Datasets:

imageomics
/

kabr-worked-examples

time(millisecond) int64	datetime(utc) string	latitude float64	longitude float64	height_above_takeoff(feet) float64	height_above_ground_at_drone_location(feet) string	ground_elevation_at_drone_location(feet) string	altitude_above_seaLevel(feet) float64	height_sonar(feet) float64	speed(mph) float64	distance(feet) float64	mileage(feet) float64	satellites int64	gpslevel int64	voltage(v) float64	max_altitude(feet) float64	max_ascent(feet) float64	max_speed(mph) float64	max_distance(feet) float64	xSpeed(mph) float64	ySpeed(mph) float64	zSpeed(mph) float64	compass_heading(degrees) float64	pitch(degrees) float64	roll(degrees) float64	isVideo int64	rc_elevator int64	rc_aileron int64	rc_throttle int64	rc_rudder int64	rc_elevator(percent) int64	rc_aileron(percent) int64	rc_throttle(percent) int64	rc_rudder(percent) int64	gimbal_heading(degrees) float64	battery_percent int64	voltageCell1 float64	voltageCell2 float64	voltageCell3 float64	current(A) float64	battery_temperature(f) float64	altitude(feet) float64	ascent(feet) float64	flycStateRaw int64	flycState string	message string
0	2023-01-18 09:47:03	0.349825	36.879798	0	Available with any HD 360 subscription	Available with any HD 360 subscription	5,821.801319	0.328084	0	0	0	27	5	0	5,821.801319	0	0	0	0	0	0	71.9	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	Setting new Return-To-Home altitude to 45m (148 ft). Data Recorder File Index is 75. Setting new Maximum Flight Altitude to 70m (230 ft)
100	2023-01-18 09:47:03	0.349825	36.879798	0	null	null	5,821.801319	0.328084	0	0.002953	0.002953	27	5	0	5,821.801319	0	0	0.002953	0	0	0	71.9	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
200	2023-01-18 09:47:03	0.349825	36.879798	0	null	null	5,821.801319	0.328084	0	0.003165	0.008914	27	5	0	5,821.801319	0	0	0.003165	0	0	0	71.9	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
300	2023-01-18 09:47:03	0.349825	36.879798	0	null	null	5,821.801319	0.328084	0	0.001988	0.010976	27	5	0	5,821.801319	0	0	0.003165	0	0	0	71.9	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
400	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.050603	0.063009	27	5	0	5,821.801319	0	0	0.050603	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
500	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.057011	0.069509	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
600	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.045062	0.081491	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.8	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
700	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.050147	0.086685	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
800	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.041023	0.09587	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
900	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.045063	0.100041	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
1,000	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.036674	0.108562	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72	2.4	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
1,100	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.039493	0.111518	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
1,200	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.034014	0.117054	27	5	0	5,821.801319	0	0	0.057011	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	71.9	100	4.109	4.109	4.098	0	93.38	5,821.801319	0	41	Motors_Started	null
1,300	2023-01-18 09:47:04	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.036496	0.119818	27	5	12.323	5,821.801319	0	0	0.057011	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	41	Motors_Started	null
1,400	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.088277	0.171624	27	5	12.323	5,821.801319	0	0	0.088277	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	41	Motors_Started	null
1,500	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.094955	0.178373	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
1,600	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.081968	0.191489	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
1,700	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.087362	0.196947	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
1,800	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.077422	0.207024	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
1,900	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.08137	0.211032	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,000	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.072363	0.22013	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,100	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.074918	0.222754	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	364	364	364	1,684	-100	-100	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,200	2023-01-18 09:47:05	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.068253	0.229501	27	5	12.323	5,821.801319	0	0	0.094955	0	0	0	72.1	2.3	0.8	1	475	425	364	1,684	-83	-91	-100	100	72	100	4.109	4.109	4.098	3.354	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,300	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.069662	0.231001	27	5	12.368	5,821.801319	0	0	0.094955	0	0	0	72.2	2.3	0.8	1	705	706	364	1,645	-48	-48	-100	94	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,400	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.121629	0.282972	27	5	12.368	5,821.801319	0	0	0.121629	0	0	0	72.2	2.3	0.8	1	705	706	364	1,645	-48	-48	-100	94	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,500	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.127436	0.288819	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	942	1,024	568	1,379	-12	0	-69	54	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,600	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.115857	0.300407	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.1	2.3	0.8	1	1,017	1,024	658	1,268	-1	0	-55	37	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,700	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.120305	0.304903	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	887	1,050	0	0	-21	4	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,800	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.111061	0.314164	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.1	2.3	0.8	1	1,024	1,024	1,024	1,024	0	0	0	0	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
2,900	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.114271	0.317456	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,024	1,027	0	0	0	0	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,000	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.106729	0.325043	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,024	1,024	0	0	0	0	72	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,100	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.109128	0.327558	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,071	1,024	0	0	7	0	72.1	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,200	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.10425	0.33249	27	5	12.368	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,071	1,024	0	0	7	0	72.1	100	4.129	4.13	4.117	3.379	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,300	2023-01-18 09:47:06	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.105971	0.334337	27	5	12.375	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,090	1,024	0	0	10	0	72.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,400	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.117953	0.391959	27	5	12.375	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,092	1,024	0	0	10	0	72.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,500	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.12131	0.396591	27	5	12.375	5,821.801319	0	0	0.127436	0	0	0	72.2	2.3	0.8	1	1,024	1,024	1,119	1,024	0	0	14	0	72.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,600	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.166587	0.450997	27	5	12.375	5,821.801319	0	0	0.166587	0	0	0	72.2	2.2	0.8	1	1,024	1,024	1,226	1,024	0	0	31	0	72.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,700	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.173667	0.458192	27	5	12.375	5,821.801319	0	0	0.173667	0	0	0	72.1	2.1	0.8	1	1,024	1,024	1,379	1,060	0	0	54	5	72.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,800	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.16465	0.467825	27	5	12.375	5,821.801319	0	0	0.173667	0	0	0	71.5	1.5	0.8	1	1,024	1,024	1,483	1,035	0	0	70	2	71.9	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
3,900	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.17913	0.482789	27	5	12.375	5,821.801319	0	0	0.17913	0	0	0	70.2	-1.3	0.7	1	1,024	1,024	1,639	1,024	0	0	93	0	71.1	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
4,000	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0	0.168943	0.503655	27	5	12.375	5,821.801319	0	0	0.17913	0	0	0	70.6	-3.4	0.7	1	1,024	1,024	1,684	1,024	0	0	100	0	70.7	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
4,100	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0.223694	0.172534	0.537156	27	5	12.375	5,821.801319	0	0.223694	0.17913	0	0.223694	-0.223694	69.8	-3.7	1.1	1	1,024	1,024	1,684	1,024	0	0	100	0	70.6	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	10	Assisted_Takeoff	null
4,200	2023-01-18 09:47:07	0.349824	36.879798	0	null	null	5,821.801319	0.328084	0.223694	0.191105	0.595062	27	5	12.375	5,821.801319	0	0.223694	0.191105	0	0.223694	-0.894776	69.7	0.3	-0.7	1	1,024	1,024	1,684	1,024	0	0	100	0	70.6	100	4.129	4.13	4.116	2.286	93.38	5,821.801319	0	6	P-GPS	null
4,300	2023-01-18 09:47:07	0.349824	36.879798	0.328084	null	null	5,822.129403	0.328084	0.313172	0.243313	0.655302	27	5	12.328	5,822.129403	0.328084	0.313172	0.243313	-0.223694	0.223694	-1.789552	69.4	1.6	-1.3	1	1,024	1,024	1,684	1,097	0	0	100	11	70.6	100	4.072	4.068	4.049	3.039	93.38	5,822.129403	0.328084	6	P-GPS	null
4,400	2023-01-18 09:47:08	0.349824	36.879798	0.328084	null	null	5,822.129403	0.328084	0.447388	0.325056	0.747162	27	5	12.328	5,822.129403	0.328084	0.447388	0.325056	-0.447388	0	-2.460634	69.5	0.3	-1.3	1	1,024	1,024	1,684	1,180	0	0	100	24	70.6	100	4.072	4.068	4.049	3.039	93.38	5,822.129403	0.328084	6	P-GPS	null
4,500	2023-01-18 09:47:08	0.349823	36.879798	0.984252	null	null	5,822.785571	0.328084	0.447388	0.40395	0.830112	27	5	12.328	5,822.785571	0.984252	0.447388	0.40395	-0.447388	0	-3.131716	70.1	-1.3	-2.1	1	1,024	1,024	1,684	1,154	0	0	100	20	71	100	4.072	4.068	4.049	3.039	93.38	5,822.785571	0.984252	6	P-GPS	null
4,600	2023-01-18 09:47:08	0.349823	36.879798	1.312336	null	null	5,823.113655	1.64042	0.447388	0.438858	0.925322	27	5	12.328	5,823.113655	1.312336	0.447388	0.438858	-0.447388	0	-4.026492	70.7	-2.5	-3.3	1	1,024	1,024	1,684	1,111	0	0	100	13	71.6	100	4.072	4.068	4.049	3.039	93.38	5,823.113655	1.312336	6	P-GPS	null
4,700	2023-01-18 09:47:08	0.349823	36.879798	2.296588	null	null	5,824.097907	2.296588	0.447388	0.535577	1.02606	27	5	12.328	5,824.097907	2.296588	0.447388	0.535577	-0.447388	0	-4.921268	71.1	-2.6	-4.3	1	1,024	1,024	1,684	1,087	0	0	100	10	72.2	100	4.072	4.068	4.049	3.039	93.38	5,824.097907	2.296588	6	P-GPS	null
4,800	2023-01-18 09:47:08	0.349823	36.879798	2.952756	null	null	5,824.754075	3.28084	0.447388	0.590807	1.108107	27	5	12.328	5,824.754075	2.952756	0.447388	0.590807	-0.447388	0	-6.039738	71.7	-3.6	-4.4	1	1,024	1,024	1,684	1,048	0	0	100	4	72.6	100	4.072	4.068	4.049	3.039	93.38	5,824.754075	2.952756	6	P-GPS	null
4,900	2023-01-18 09:47:08	0.349823	36.879798	3.937008	null	null	5,825.738327	4.265092	0.447388	0.670984	1.195161	27	5	12.328	5,825.738327	3.937008	0.447388	0.670984	-0.447388	0	-6.934514	72.3	-4.8	-4.9	1	1,024	1,024	1,684	1,024	0	0	100	0	72.9	100	4.072	4.068	4.049	3.039	93.38	5,825.738327	3.937008	6	P-GPS	null
5,000	2023-01-18 09:47:08	0.349823	36.879798	4.92126	null	null	5,826.722579	5.249344	0.447388	0.697415	1.248963	27	5	12.328	5,826.722579	4.92126	0.447388	0.697415	-0.447388	0	-8.052984	72.4	-3.5	-4.7	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	4.072	4.068	4.049	3.039	93.38	5,826.722579	4.92126	6	P-GPS	null
5,100	2023-01-18 09:47:08	0.349822	36.879798	6.233596	null	null	5,828.034915	6.56168	0.447388	0.749803	1.304567	27	5	12.328	5,828.034915	6.233596	0.447388	0.749803	-0.223694	0	-8.94776	72.6	-3.9	-4.6	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	4.072	4.068	4.049	3.039	93.38	5,828.034915	6.233596	6	P-GPS	null
5,200	2023-01-18 09:47:08	0.349822	36.879798	7.545932	null	null	5,829.347251	8.2021	0.223694	0.874124	1.430085	27	5	12.328	5,829.347251	7.545932	0.447388	0.874124	-0.223694	0	-9.842536	72.5	-3.1	-5.5	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	4.072	4.068	4.049	3.039	93.38	5,829.347251	7.545932	6	P-GPS	null
5,300	2023-01-18 09:47:08	0.349822	36.879798	9.186352	null	null	5,830.987671	9.514436	0.223694	0.917051	1.475879	27	5	12.032	5,830.987671	9.186352	0.447388	0.917051	-0.223694	0	-10.737312	72.6	-2.5	-4.9	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,830.987671	9.186352	6	P-GPS	null
5,400	2023-01-18 09:47:09	0.349822	36.879798	10.826772	null	null	5,832.628091	11.48294	0.223694	1.050085	1.609255	27	5	12.032	5,832.628091	10.826772	0.447388	1.050085	-0.223694	0	-11.632088	72.6	-3.9	-4.2	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,832.628091	10.826772	6	P-GPS	null
5,500	2023-01-18 09:47:09	0.349822	36.879798	12.795276	null	null	5,834.596595	13.12336	0.223694	1.096299	1.660112	27	5	12.032	5,834.596595	12.795276	0.447388	1.096299	-0.223694	0	-12.750558	72.5	-3.2	-4.7	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,834.596595	12.795276	6	P-GPS	Home Point updated. RTH altitude adjusted to 45 m (Code: 120852)
5,600	2023-01-18 09:47:09	0.349821	36.879797	14.435696	null	null	5,836.237015	15.091864	0.313172	1.18753	1.756161	27	5	12.032	5,836.237015	14.435696	0.447388	1.18753	-0.223694	-0.223694	-13.42164	72.9	-4.1	-5.4	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,836.237015	14.435696	6	P-GPS	null
5,700	2023-01-18 09:47:09	0.349821	36.879797	16.732284	null	null	5,838.533603	17.060368	0.313172	1.246837	1.824177	27	5	12.032	5,838.533603	16.732284	0.447388	1.246837	-0.223694	-0.223694	-13.645334	72.9	-5	-4.8	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,838.533603	16.732284	6	P-GPS	null
5,800	2023-01-18 09:47:09	0.349821	36.879797	18.700788	null	null	5,840.502107	19.356956	0.313172	1.275381	1.864971	27	5	12.032	5,840.502107	18.700788	0.447388	1.275381	-0.223694	-0.223694	-14.092722	73.3	-7	-5.3	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,840.502107	18.700788	6	P-GPS	null
5,900	2023-01-18 09:47:09	0.349821	36.879797	20.669292	null	null	5,842.470611	21.32546	0.447388	1.34875	1.940295	27	5	12.032	5,842.470611	20.669292	0.447388	1.34875	-0.447388	0	-14.092722	73.3	-6.9	-7.7	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,842.470611	20.669292	6	P-GPS	null
6,000	2023-01-18 09:47:09	0.349821	36.879797	22.637796	null	null	5,844.439115	23.622048	0.223694	1.368333	1.97415	27	5	12.032	5,844.439115	22.637796	0.447388	1.368333	-0.223694	0	-13.869028	73.2	-4.6	-8	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,844.439115	22.637796	6	P-GPS	null
6,100	2023-01-18 09:47:09	0.349821	36.879797	24.934384	null	null	5,846.735703	25.590552	0.223694	1.422346	2.028291	27	5	12.032	5,846.735703	24.934384	0.447388	1.422346	-0.223694	0	-13.645334	73.1	-5.6	-7.5	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,846.735703	24.934384	6	P-GPS	null
6,200	2023-01-18 09:47:09	0.349821	36.879797	26.902888	null	null	5,848.704207	27.559056	0.223694	1.441982	2.099308	27	5	12.032	5,848.704207	26.902888	0.447388	1.441982	-0.223694	0	-13.42164	72.8	-5.4	-8.8	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	100	3.982	3.978	3.961	10.31	93.38	5,848.704207	26.902888	6	P-GPS	null
6,300	2023-01-18 09:47:09	0.349821	36.879797	28.871392	null	null	5,850.672711	29.855644	0.223694	1.48875	2.147356	27	5	11.9	5,850.672711	28.871392	0.447388	1.48875	-0.223694	0	-13.197946	72.7	-5.7	-8.7	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,850.672711	28.871392	6	P-GPS	null
6,400	2023-01-18 09:47:10	0.34982	36.879797	30.839896	null	null	5,852.641215	31.824148	0	1.641709	2.303747	27	5	11.9	5,852.641215	30.839896	0.447388	1.641709	0	0	-13.197946	72.7	-5.8	-8.1	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,852.641215	30.839896	6	P-GPS	null
6,500	2023-01-18 09:47:10	0.34982	36.879797	32.8084	null	null	5,854.609719	33.464568	0	1.678409	2.346772	27	5	11.9	5,854.609719	32.8084	0.447388	1.678409	0	0	-13.197946	72.7	-5.9	-7.2	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,854.609719	32.8084	6	P-GPS	null
6,600	2023-01-18 09:47:10	0.34982	36.879797	34.776904	null	null	5,856.578223	35.433072	0	1.698996	2.37397	27	5	11.9	5,856.578223	34.776904	0.447388	1.698996	0	0	-13.197946	72.7	-6.2	-6.7	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,856.578223	34.776904	6	P-GPS	null
6,700	2023-01-18 09:47:10	0.34982	36.879797	36.745408	null	null	5,858.546727	37.401576	0	1.725417	2.408839	27	5	11.9	5,858.546727	36.745408	0.447388	1.725417	0	0	-13.197946	72.9	-6.2	-6.9	1	1,024	1,024	1,660	1,024	0	0	96	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,858.546727	36.745408	6	P-GPS	null
6,800	2023-01-18 09:47:10	0.34982	36.879797	38.713912	null	null	5,860.515231	39.37008	0	1.767946	2.452585	27	5	11.9	5,860.515231	38.713912	0.447388	1.767946	0	0	-13.197946	73	-6.2	-6.8	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,860.515231	38.713912	6	P-GPS	null
6,900	2023-01-18 09:47:10	0.34982	36.879796	40.354332	null	null	5,862.155651	41.338584	0	1.790709	2.481772	27	5	11.9	5,862.155651	40.354332	0.447388	1.790709	0	0	-12.974252	73.1	-6.3	-6.9	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,862.155651	40.354332	6	P-GPS	null
7,000	2023-01-18 09:47:10	0.34982	36.879796	42.322836	null	null	5,864.124155	43.307088	0	1.789026	2.533862	27	5	11.9	5,864.124155	42.322836	0.447388	1.790709	0	0	-12.974252	73.1	-6.5	-6.6	1	1,024	1,024	1,684	1,024	0	0	100	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,864.124155	42.322836	6	P-GPS	null
7,100	2023-01-18 09:47:10	0.34982	36.879796	44.29134	null	null	5,866.092659	44.947508	0	1.803547	2.558606	27	5	11.9	5,866.092659	44.29134	0.447388	1.803547	0	0	-12.974252	73.2	-6.4	-6.5	1	1,024	1,024	1,676	1,024	0	0	99	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,866.092659	44.29134	6	P-GPS	null
7,200	2023-01-18 09:47:10	0.34982	36.879796	46.259844	null	null	5,868.061163	46.587928	0	1.807405	2.570528	27	5	11.9	5,868.061163	46.259844	0.447388	1.807405	0	0	-12.974252	73.3	-6.2	-6.5	1	1,024	1,024	1,677	1,024	0	0	99	0	73.1	99	4.014	4.011	3.997	15.112	93.56	5,868.061163	46.259844	6	P-GPS	null
7,300	2023-01-18 09:47:10	0.34982	36.879796	48.228348	null	null	5,870.029667	48.556432	0	1.819918	2.588832	27	5	11.981	5,870.029667	48.228348	0.447388	1.819918	0	0	-12.974252	73.3	-6.4	-6.6	1	1,024	1,024	1,663	1,024	0	0	97	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,870.029667	48.228348	6	P-GPS	null
7,400	2023-01-18 09:47:11	0.34982	36.879796	50.196852	null	null	5,871.998171	50.524936	0	1.861867	2.649912	27	5	11.981	5,871.998171	50.196852	0.447388	1.861867	0	0	-12.974252	73.3	-6.5	-7.1	1	1,024	1,024	1,660	1,024	0	0	96	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,871.998171	50.196852	6	P-GPS	null
7,500	2023-01-18 09:47:11	0.34982	36.879796	52.165356	null	null	5,873.966675	52.49344	0	1.879131	2.670991	27	5	11.981	5,873.966675	52.165356	0.447388	1.879131	0	0	-12.750558	73.3	-6.6	-7.3	1	1,024	1,024	1,651	1,024	0	0	95	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,873.966675	52.165356	6	P-GPS	null
7,600	2023-01-18 09:47:11	0.34982	36.879796	53.805776	null	null	5,875.607095	54.461944	0	1.797559	2.756273	27	5	11.981	5,875.607095	53.805776	0.447388	1.879131	0	0	-12.750558	73.3	-6.4	-7.1	1	1,024	1,024	1,500	1,024	0	0	72	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,875.607095	53.805776	6	P-GPS	null
7,700	2023-01-18 09:47:11	0.34982	36.879796	55.77428	null	null	5,877.575599	56.430448	0	1.810469	2.771824	27	5	11.981	5,877.575599	55.77428	0.447388	1.879131	0	0	-12.526864	73.4	-6.9	-8	1	1,024	1,024	1,127	1,024	0	0	16	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,877.575599	55.77428	6	P-GPS	null
7,800	2023-01-18 09:47:11	0.34982	36.879796	57.742784	null	null	5,879.544103	58.070868	0	1.845368	2.857864	27	5	11.981	5,879.544103	57.742784	0.447388	1.879131	0	0	-11.632088	73.5	-7.3	-8.6	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,879.544103	57.742784	6	P-GPS	null
7,900	2023-01-18 09:47:11	0.34982	36.879796	59.383204	null	null	5,881.184523	59.711288	0	1.872986	2.889328	27	5	11.981	5,881.184523	59.383204	0.447388	1.879131	0	0	-10.737312	73.6	-7.6	-8.9	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,881.184523	59.383204	6	P-GPS	null
8,000	2023-01-18 09:47:11	0.34982	36.879796	60.69554	null	null	5,882.496859	61.023624	0	1.8923	2.919429	27	5	11.981	5,882.496859	60.69554	0.447388	1.8923	0	0	-9.842536	73.7	-7.8	-8.9	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,882.496859	60.69554	6	P-GPS	null
8,100	2023-01-18 09:47:11	0.34982	36.879796	62.33596	null	null	5,884.137279	62.33596	0.223694	1.931188	2.961057	27	5	11.981	5,884.137279	62.33596	0.447388	1.931188	-0.223694	0	-8.94776	73.9	-8.6	-9.5	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,884.137279	62.33596	6	P-GPS	null
8,200	2023-01-18 09:47:11	0.34982	36.879796	63.648296	null	null	5,885.449615	63.648296	0.223694	1.948291	2.988717	27	5	11.981	5,885.449615	63.648296	0.447388	1.948291	-0.223694	0	-8.052984	74.1	-8.9	-10	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	3.996	3.982	3.97	10.914	93.56	5,885.449615	63.648296	6	P-GPS	null
8,300	2023-01-18 09:47:11	0.34982	36.879796	64.632548	null	null	5,886.433867	64.632548	0.223694	1.994068	3.036152	27	5	11.971	5,886.433867	64.632548	0.447388	1.994068	-0.223694	0	-6.934514	74.1	-9	-10.4	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,886.433867	64.632548	6	P-GPS	null
8,400	2023-01-18 09:47:12	0.349819	36.879796	65.6168	null	null	5,887.418119	65.6168	0.223694	2.027753	3.07126	27	5	11.971	5,887.418119	65.6168	0.447388	2.027753	-0.223694	0	-6.039738	74.2	-9.3	-10.5	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,887.418119	65.6168	6	P-GPS	null
8,500	2023-01-18 09:47:12	0.349819	36.879795	66.272968	null	null	5,888.074287	66.272968	0.223694	2.074249	3.118255	27	5	11.971	5,888.074287	66.272968	0.447388	2.074249	-0.223694	0	-4.921268	74.3	-9.4	-10.6	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,888.074287	66.272968	6	P-GPS	null
8,600	2023-01-18 09:47:12	0.349819	36.879795	66.929136	null	null	5,888.730455	66.929136	0.223694	2.101476	3.171693	27	5	11.971	5,888.730455	66.929136	0.447388	2.101476	-0.223694	0	-4.026492	74.3	-9.2	-11	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,888.730455	66.929136	6	P-GPS	null
8,700	2023-01-18 09:47:12	0.349819	36.879795	67.585304	null	null	5,889.386623	67.25722	0.223694	2.144268	3.215338	27	5	11.971	5,889.386623	67.585304	0.447388	2.144268	-0.223694	0	-2.908022	74.3	-9.3	-11.4	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.386623	67.585304	6	P-GPS	null
8,800	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.585304	0.223694	2.177871	3.256319	27	5	11.971	5,889.714707	67.913388	0.447388	2.177871	-0.223694	0	-2.013246	74.3	-9.5	-11.4	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.714707	67.913388	6	P-GPS	null
8,900	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.585304	0	2.215033	3.294455	27	5	11.971	5,889.714707	67.913388	0.447388	2.215033	0	0	-0.894776	74.2	-9.3	-10.9	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.714707	67.913388	6	P-GPS	null
9,000	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.585304	0	2.207818	3.360663	27	5	11.971	5,889.714707	67.913388	0.447388	2.215033	0	0	-0.223694	74.4	-9.8	-11.5	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.714707	67.913388	6	P-GPS	null
9,100	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.585304	0	2.214482	3.370735	27	5	11.971	5,889.714707	67.913388	0.447388	2.215033	0	0	0	74.5	-9.8	-11.1	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.714707	67.913388	6	P-GPS	null
9,200	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.585304	0.223694	2.15107	3.43481	27	5	11.971	5,889.714707	67.913388	0.447388	2.215033	0	0.223694	0	74.3	-7.3	-10.8	1	1,024	1,024	1,024	1,024	0	0	0	0	73.1	99	4.034	4.032	4.02	11.246	93.74	5,889.714707	67.913388	6	P-GPS	null
9,300	2023-01-18 09:47:12	0.349819	36.879795	67.913388	null	null	5,889.714707	67.25722	0.313172	2.103465	3.482448	27	5	12.178	5,889.714707	67.913388	0.447388	2.215033	0.223694	0.223694	0	73.6	-5.1	-9.7	1	1,041	1,024	1,024	1,024	3	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,889.714707	67.913388	6	P-GPS	null
9,400	2023-01-18 09:47:13	0.349819	36.879795	67.913388	null	null	5,889.714707	67.25722	0.313172	2.164846	3.543996	27	5	12.178	5,889.714707	67.913388	0.447388	2.215033	0.223694	0.223694	0	73.2	-4.7	-8.4	1	1,092	1,024	1,024	1,024	10	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,889.714707	67.913388	6	P-GPS	null
9,500	2023-01-18 09:47:13	0.349819	36.879795	68.241472	null	null	5,890.042791	67.585304	0.313172	2.108228	3.600755	27	5	12.178	5,890.042791	68.241472	0.447388	2.215033	0.223694	0.223694	0	72.8	-4.4	-6.4	1	1,093	1,024	1,024	1,024	10	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,890.042791	68.241472	6	P-GPS	null
9,600	2023-01-18 09:47:13	0.349819	36.879795	68.241472	null	null	5,890.042791	67.913388	0.492127	2.097822	3.642421	27	5	12.178	5,890.042791	68.241472	0.492127	2.215033	0.223694	0.447388	0	72.4	-3.2	-6.8	1	1,093	1,024	1,024	1,024	10	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,890.042791	68.241472	6	P-GPS	null
9,700	2023-01-18 09:47:13	0.34982	36.879795	68.241472	null	null	5,890.042791	68.569556	0.313172	2.039006	3.701936	27	5	12.178	5,890.042791	68.241472	0.492127	2.215033	0.223694	0.223694	0	72.6	-3.3	-6.3	1	1,092	1,024	1,024	1,024	10	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,890.042791	68.241472	6	P-GPS	null
9,800	2023-01-18 09:47:13	0.349819	36.879795	68.241472	null	null	5,890.042791	68.89764	0.313172	2.030098	3.734154	27	5	12.178	5,890.042791	68.241472	0.492127	2.215033	0.223694	0.223694	0	72.7	-3.7	-6.3	1	1,106	1,024	1,024	1,024	12	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,890.042791	68.241472	6	P-GPS	null
9,900	2023-01-18 09:47:13	0.34982	36.879796	68.241472	null	null	5,890.042791	69.225724	0.313172	1.972156	3.79311	27	5	12.178	5,890.042791	68.241472	0.492127	2.215033	0.223694	0.223694	0	72.6	-3.4	-6.6	1	1,115	1,024	1,024	1,024	14	0	0	0	73.1	99	4.071	4.07	4.056	5.295	93.92	5,890.042791	68.241472	6	P-GPS	null

End of preview. Expand in Data Studio

Dataset Card for KABR Worked Examples

This dataset is comprised of manually annotated bounding box detections, mini-scenes, behavior annotations, and associated telemetry for three drone video sessions that were used for kabr-tools case studies. Drone video was collected at Mpala Research Centre in January 2023; please see the full video dataset for more information on original video context.

Dataset Details

Annotations were created to evaluate the kabr-tools pipeline and conduct case studies on Grevy's landscape of fear and inter-species spatial distribution. Annotations include manual detections and tracks, mini-scenes cut from source videos, behavior annotations from an X3D action recognition model, and associated drone telemetry data. The detections contain bounding box coordinates, image file names, and class labels for each annotated animal. Annotations were created using CVAT to manually draw bounding boxes around animals in a selection of raw drone videos. The annotations were then exported as xml files and used to create the provided mini-scenes. The KABR X3D model was used to label the mini-scenes with predicted behaviors. Telemetry data was exported from Airdata.

Session Summary

Session	Date Collected	Demographic Information and Habitat	Video File IDs in Session	Session Source Videos (link)
`ex-1`	2023-01-18	2 Adult male Grevy's zebras in an open plain	`DJI_0068`, `DJI_0069`, `DJI_0070`, `DJI_0071`	imageomics/KABR-raw-videos/18_01_2023_session_7/
`ex-2`	2023-01-20	5 Grevy's zebras in a semi-open habitat along a roadway	`DJI_0142`, `DJI_0143`, `DJI_0144`, `DJI_0145`, `DJI_0146`, `DJI_0147`	imageomics/KABR-raw-videos/20_01_2023_session_3/
`ex-3`	2023-01-21	Mixed herd of 3 reticulated giraffes, 2 plains zebras and 11 Grevy's zebras in a closed habitat with dense vegetation near Mo Kenya	`DJI_0206`, `DJI_0208`, `DJI_0210`, `DJI_0211`	imageomics/KABR-raw-videos/21_01_2023_session_5/

Note: Session numbers (as used in identifiers) are based on all KABR video sessions, while we focus in this dataset on Sessions 7, 5, and 3, which we label as Sessions ex-1, ex-2, and ex-3, respectively.

Dataset Structure


├── behavior/
│   ├── 18_01_2023_session_7-DJI_0068.csv
│   ├── 18_01_2023_session_7-DJI_0069.csv
│   ├── ...
│   ├── 21_01_2023_session_5-DJI_0211.csv
│   └── 21_01_2023_session_5-DJI_0212.csv
├── detections/
│   ├── 18_01_2023_session_7-DJI_0068.xml
│   ├── 18_01_2023_session_7-DJI_0069.xml
│   ├── ...
│   ├── 21_01_2023_session_5-DJI_0211.xml
│   └── 21_01_2023_session_5-DJI_0212.xml
├── mini_scenes/
│   ├── 18_01_2023_session_7-DJI_0068/
│   │   ├── 0.mp4
│   │   ├── 1.mp4
│   │   └── metadata/
│   │       ├── DJI_0068.jpg
│   │       ├── DJI_0068_metadata.json
│   │       └── DJI_0068_tracks.xml
│   ├── 18_01_2023_session_7-DJI_0069/
│   │   ├── 0.mp4
│   │   ├── 1.mp4
│   │   └── metadata/
│   │       ├── DJI_0069.jpg
│   │       ├── DJI_0069_metadata.json
│   │       └── DJI_0069_tracks.xml
│   ├── ...
│   ├── 21_01_2023_session_5-DJI_0211/
│   │   ├── 0.mp4
│   │   ├── ...
│   │   ├── 33.mp4
│   │   └── metadata/
│   │       ├── DJI_0211.jpg
│   │       ├── DJI_0211_metadata.json
│   │       └── DJI_0211_tracks.xml
│   └── 21_01_2023_session_5-DJI_0212/
│       ├── 0.mp4
│       ├── 10.mp4
│       ├── 11.mp4
│       ├── 12.mp4
│       ├── 13.mp4
│       ├── 14.mp4
│       ├── 1.mp4
│       ├── 2.mp4
│       ├── 3.mp4
│       ├── 4.mp4
│       ├── 5.mp4
│       ├── 6.mp4
│       ├── 7.mp4
│       ├── 8.mp4
│       ├── 9.mp4
│       └── metadata/
│           ├── DJI_0212.jpg
│           ├── DJI_0212_metadata.json
│           └── DJI_0212_tracks.xml
├── README.md
└── telemetry/
    ├── 18_01_2023-session_7-Flight_Airdata.csv
    ├── 20_01_2023-session_3-Flight_Airdata.csv
    └── 21_01_2023-session_5-Flight_Airdata.csv

Note: Each video has an associated video_id, which is defined as <DD>_01_2023_session_<session-number>-DJI_<video-number> (ex: 21_01_2023_session_5-DJI_0212). This ID is used to identify and link all (meta)data associated with that video.

What each file/folder is for

Path / Pattern	Purpose
`behavior/<video_id>.csv`	Per-video roll-ups of X3D behavior predictions. CSV containing one row per mini-scene clip with label + references (video, track, frame).
`detections/<video_id>.xml`	Manual detections/tracks per source video (CVAT “tracks” XML). One `<track>` per animal across frames; used to cut mini-scenes.
`mini_scenes/<video_id>/DJI_XXXX.mp4`	The source video referenced by detections for that `<video_id>`.
`mini_scenes/<video_id>/<k>.mp4`	Mini-scenes (short clips) cut from the source video based on detection tracks (`0.mp4`, `1.mp4`, …).
`mini_scenes/<video_id>/metadata/DJI_XXXX_tracks.xml`	Copy of the CVAT tracks used to generate the mini-scenes (provenance).
`mini_scenes/<video_id>/metadata/DJI_XXXX_metadata.json`	Video-level metadata (session/date, FPS, resolution, timing, etc.).
`mini_scenes/<video_id>/metadata/DJI_XXXX.jpg`	Thumbnail/keyframe for quick preview.
`mini_scenes/<video_id>/actions/`	Per-clip auto behavior labels from the X3D action model (CSV or JSON; presence varies by video).
`telemetry/<DD>_01_2023-session_<session-number>-Flight_Airdata.csv`	Drone flight logs (Airdata export) for the corresponding sessions (timing, altitude, battery, etc.).
`README.md`	Repository-level notes and usage tips.

Data instances

Detection instance (XML): one <track> spans all frames of a video; each <box> is a frame-level bounding box with coordinates and flags.
Mini-scene instance (MP4): a short clip indexed by file name (k.mp4) under mini_scenes/<video_id>/.
Behavior instance (CSV row): one mini-scene with X3D-predicted behavior and references to the clip (plus optional confidence/timing).
Telemetry instance (CSV row): one flight-log record from Airdata with timestamped vehicle context.

Data fields

A. Detections (CVAT “tracks” XML)

Element / Attribute	Type	Example	Meaning
`/annotations/version`	string	`1.1`	Annotation file (XML) version.
`/annotations/track@id`	integer	`0`	Unique id for a tracked object within the video.
`/annotations/track@label`	string	`Grevy`	Class/species label.
`/annotations/track@source`	string	`manual`	How the annotation was created. These are all `manual`.
`/annotations/track/box@frame`	int (0-based)	`0,1,2,…`	Frame index.
`/annotations/track/box@outside`	enum {`0`,`1`}	`0`	`0` present; `1` not visible.
`/annotations/track/box@occluded`	enum {`0`,`1`}	`0`	Occlusion flag (`1` indicates the subject is occluded).
`/annotations/track/box@keyframe`	enum {`0`,`1`}	`1`	Keyframe marker. Every 10th frame is considered a "keyframe" (CVAT default setting).
`/annotations/track/box@xtl`	float (px)	`2342.00`	X coordinate of top-left corner.
`/annotations/track/box@ytl`	float (px)	`2427.00`	Y coordinate of top-left corner.
`/annotations/track/box@xbr`	float (px)	`2530.00`	X coordinate of bottom-right corner.
`/annotations/track/box@ybr`	float (px)	`2623.00`	Y coordinate of bottom-right corner.
`/annotations/track/box@z_order`	integer	`0`	Drawing order.

B. Behavior CSV (auto labels; one file per source video)

Note: Column names may vary slightly by export; use the header in each CSV as ground truth.

Column (typical)	Example	Meaning
`clip_path` or `clip_id`	`mini_scenes/21_01_2023_session_5-DJI_0208/33.mp4`	Relative path to the mini-scene clip.
`source_video`	`DJI_0208.mp4`	Name of the parent/source video.
`video_id`	`21_01_2023_session_5-DJI_0208`	Folder/video identifier. This ID is used to identify and link all (meta)data associated with that source video.
`clip_index`	`33`	Index of the clip within the video folder.
`behavior`	`walking`	X3D-predicted action/behavior label.
`confidence`	`0.92`	Model confidence/probability (if provided).
`start_frame`	`1234`	First frame of the segment (if provided).
`end_frame`	`1450`	Last frame of the segment (if provided).
`start_time`	`00:00:41.2`	Segment start time (if provided).
`end_time`	`00:00:48.8`	Segment end time (if provided).
`species`	`Grevy`	Species label (if propagated/available). Only three potential labels: `Grevy`, `Plain Zebra`, or `Giraffe`.
`notes`	`—`	Free-text notes or flags (optional).
`model`	`x3d`	Model identifier used to label.
`model_version`	`x3d_m`	Specific checkpoint/version tag (optional).

C. Mini-scene metadata JSON (per source video)

Typical keys (presence may vary):

Key	Example	Meaning
`video_id`	`21_01_2023_session_5-DJI_0208`	Folder/video identifier. This ID is used to identify and link all (meta)data associated with that source video.
`source_video`	`DJI_0208.mp4`	Original MP4 filename.
`session_date`	`2023-01-21`	Capture date (`YYYY-MM-DD`).
`session_id`	`session_5`	Field session tag.
`fps`	`29.97`	Frames per second of recording.
`resolution`	`[3840, 2160]`	Width × height (px) (in list format).
`duration_s`	`123.45`	Video duration (seconds).
`timezone`	`Africa/Nairobi`	Local timezone of recording (UTC+3).
`generator`	`mini_scene_cutter@<git-sha>`	Tool/commit that wrote the metadata.
`tracks_xml`	`DJI_0208_tracks.xml`	Provenance link to the CVAT tracks file.

D. Telemetry CSV (Airdata export)

Columns depend on Airdata export settings; common fields include:

Column (common)	Example	Meaning
`UTC Timestamp`	`2023-01-21 12:49:07`	Log timestamp (UTC).
`Latitude` , `Longitude`	`0.28123`, `37.12345`	Aircraft location in decimal degrees.
`Altitude (m)`	`68.2`	Altitude (meters) above takeoff or MSL (per export).
`AGL (m)`	`47.9`	Above-ground level (in meters, if provided).
`Speed (m/s)`	`9.4`	Horizontal speed (meters per second).
`Heading (deg)`	`135`	Yaw/heading.
`Battery (%)`	`54`	Remaining battery percentage.
`FlyState`	`P-GPS`	This indicates high-level drone status, such as `Motors_Started`, `Assisted_Takeoff`, `P-GPS` (positioning-gps mode), `Landing`.
`Distance (m)`	`122.5`	Distance from home point (in meters). Specifically, Distance = current GPS - home point GPS.

Dataset Creation

Curation Rationale

Created to evaluate kabr-tools pipeline and conduct case studies on Grevy's landscape of fear and inter-species spatial distribution.

Source Data

Data Collection and Processing

Data collected at Mpala Research Centre, Kenya, in January 2023. The data was collected using a DJI Air 2S drone and manually annotated using CVAT. The annotations were exported as XML files.

Who are the source data producers?

Imageomics/KABR-raw-videos dataset authors.

Annotations

Annotation process

A local instance of CVAT was used to manually annotate the bounding boxes around animals in the videos. The annotations were then exported as XML files to create mini-scenes using tracks_extractor.py. The mini-scenes were then labeled with predicted behaviors using the KABR X3D action recognition model using the miniscene2behavior.py.

Who are the annotators?

Alison Zhong and Jenna Kline

Personal and Sensitive Information

Videos were trimmed (as needed) to remove people before annotation. Endangered species are included in the dataset, but no personal or sensitive information is included.

Considerations for Using the Data

Intended Use Cases

This dataset serves as a worked example for the kabr-tools pipeline and is specifically designed for:

Pipeline demonstration: Showing complete end-to-end processing from raw videos to behavioral annotations.
Method validation: Evaluating automated detection and behavior recognition against manual annotations.
Case study research: Supporting specific research questions on Grevy's zebra landscape of fear and inter-species spatial distribution.
Educational purposes: Teaching researchers how to use the kabr-tools pipeline with real data.
Reproducibility: Providing a reference implementation with known inputs and outputs.

Important Data Considerations

Limited scope: This is a demonstration dataset with only 3 sessions and 15 video files, designed to illustrate methodology rather than provide comprehensive coverage.

Session heterogeneity: Each example session represents distinctly different scenarios:

Session ex-1: Minimal complexity (2 male Grevy's zebras, open habitat)
Session ex-2: Moderate complexity (5 Grevy's zebras, semi-open roadway habitat)
Session ex-3: High complexity (mixed species, dense vegetation, 16 total animals)

Processing completeness: Not all videos have complete processing outputs - some lack actions/ folders, reflecting real-world pipeline execution variability.

Annotation methodology: Manual detections serve as ground truth, while behavior labels are X3D model predictions, not expert-validated behaviors.

Bias, Risks, and Limitations

Sample size limitations:

Only 15 video files across 3 sessions
Insufficient for statistical generalization
Designed for demonstration, not comprehensive analysis

Species representation bias:

Heavily weighted toward Grevy's zebras (endangered species focus)
Giraffes only present in one session (Session ex-3)
Plains zebras only in mixed-species context
May not represent typical behavioral patterns for each species

Habitat and temporal constraints:

Single location (Mpala Research Centre, Kenya)
3-day collection window (January 18-21, 2023)
Limited environmental and seasonal variability
Habitat types may not represent species' full range

Technical processing limitations:

X3D behavior predictions are automated, not expert-validated
Mini-scene extraction dependent on manual annotation quality
Telemetry synchronization with video timestamps may require adjustment
Some videos lack complete behavioral annotation outputs

Methodological constraints:

Manual annotations by only 2 annotators (potential inter-annotator variability)
CVAT tracking may have limitations in dense vegetation (Session ex-3)
Behavior model trained on different dataset, may not generalize perfectly

Recommendations

For pipeline evaluation and development:

Use manual detections in detections/*.xml as ground truth for automated detection validation
Compare processing outputs across sessions to understand pipeline performance in different scenarios
Use Session ex-1 (simple) for initial testing, Session ex-3 (complex) for stress testing
Validate timestamp alignment between telemetry and video data before spatial analysis

For case study research:

Landscape of fear studies: Focus on Grevy's zebra data from Sessions ex-1 and ex-2; use telemetry data to correlate spatial position with behaviors
Inter-species analysis: Use Session ex-3 mixed-species data; consider habitat complexity when interpreting interactions
Account for small sample sizes in statistical analyses and interpretation

For educational use:

Start with Session ex-1 data for learning pipeline basics
Progress through sessions in order of increasing complexity
Use metadata files to understand processing provenance
Examine both successful and incomplete processing examples

Technical recommendations:

Verify file completeness before analysis (not all videos have actions/ folders)
Check CSV headers as column names may vary between exports
Use metadata JSON files to understand video-specific processing parameters
Cross-reference telemetry timestamps with video timing for spatial-behavioral analysis

Data interpretation cautions:

Treat X3D behavior predictions as model outputs, not ground truth
Consider habitat context when interpreting behavioral patterns
Account for species-specific behavioral repertoires in analysis
Use this dataset to understand methodology, not to draw broad ecological conclusions

References

Original KABR mini-scene dataset: https://huggingface.co/datasets/imageomics/KABR
KABR Raw Videos (not processed for KABR mini-scene dataset): https://huggingface.co/datasets/imageomics/KABR-raw-videoss
kabr-tools repository: https://github.com/Imageomics/kabr-tools
Mpala Research Centre: https://mpala.org/

Licensing Information

This dataset is dedicated to the public domain for the benefit of scientific pursuits under the CC0 1.0 Universal Public Domain Dedication. We ask that you cite the dataset and related publications using the citations below if you make use of it in your research.

Citation

BibTeX:

Dataset

@misc{KABR_worked_examples,
  author = {Kline, Jenna and Zhong, Alison and Kholiavchenko, Maksim and Ramirez, Michelle and Stevens, Sam and Sheets, Alec and Babu, Reshma and Banerji, Namrata and Campolongo, Elizabeth and Thompson, Matthew and Van Tiel, Nina and Miliko, Jackson and Duporge, Isla and Rosser, Neil and Stewart, Charles and Berger-Wolf, Tanya and Rubenstein, Daniel},
  title = {{KABR} Worked Examples: Manually Annotated Detections and Behavioral Analysis for Kenyan Wildlife Pipeline Demonstration (Revision 43d7c45)},
  year = {2025},
  url = {https://huggingface.co/datasets/imageomics/kabr-worked-examples},
  publisher = {Hugging Face},
  doi = {10.57967/hf/7003}
}

Related Publications

@inproceedings{kholiavchenko2024kabr,
  title={KABR: In-Situ Dataset for Kenyan Animal Behavior Recognition from Drone Videos},
  author={Kholiavchenko, Maksim and Kline, Jenna and Ramirez, Michelle and Stevens, Sam and Sheets, Alec and Babu, Reshma and Banerji, Namrata and Campolongo, Elizabeth and Thompson, Matthew and Van Tiel, Nina and Miliko, Jackson and Bessa, Eduardo and Duporge, Isla and Berger-Wolf, Tanya and Rubenstein, Daniel and Stewart, Charles},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={31-40},
  year={2024}
}

kabr-tools manuscript (pre-print)

@misc{kline2025kabrtoolsautomatedframeworkmultispecies,
      title={kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring}, 
      author={Jenna Kline and Maksim Kholiavchenko and Samuel Stevens and Nina van Tiel and Alison Zhong and Namrata Banerji and Alec Sheets and Sowbaranika Balasubramaniam and Isla Duporge and Matthew Thompson and Elizabeth Campolongo and Jackson Miliko and Neil Rosser and Tanya Berger-Wolf and Charles V. Stewart and Daniel I. Rubenstein},
      year={2025},
      eprint={2510.02030},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2510.02030}
}

Please also cite the original data source:

KABR Raw Videos: https://huggingface.co/datasets/imageomics/KABR-raw-videos

Contributions

This work was supported by the Imageomics Institute, which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under Award #2118240 (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning). Additional support was provided by the AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE), funded by the US National Science Foundation under Award #2112606.

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

The raw data fed into the KABR tools pipeline to produce this worked example was collected at the Mpala Research Centre in Kenya, in accordance with Research License No. NACOSTI/P/22/18214. The data collection protocol adhered strictly to the guidelines set forth by the Institutional Animal Care and Use Committee under permission No. IACUC 1835F.

Dataset Creation Contributors

Data Collection: Field team at Mpala Research Centre, Kenya
Manual Annotations: Alison Zhong and Jenna Kline
Pipeline Development: kabr-tools development team
Behavioral Analysis: X3D model predictions using KABR-trained models
Data Curation: Alison Zhong and Jenna Kline
Quality Assurance: Imageomics Institute research team

Glossary

Mini-scene: Short video clips (typically 5-10 seconds) extracted from source videos, centered on individual animals based on tracking annotations.

Mo Kenya: A big hill to the north of Mpala.

CVAT: Computer Vision Annotation Tool - open-source software used for manual video annotation and object tracking.

X3D: 3D CNN architecture used for video-based action recognition, adapted for animal behavior classification in the KABR project. Model: Imageomics/X3D-KABR-Kinetics.

Track: A sequence of bounding boxes following a single animal across multiple video frames.

Telemetry: Flight data recorded by the drone during video capture, including GPS coordinates, altitude, speed, and battery status.

Session: A discrete data collection period, typically representing one flight or filming session on a specific date.

More Information

For detailed usage instructions and code examples, see the kabr-tools repository and associated docs.

For questions about the broader KABR project and related datasets, visit the Imageomics Institute website and see the KABR Collection.

This dataset is part of a larger effort to develop automated methods for wildlife monitoring and conservation using computer vision and machine learning techniques.