb_b)
+            Ts_A_B.append(T_A_B)
+        return Ts_A_B

nymeria/narration_provider.py

@@ -0,0 +1,12 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from pathlib import Path
+
+
+class NarrationProvider:
+    def __init__(self, rootdir: Path):
+        pass

nymeria/path_provider.py

@@ -0,0 +1,57 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from dataclasses import fields
+from pathlib import Path
+
+from nymeria.definitions import BodyFiles, MetaFiles, Subpaths, TextFiles
+
+
+class SequencePathProvider:
+    """
+    \brief Each sequence contains the following subfolders:
+        - recording_head
+        - recording_lwrist
+        - recording_rwrist
+        - recording_observer
+        - body
+        - narration
+    """
+
+    def __init__(self, rootdir: Path) -> None:
+        assert rootdir.is_dir(), f"{rootdir=} not found"
+        self.rootdir = rootdir
+        self.license = rootdir / MetaFiles.license
+        self.metadata = rootdir / MetaFiles.metadata_json
+        self.body_paths = BodyFiles(
+            **{
+                f.name: str(rootdir / getattr(BodyFiles, f.name))
+                for f in fields(BodyFiles)
+            }
+        )
+        self.narration_paths = TextFiles(
+            **{
+                f.name: str(rootdir / getattr(TextFiles, f.name))
+                for f in fields(TextFiles)
+            }
+        )
+
+        self.recording_head: Path = rootdir / Subpaths.recording_head
+        self.recording_lwrist: Path = rootdir / Subpaths.recording_lwrist
+        self.recording_rwrist: Path = rootdir / Subpaths.recording_rwrist
+        self.recording_observer: Path = rootdir / Subpaths.recording_observer
+
+    def __repr__(self) -> str:
+        return (
+            f"SequencePaths(\n"
+            f"  license={self.license},\n"
+            f"  metadata={self.metadata},\n"
+            f"  body_files={self.body_files},\n"
+            f"  recording_head={self.recording_head},\n"
+            f"  recording_observer={self.recording_observer},\n"
+            f"  recording_lwrist={self.recording_lwrist},\n"
+            f"  recording_rwrist={self.recording_rwrist}\n)"
+        )

nymeria/recording_data_provider.py

@@ -0,0 +1,251 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from enum import Enum
+from pathlib import Path
+
+import numpy as np
+from loguru import logger
+
+from nymeria.definitions import Subpaths, VrsFiles
+from projectaria_tools.core import data_provider, mps
+from projectaria_tools.core.data_provider import VrsDataProvider
+from projectaria_tools.core.mps import (
+    ClosedLoopTrajectoryPose,
+    MpsDataPathsProvider,
+    MpsDataProvider,
+)
+from projectaria_tools.core.sensor_data import (
+    ImageData,
+    ImageDataRecord,
+    TimeDomain,
+    TimeQueryOptions,
+)
+from projectaria_tools.core.stream_id import StreamId
+
+
+class AriaStream(Enum):
+    camera_slam_left = "1201-1"
+    camera_slam_right = "1201-2"
+    camera_rgb = "214-1"
+    imu_right = "1202-1"
+    imu_left = "1202-2"
+
+
+class RecordingPathProvider:
+    """
+    \brief This class will not check of input recording path is valid
+    """
+
+    def __init__(self, recording_path: Path):
+        self.recording_path: Path = recording_path
+        self.tag: str = recording_path.name
+
+    @property
+    def data_vrsfile(self) -> Path:
+        return self.recording_path / VrsFiles.data
+
+    @property
+    def motion_vrsfile(self) -> Path:
+        return self.recording_path / VrsFiles.motion
+
+    @property
+    def mps_path(self) -> MpsDataPathsProvider | None:
+        mps_path = self.recording_path / Subpaths.mps
+        if mps_path.is_dir():
+            return MpsDataPathsProvider(str(mps_path))
+        else:
+            return None
+
+    @property
+    def points_npz_cache(self) -> Path:
+        return self.recording_path / Subpaths.mps_slam / "semidense_points_cache.npz"
+
+
+class RecordingDataProvider(RecordingPathProvider):
+    def __init__(self, recording_path: Path) -> None:
+        super().__init__(recording_path)
+
+        self._vrs_dp = None
+        self._mps_dp = None
+        if not self.recording_path.is_dir():
+            return
+
+        # load vrs
+        if self.data_vrsfile.is_file():
+            self._vrs_dp = data_provider.create_vrs_data_provider(
+                str(self.data_vrsfile)
+            )
+        elif self.motion_vrsfile.is_file():
+            self._vrs_dp = data_provider.create_vrs_data_provider(
+                str(self.motion_vrsfile)
+            )
+
+        # load mps
+        if self.mps_path is not None:
+            self._mps_dp = MpsDataProvider(self.mps_path.get_data_paths())
+
+    @property
+    def vrs_dp(self) -> VrsDataProvider | None:
+        return self._vrs_dp
+
+    @property
+    def mps_dp(self) -> MpsDataProvider | None:
+        return self._mps_dp
+
+    def get_global_timespan_ns(self) -> tuple[int, int]:
+        if self.vrs_dp is None:
+            raise RuntimeError(
+                f"require {self.data_vrsfile=} or {self.motion_vrsfile=}"
+            )
+
+        t_start = self.vrs_dp.get_first_time_ns_all_streams(TimeDomain.TIME_CODE)
+        t_end = self.vrs_dp.get_last_time_ns_all_streams(TimeDomain.TIME_CODE)
+        return t_start, t_end
+
+    @property
+    def has_pointcloud(self) -> bool:
+        if self.mps_dp is None or not self.mps_dp.has_semidense_point_cloud():
+            return False
+        else:
+            return True
+
+    def get_pointcloud(
+        self,
+        th_invdep: float = 0.0004,
+        th_dep: float = 0.02,
+        max_point_count: int = 50_000,
+        cache_to_npz: bool = False,
+    ) -> np.ndarray:
+        assert self.has_pointcloud, "recording has no point cloud"
+        points = self.mps_dp.get_semidense_point_cloud()
+
+        points = mps.utils.filter_points_from_confidence(
+            raw_points=points, threshold_dep=th_dep, threshold_invdep=th_invdep
+        )
+        points = mps.utils.filter_points_from_count(
+            raw_points=points, max_point_count=max_point_count
+        )
+
+        points = np.array([x.position_world for x in points])
+
+        if cache_to_npz:
+            np.savez(
+                self.points_npz_cache,
+                points=points,
+                threshold_dep=th_dep,
+                threshold_invdep=th_invdep,
+                max_point_count=max_point_count,
+            )
+        return points
+
+    def get_pointcloud_cached(
+        self,
+        th_invdep: float = 0.0004,
+        th_dep: float = 0.02,
+        max_point_count: int = 50_000,
+    ) -> np.ndarray:
+        assert self.has_pointcloud, "recording has no point cloud"
+        if self.points_npz_cache.is_file():
+            logger.info(f"load cached point cloud from {self.points_npz_cache}")
+            return np.load(self.points_npz_cache)["points"]
+
+        return self.get_pointcloud(cache_to_npz=True)
+
+    @property
+    def has_vrs(self) -> bool:
+        return self.vrs_dp is not None
+
+    @property
+    def has_rgb(self) -> bool:
+        return self.has_vrs and self.vrs_dp.check_stream_is_active(StreamId("214-1"))
+
+    def get_rgb_image(
+        self, t_ns: int, time_domain: TimeDomain = TimeDomain.TIME_CODE
+    ) -> tuple[ImageData, ImageDataRecord, int]:
+        assert self.has_rgb, "recording has no rgb video"
+        assert time_domain in [
+            TimeDomain.DEVICE_TIME,
+            TimeDomain.TIME_CODE,
+        ], "unsupported time domain"
+
+        if time_domain == TimeDomain.TIME_CODE:
+            t_ns_device = self.vrs_dp.convert_from_timecode_to_device_time_ns(
+                timecode_time_ns=t_ns
+            )
+        else:
+            t_ns_device = t_ns
+
+        image_data, image_meta = self.vrs_dp.get_image_data_by_time_ns(
+            StreamId("214-1"),
+            time_ns=t_ns_device,
+            time_domain=TimeDomain.DEVICE_TIME,
+            time_query_options=TimeQueryOptions.CLOSEST,
+        )
+        t_diff = t_ns_device - image_meta.capture_timestamp_ns
+
+        return image_data, image_meta, t_diff
+
+    @property
+    def has_pose(self) -> bool:
+        if self.mps_dp is None or not self.mps_dp.has_closed_loop_poses():
+            return False
+        else:
+            return True
+
+    def get_pose(
+        self, t_ns: int, time_domain: TimeDomain
+    ) -> tuple[ClosedLoopTrajectoryPose, int]:
+        t_ns = int(t_ns)
+        assert self.has_pose, "recording has no closed loop trajectory"
+        assert time_domain in [
+            TimeDomain.DEVICE_TIME,
+            TimeDomain.TIME_CODE,
+        ], "unsupported time domain"
+
+        if time_domain == TimeDomain.TIME_CODE:
+            assert self.vrs_dp, "require vrs for time domain mapping"
+            t_ns_device = self.vrs_dp.convert_from_timecode_to_device_time_ns(
+                timecode_time_ns=t_ns
+            )
+
+        else:
+            t_ns_device = t_ns
+
+        pose = self.mps_dp.get_closed_loop_pose(t_ns_device, TimeQueryOptions.CLOSEST)
+        t_diff = pose.tracking_timestamp.total_seconds() * 1e9 - t_ns_device
+        return pose, t_diff
+
+    def sample_trajectory_world_device(self, sample_fps: float = 1) -> np.ndarray:
+        assert self.has_pose, "recording has no closed loop trajectory"
+        assert self.has_vrs, "current implementation assume vrs is loaded."
+        t_start, t_end = self.get_global_timespan_ns()
+        t_start = self.vrs_dp.convert_from_timecode_to_device_time_ns(t_start)
+        t_end = self.vrs_dp.convert_from_timecode_to_device_time_ns(t_end)
+
+        dt = int(1e9 / sample_fps)
+        traj_world_device = []
+        for t_ns in range(t_start, t_end, dt):
+            pose = self.mps_dp.get_closed_loop_pose(t_ns, TimeQueryOptions.CLOSEST)
+            traj_world_device.append(
+                pose.transform_world_device.to_matrix().astype(np.float32)
+            )
+
+        traj_world_device = np.stack(traj_world_device, axis=0)
+        return traj_world_device
+
+
+def create_recording_data_provider(
+    recording_path: Path,
+) -> RecordingDataProvider | None:
+    if not recording_path.is_dir():
+        return None
+
+    dp = RecordingDataProvider(recording_path)
+    if dp.vrs_dp is None and dp.mps_dp is None:
+        return None
+    else:
+        return dp

nymeria/sequence_attributes.py

@@ -0,0 +1,62 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from dataclasses import dataclass
+
+
+@dataclass
+class SequenceAttributes:
+    date: str
+    session_id: str
+    fake_name: str
+    act_id: str
+    uid: str
+
+    location: str
+    script: str
+    action_duration_sec: float = -1
+
+    has_two_participants: bool = False
+    pt2: str = None
+    body_motion: bool = False
+
+    head_data: bool = False
+    head_slam: bool = False
+    head_trajectory_m: float = None
+    head_duration_sec: float = None
+    head_general_gaze: bool = False
+    head_personalized_gaze: bool = False
+
+    left_wrist_data: bool = False
+    left_wrist_slam: bool = False
+    left_wrist_trajectory_m: float = None
+    left_wrist_duration_sec: float = None
+
+    right_wrist_data: bool = False
+    right_wrist_slam: bool = False
+    right_wrist_trajectory_m: float = None
+    right_wrist_duration_sec: float = None
+
+    observer_data: bool = False
+    observer_slam: bool = False
+    observer_general_gaze: bool = False
+    observer_personalized_gaze: bool = False
+    observer_trajectory_m: float = None
+    observer_duration_sec: float = None
+
+    timesync: bool = False
+
+    motion_narration: bool = False
+    atomic_action: bool = False
+    activity_summarization: bool = False
+
+    participant_gender: str = None
+    participant_height_cm: float = -1
+    participant_weight_kg: float = -1
+    participant_bmi: float = -1
+    participant_age_group: str = None
+    participant_ethnicity: str = None
+    participant_xsens_suit_size: str = None

nymeria/xsens_constants.py

@@ -0,0 +1,98 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+class XSensConstants:
+    """
+    \brief Transformations segment_tXYZ and segment_qWXYZ are defined as
+           from XSens segment/part coordinates to XSens world coordinates.
+           See XSens manual for details.
+    """
+
+    num_parts: int = 23
+    num_bones: int = 22
+    num_sensors: int = 17
+    k_timestamps_us: str = "timestamps_us"
+    k_frame_count: str = "frameCount"
+    k_framerate: str = "frameRate"
+    k_part_tXYZ: str = "segment_tXYZ"
+    k_part_qWXYZ: str = "segment_qWXYZ"
+    k_ipose_part_tXYZ: str = "identity_segment_tXYZ"
+    k_ipose_part_qWXYZ: str = "identity_segment_qWXYZ"
+    k_tpose_part_tXYZ: str = "tpose_segment_tXYZ"
+    k_tpose_part_qWXYZ: str = "tpose_segment_qWXYZ"
+    k_foot_contacts: str = "foot_contacts"
+    k_sensor_tXYZ: str = "sensor_tXYZ"
+    k_sensor_qWXYZ: str = "sensor_qWXYZ"
+    part_names = [
+        "Pelvis",
+        "L5",
+        "L3",
+        "T12",
+        "T8",
+        "Neck",
+        "Head",
+        "R_Shoulder",
+        "R_UpperArm",
+        "R_Forearm",
+        "R_Hand",
+        "L_Shoulder",
+        "L_UpperArm",
+        "L_Forearm",
+        "L_Hand",
+        "R_UpperLeg",
+        "R_LowerLeg",
+        "R_Foot",
+        "R_Toe",
+        "L_UpperLeg",
+        "L_LowerLeg",
+        "L_Foot",
+        "L_Toe",
+    ]  # num = 23
+    kintree_parents: list[int] = [
+        -1,
+        0,
+        1,
+        2,
+        3,
+        4,
+        5,
+        4,
+        7,
+        8,
+        9,
+        4,
+        11,
+        12,
+        13,
+        0,
+        15,
+        16,
+        17,
+        0,
+        19,
+        20,
+        21,
+    ]  # num = 23
+    sensor_names: list[int] = [
+        "Pelvis",
+        "T8",
+        "Head",
+        "RightShoulder",
+        "RightUpperArm",
+        "RightForeArm",
+        "RightHand",
+        "LeftShoulder",
+        "LeftUpperArm",
+        "LeftForeArm",
+        "LeftHand",
+        "RightUpperLeg",
+        "RightLowerLeg",
+        "RightFoot",
+        "LeftUpperLeg",
+        "LeftLowerLeg",
+        "LeftFoot",
+    ]  # num = 17

setup.py

@@ -0,0 +1,18 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from setuptools import find_packages, setup
+
+setup(
+    name="nymeria",
+    version="0.0.1",
+    packages=find_packages(),
+    author="Lingni Ma",
+    author_email="lingni.ma@meta.com",
+    description="The official repo to support the Nymeria dataset",
+    python_requires=">=3.10",
+    install_requires=["click", "requests", "tqdm"],
+)

viewer.py

@@ -0,0 +1,46 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import sys
+from pathlib import Path
+
+import click
+import rerun as rr
+from loguru import logger
+from nymeria.data_provider import NymeriaDataProvider
+from nymeria.data_viewer import NymeriaViewer
+
+
+@click.command()
+@click.option(
+    "-i", "sequence_dir", type=Path, required=True, help="The directory of sequence "
+)
+@click.option(
+    "-s", "save_rrd", is_flag=True, default=False, help="Save rerun into logfile"
+)
+def main(sequence_dir: Path, save_rrd: bool) -> None:
+    logger.remove()
+    logger.add(
+        sys.stdout,
+        colorize=True,
+        format="<level>{level: <7}</level> <blue>{name}.py:</blue><green>{function}</green><yellow>:{line}</yellow> {message}",
+        level="INFO",
+    )
+
+    # See NymeriaDataProviderConfig for configuration
+    nymeria_dp = NymeriaDataProvider(sequence_rootdir=sequence_dir, load_wrist=True)
+
+    output_rrd: Path = sequence_dir / "nymeria.rrd" if save_rrd else None
+    viewer = NymeriaViewer(output_rrd=output_rrd)
+    viewer(nymeria_dp)
+    if save_rrd:
+        logger.info(f"Save visualization to {output_rrd=}")
+
+    rr.disconnect()
+
+
+if __name__ == "__main__":
+    main()