Datasets:

katospiegel
/

ordfts-hackathon-pneuma-vehicles-segmentation

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train · 273 rows

Time [s] float32 80 80.4	id int32 5 379	Type stringclasses 6 values	x_img [px] int32 55 3.78k	y_img [px] int32 4 2.03k	Angle_img [rad] float32 0 6.28	Frame stringclasses 2 values
80	339	Car	2,422	1,133	1.58	00001
80	341	Car	2,414	424	1.56	00001
80	342	Motorcycle	1,522	1,491	4.61	00001
80	343	Car	2,755	531	3.21	00001
80	345	Motorcycle	1,509	1,492	4.7	00001
80	346	Car	860	1,394	0.02	00001
80	348	Motorcycle	2,406	1,270	1.57	00001
80	349	Car	3,089	1,428	6.27	00001
80	350	Car	903	1,376	0.01	00001
80	351	Car	2,658	1,419	0.01	00001
80	352	Taxi	2,887	1,426	4.32	00001
80	353	Car	1,503	705	4.66	00001
80	354	Motorcycle	1,227	1,387	0.01	00001
80	355	Motorcycle	2,869	586	4.07	00001
80	356	Heavy Vehicle	3,055	541	3.12	00001
80	357	Car	775	1,369	6.28	00001
80	358	Taxi	2,721	1,440	6.26	00001
80	359	Motorcycle	3,161	536	3.17	00001
80	360	Car	666	1,367	0.01	00001
80	361	Motorcycle	2,410	1,937	1.57	00001
80	362	Car	2,906	1,655	4.68	00001
80	363	Car	2,160	542	3.15	00001
80	364	Car	517	1,365	0.01	00001
80	365	Motorcycle	2,892	1,658	4.67	00001
80	366	Motorcycle	759	1,396	0.05	00001
80	367	Motorcycle	2,916	1,706	4.76	00001
80	368	Car	387	1,366	0.02	00001
80	369	Car	3,485	535	3.12	00001
80	371	Bus	260	1,407	0.03	00001
80	372	Car	3,613	544	3.15	00001
80	373	Car	124	521	3.16	00001
80	374	Bus	2,934	1,948	4.71	00001
80	375	Motorcycle	2,470	556	2.64	00001
80	376	Motorcycle	1,463	459	0.86	00001
80	377	Taxi	3,734	532	3.15	00001
80	378	Car	55	1,366	0.04	00001
80	379	Car	2,903	2,032	4.67	00001
80.400002	5	Taxi	1,965	573	4.77	00002
80.400002	21	Car	1,599	1,016	5.59	00002
80.400002	22	Car	3,400	1,453	6.16	00002
80.400002	25	Car	3,127	1,499	0.75	00002
80.400002	26	Medium Vehicle	1,474	1,173	4.53	00002
80.400002	31	Motorcycle	1,079	508	3.12	00002
80.400002	32	Motorcycle	3,247	782	5.01	00002
80.400002	33	Medium Vehicle	2,462	203	1.86	00002
80.400002	34	Car	1,654	1,021	3.05	00002
80.400002	40	Car	522	497	2.42	00002
80.400002	65	Taxi	1,496	4	4.69	00002
80.400002	67	Car	1,983	1,196	3.58	00002
80.400002	87	Car	2,456	825	2.08	00002
80.400002	94	Car	1,495	270	4.75	00002
80.400002	95	Car	1,493	225	4.73	00002
80.400002	103	Car	3,775	510	3.01	00002
80.400002	104	Car	2,461	771	2.31	00002
80.400002	105	Motorcycle	464	1,446	0.04	00002
80.400002	106	Car	2,299	513	3.05	00002
80.400002	108	Car	2,674	1,506	1.02	00002
80.400002	115	Bus	2,940	1,661	4.06	00002
80.400002	116	Motorcycle	1,449	1,250	1.64	00002
80.400002	122	Heavy Vehicle	2,937	509	3.11	00002
80.400002	127	Car	1,984	948	3.57	00002
80.400002	132	Medium Vehicle	3,009	511	3.14	00002
80.400002	139	Car	1,140	545	3.33	00002
80.400002	148	Taxi	1,497	938	4.71	00002
80.400002	151	Car	1,502	752	4.72	00002
80.400002	160	Car	3,509	1,362	0	00002
80.400002	171	Taxi	2,185	1,418	0.02	00002
80.400002	176	Taxi	1,496	615	4.73	00002
80.400002	187	Car	1,499	655	4.69	00002
80.400002	190	Car	2,834	1,330	4.57	00002
80.400002	192	Car	1,493	796	4.69	00002
80.400002	194	Car	2,419	1,803	1.58	00002
80.400002	196	Car	2,644	1,397	6.26	00002
80.400002	199	Motorcycle	1,485	431	4.73	00002
80.400002	203	Car	2,609	1,422	0.05	00002
80.400002	206	Bus	1,422	1,421	6.27	00002
80.400002	212	Motorcycle	1,616	1,374	6.24	00002
80.400002	213	Car	1,543	1,372	0.01	00002
80.400002	218	Car	2,608	1,376	6.23	00002
80.400002	227	Motorcycle	2,736	1,370	6.09	00002
80.400002	230	Taxi	3,474	1,434	0.04	00002
80.400002	231	Taxi	2,697	1,406	0.03	00002
80.400002	232	Taxi	2,320	1,373	6.28	00002
80.400002	233	Taxi	1,951	1,417	6.28	00002
80.400002	234	Taxi	1,499	324	4.68	00002
80.400002	235	Taxi	1,501	410	4.74	00002
80.400002	241	Medium Vehicle	1,292	532	3.09	00002
80.400002	242	Motorcycle	1,506	196	4.73	00002
80.400002	243	Motorcycle	733	516	3.15	00002
80.400002	244	Car	1,361	1,370	0.02	00002
80.400002	253	Motorcycle	2,440	1,803	0.62	00002
80.400002	256	Medium Vehicle	3,014	510	3.1	00002
80.400002	257	Motorcycle	2,502	550	3.11	00002
80.400002	262	Motorcycle	1,728	1,394	0	00002
80.400002	263	Motorcycle	2,211	1,403	0.09	00002
80.400002	264	Motorcycle	1,787	1,384	0.01	00002
80.400002	265	Car	1,863	1,396	0.01	00002
80.400002	271	Car	306	522	3.11	00002
80.400002	276	Motorcycle	2,756	1,394	0.06	00002
80.400002	280	Car	3,485	1,406	0.04	00002