Datasets:

target-bench
/

preprocessed_dataset

frame int64	image_timestamp int64	pos_x float64	pos_y float64	pos_z float64	quat_x float64	quat_y float64	quat_z float64	quat_w float64	interpolated bool
0	1,760,731,336,074,678,800	0.233617	0.015742	-0.046532	-0.004656	-0.044925	0.003607	0.998973	true
1	1,760,731,336,090,752,000	0.240926	0.014078	-0.053468	-0.004966	-0.046216	0.004059	0.998911	true
2	1,760,731,336,105,101,000	0.247452	0.012593	-0.05966	-0.005243	-0.047368	0.004463	0.998854	true
3	1,760,731,336,135,293,400	0.263158	0.017787	-0.05511	-0.004811	-0.045703	0.002894	0.998939	true
4	1,760,731,336,163,509,800	0.278673	0.026169	-0.043406	-0.003975	-0.042414	0.000401	0.999092	true
5	1,760,731,336,196,840,000	0.297001	0.036069	-0.029581	-0.002988	-0.038527	-0.002543	0.99925	true
6	1,760,731,336,228,889,000	0.314199	0.041087	-0.026051	-0.002726	-0.037173	-0.004366	0.999296	true
7	1,760,731,336,262,888,000	0.331891	0.04057	-0.034973	-0.003339	-0.038828	-0.004993	0.999228	true
8	1,760,731,336,304,239,000	0.353409	0.039941	-0.045825	-0.004085	-0.040841	-0.005755	0.999141	true
9	1,760,731,336,333,959,700	0.371313	0.043047	-0.04622	-0.00445	-0.040022	-0.00538	0.999174	true
10	1,760,731,336,372,563,000	0.396244	0.04953	-0.041644	-0.004805	-0.037401	-0.004258	0.99928	true
11	1,760,731,336,398,322,400	0.412879	0.053855	-0.038591	-0.005042	-0.035651	-0.003509	0.999345	true
12	1,760,731,336,434,770,000	0.436354	0.058621	-0.036893	-0.005421	-0.034954	-0.002484	0.999371	true
13	1,760,731,336,476,658,700	0.463269	0.062768	-0.03752	-0.005898	-0.035901	-0.00134	0.999337	true
14	1,760,731,336,499,786,200	0.47813	0.065057	-0.037867	-0.006162	-0.036424	-0.000708	0.999317	true
15	1,760,731,336,544,255,200	0.507805	0.054366	-0.043615	-0.006093	-0.03691	0.000697	0.9993	true
16	1,760,731,336,566,197,200	0.522672	0.046025	-0.047484	-0.005943	-0.037044	0.001428	0.999295	true
17	1,760,731,336,605,705,500	0.54944	0.031005	-0.054451	-0.005671	-0.037286	0.002746	0.999285	true
18	1,760,731,336,649,326,800	0.57048	0.035138	-0.049298	-0.004087	-0.035814	0.000985	0.99935	true
19	1,760,731,336,672,853,200	0.580485	0.040634	-0.044492	-0.00303	-0.034746	-0.000472	0.999391	true
20	1,760,731,336,706,002,700	0.594582	0.048378	-0.037722	-0.00154	-0.033241	-0.002524	0.999443	true
21	1,760,731,336,731,835,000	0.609859	0.046012	-0.036795	-0.001166	-0.033416	-0.002844	0.999437	true
22	1,760,731,336,761,803,000	0.630046	0.038443	-0.038216	-0.001182	-0.034392	-0.00248	0.999405	true
23	1,760,731,336,797,421,600	0.654038	0.029448	-0.039906	-0.001201	-0.035552	-0.002047	0.999365	true
24	1,760,731,336,833,660,000	0.676318	0.028558	-0.040837	-0.001864	-0.035238	-0.001624	0.999376	true
25	1,760,731,336,867,061,200	0.694997	0.03494	-0.041009	-0.003035	-0.033648	-0.00125	0.999428	true
26	1,760,731,336,895,290,600	0.710784	0.040334	-0.041154	-0.004025	-0.032304	-0.000934	0.99947	true
27	1,760,731,336,933,554,200	0.733896	0.043652	-0.043473	-0.004722	-0.031632	-0.000457	0.999488	true
28	1,760,731,336,964,978,000	0.755451	0.040379	-0.048563	-0.004327	-0.03281	0.000009	0.999452	true
29	1,760,731,336,997,346,000	0.777653	0.037007	-0.053806	-0.00392	-0.034022	0.000489	0.999413	true
30	1,760,731,337,034,923,000	0.799671	0.034417	-0.054549	-0.002968	-0.033656	0.000003	0.999429	true
31	1,760,731,337,067,169,300	0.815257	0.033361	-0.050482	-0.001729	-0.03178	-0.001332	0.999493	true
32	1,760,731,337,095,807,000	0.829099	0.032422	-0.046871	-0.000629	-0.030113	-0.002518	0.999543	true
33	1,760,731,337,132,780,300	0.851244	0.030348	-0.049683	-0.000379	-0.030619	-0.003795	0.999524	true
34	1,760,731,337,164,671,500	0.874314	0.027758	-0.059052	-0.001249	-0.033524	-0.004661	0.999426	true
35	1,760,731,337,195,417,900	0.896555	0.025261	-0.068084	-0.002089	-0.036324	-0.005497	0.999323	true
36	1,760,731,337,231,967,200	0.92224	0.023438	-0.071038	-0.002743	-0.037132	-0.004772	0.999295	true
37	1,760,731,337,270,549,500	0.948111	0.023397	-0.061337	-0.002867	-0.033833	-0.001178	0.999423	true
38	1,760,731,337,309,794,800	0.974427	0.023355	-0.051469	-0.002993	-0.030476	0.002478	0.999528	true
39	1,760,731,337,345,770,500	0.996632	0.020318	-0.050949	-0.003561	-0.030334	0.003421	0.999528	true
40	1,760,731,337,363,708,400	1.007561	0.018578	-0.051331	-0.003878	-0.030483	0.00371	0.999521	true
41	1,760,731,337,408,131,000	1.034624	0.014271	-0.052275	-0.004664	-0.030854	0.004427	0.999503	true
42	1,760,731,337,432,708,400	1.04663	0.012579	-0.052622	-0.004297	-0.030691	0.004555	0.999509	true
43	1,760,731,337,462,823,000	1.060048	0.010808	-0.05297	-0.003498	-0.03033	0.004596	0.999523	true
44	1,760,731,337,506,744,300	1.079617	0.008224	-0.053478	-0.002333	-0.029803	0.004655	0.999542	true
45	1,760,731,337,534,092,500	1.094552	0.007183	-0.057652	-0.001507	-0.030255	0.003567	0.999535	true
46	1,760,731,337,564,274,400	1.112242	0.006283	-0.063951	-0.000553	-0.031095	0.001873	0.999515	true
47	1,760,731,337,599,067,000	1.132633	0.005246	-0.071213	0.000548	-0.032064	-0.00008	0.999486	true
48	1,760,731,337,637,382,400	1.155493	0.004135	-0.069854	0.000801	-0.032986	-0.000253	0.999455	true
49	1,760,731,337,665,935,400	1.172732	0.003323	-0.064102	0.000504	-0.033599	0.00062	0.999435	true
50	1,760,731,337,698,380,500	1.192321	0.0024	-0.057567	0.000166	-0.034296	0.001611	0.99941	true
51	1,760,731,337,731,547,600	1.211444	0.001631	-0.055187	-0.000927	-0.03409	0.002197	0.999416	true
52	1,760,731,337,763,892,200	1.229232	0.001047	-0.056976	-0.002707	-0.033012	0.00236	0.999449	true
53	1,760,731,337,800,290,000	1.249248	0.00039	-0.058988	-0.00471	-0.031798	0.002544	0.99948	true
54	1,760,731,337,835,595,300	1.271473	-0.001088	-0.06045	-0.005129	-0.032367	0.002972	0.999458	true
55	1,760,731,337,865,460,500	1.291891	-0.002821	-0.061405	-0.004606	-0.033852	0.003477	0.99941	true
56	1,760,731,337,897,713,400	1.31394	-0.004693	-0.062436	-0.004042	-0.035456	0.004023	0.999355	true
57	1,760,731,337,932,064,000	1.332362	-0.002965	-0.063518	-0.002855	-0.035448	0.003197	0.999362	true
58	1,760,731,337,973,950,000	1.34892	0.003482	-0.06482	-0.000725	-0.033436	0.00055	0.99944	true
59	1,760,731,338,000,267,000	1.359324	0.007533	-0.065638	0.000614	-0.032172	-0.001113	0.999482	true
60	1,760,731,338,032,982,000	1.377032	0.008961	-0.067868	0.001415	-0.032701	-0.002461	0.999461	true
61	1,760,731,338,065,096,400	1.398033	0.007628	-0.070976	0.001548	-0.034812	-0.003239	0.999387	true
62	1,760,731,338,100,284,400	1.421043	0.006168	-0.074382	0.001694	-0.037125	-0.004092	0.999301	true
63	1,760,731,338,145,454,600	1.451167	0.003897	-0.074312	0.00092	-0.037	-0.002712	0.999311	true
64	1,760,731,338,181,652,700	1.475522	0.001931	-0.072619	-0.000054	-0.03576	-0.000694	0.99936	true
65	1,760,731,338,200,186,600	1.487993	0.000924	-0.071752	-0.000553	-0.035125	0.00034	0.999383	true
66	1,760,731,338,241,270,300	1.511039	0.000965	-0.066786	-0.001296	-0.034135	0.002048	0.999414	true
67	1,760,731,338,263,356,400	1.522018	0.001685	-0.063183	-0.001583	-0.033731	0.002787	0.999426	true
68	1,760,731,338,295,015,200	1.537754	0.002717	-0.058017	-0.001996	-0.033152	0.003847	0.999441	true
69	1,760,731,338,339,679,700	1.561752	0.00331	-0.057594	-0.001847	-0.033112	0.003353	0.999444	true
70	1,760,731,338,366,121,200	1.576786	0.003263	-0.06051	-0.001421	-0.033448	0.002145	0.999437	true
71	1,760,731,338,398,445,600	1.595165	0.003207	-0.064074	-0.000901	-0.033857	0.000667	0.999426	true
72	1,760,731,338,447,163,000	1.618151	0.002729	-0.065454	0.000783	-0.033255	-0.000935	0.999446	true
73	1,760,731,338,466,523,000	1.626205	0.00245	-0.065088	0.001659	-0.032736	-0.001428	0.999462	true
74	1,760,731,338,507,314,200	1.643175	0.001862	-0.064316	0.003505	-0.031642	-0.002468	0.99949	true
75	1,760,731,338,538,179,300	1.661767	0.000664	-0.066323	0.003131	-0.032845	-0.002558	0.999452	true
76	1,760,731,338,577,707,000	1.688263	-0.00122	-0.070104	0.001825	-0.035333	-0.002349	0.999371	true
77	1,760,731,338,600,339,000	1.703433	-0.002298	-0.072269	0.001077	-0.036757	-0.00223	0.999321	true
78	1,760,731,338,632,237,000	1.721249	-0.002906	-0.07163	0.00007	-0.037026	-0.00128	0.999313	true
79	1,760,731,338,665,895,700	1.736203	-0.002562	-0.06698	-0.000941	-0.035433	0.000565	0.999371	true
80	1,760,731,338,708,300,800	1.755044	-0.00213	-0.06112	-0.002215	-0.033427	0.002888	0.999435	true
81	1,760,731,338,743,057,700	1.775862	-0.000779	-0.060032	-0.001973	-0.033929	0.002979	0.999418	true
82	1,760,731,338,768,200,200	1.791908	0.000381	-0.059926	-0.001563	-0.034687	0.002711	0.999393	true
83	1,760,731,338,798,774,800	1.81142	0.001791	-0.059798	-0.001063	-0.035608	0.002386	0.999362	true
84	1,760,731,338,836,008,000	1.831981	0.003234	-0.060957	0.000111	-0.035303	0.001355	0.999376	true
85	1,760,731,338,871,220,200	1.849191	0.004405	-0.062971	0.001616	-0.034019	-0.000063	0.99942	true
86	1,760,731,338,911,522,600	1.868888	0.005746	-0.065276	0.003339	-0.032548	-0.001685	0.999463	true
87	1,760,731,338,950,162,700	1.893647	0.00368	-0.068896	0.001762	-0.034537	-0.002898	0.999398	true
88	1,760,731,338,967,912,700	1.905251	0.002599	-0.070615	0.00091	-0.035584	-0.003442	0.99936	true
89	1,760,731,338,999,039,500	1.925601	0.000704	-0.073628	-0.000583	-0.03742	-0.004395	0.99929	true
90	1,760,731,339,037,257,500	1.948057	-0.00016	-0.073877	-0.001363	-0.037578	-0.00424	0.999284	true
91	1,760,731,339,062,124,500	1.961328	0.000053	-0.072209	-0.001311	-0.036571	-0.003437	0.999324	true
92	1,760,731,339,097,367,000	1.980135	0.000356	-0.069846	-0.001238	-0.035143	-0.002299	0.999379	true
93	1,760,731,339,133,000,700	1.999591	0.002581	-0.067895	-0.001115	-0.034669	-0.001069	0.999398	true
94	1,760,731,339,165,755,600	2.017859	0.006298	-0.066484	-0.000959	-0.035079	0.000129	0.999384	true
95	1,760,731,339,198,478,600	2.036109	0.010012	-0.065074	-0.000803	-0.035489	0.001326	0.999369	true
96	1,760,731,339,235,247,400	2.054694	0.011174	-0.06487	-0.000387	-0.035302	0.001501	0.999375	true
97	1,760,731,339,265,411,800	2.068539	0.009935	-0.065708	0.000131	-0.034677	0.000792	0.999398	true
98	1,760,731,339,298,103,600	2.083545	0.008592	-0.066617	0.000692	-0.034	0.000024	0.999422	true
99	1,760,731,339,335,717,400	2.102154	0.00821	-0.066101	0.001637	-0.033554	-0.001442	0.999435	true

End of preview. Expand in Data Studio

This repo gives preprocessed dataset that contains front camera videos and groundtruth trajectories created based on our SLAM framework.

Downloads last month: 155

Size of downloaded dataset files:

15.9 MB

Size of the auto-converted Parquet files:

15.9 MB

Number of rows:

169,795