Split (1)

train

The full dataset viewer is not available (click to read why). Only showing a preview of the rows.

(ProtocolError('Connection aborted.', RemoteDisconnected('Remote end closed connection without response')), '(Request ID: 9459b669-ce7e-46d8-be4a-96c0464f8d32)')

Error code:   UnexpectedError

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

box_x1 float64	box_y1 float64	box_x2 float64	box_y2 float64	mask string
0.186	0.346269	0.266	0.495522	mask_0.npy
0.334375	0.466667	0.025	0.06875	mask_1.npy
0.428125	0.312941	0.346875	0.578824	mask_2.npy
0.853125	0.180769	0.104688	0.465385	mask_3.npy
0.39521	0.373438	0.157685	0.065625	mask_4.npy
0.207813	0.210773	0.120313	0.548009	mask_5.npy
0.7375	0.766667	0.234375	0.233333	mask_6.npy
0.125	0	0.873438	0.997664	mask_7.npy
0.591121	0.132813	0.03271	0.025	mask_8.npy
0.15	0.566667	0.089063	0.4	mask_9.npy
0.732813	0.009412	0.164063	0.597647	mask_10.npy
0.696262	0.545313	0.257009	0.073438	mask_11.npy
0.357813	0.410156	0.289063	0.544922	mask_12.npy
0	0	0.190625	0.398438	mask_13.npy
0.510938	0	0.457813	0.5875	mask_14.npy
0.1875	0	0.8125	0.997664	mask_15.npy
0.748438	0.572917	0.065625	0.177083	mask_16.npy
0.167188	0.227083	0.123438	0.3	mask_17.npy
0.242188	0.685417	0.159375	0.15625	mask_18.npy
0	0.43	0.090667	0.31	mask_19.npy
0.362998	0.254688	0.206089	0.473438	mask_20.npy
0.140625	0	0.859375	0.997917	mask_21.npy
0.507813	0.283433	0.171875	0.568862	mask_22.npy
0.221333	0.72	0.368	0.12	mask_23.npy
0.28125	0	0.173438	0.672917	mask_24.npy
0.340625	0.278119	0.321875	0.638037	mask_25.npy
0.659375	0.562061	0.035938	0.096019	mask_26.npy
0.828125	0.6	0.15	0.077083	mask_27.npy
0.285938	0.341253	0.504688	0.24622	mask_28.npy
0.064063	0	0.746875	0.722917	mask_29.npy
0.018	0.312312	0.266	0.684685	mask_30.npy
0.428125	0.479167	0.051563	0.114583	mask_31.npy
0.37605	0.61875	0.602941	0.229688	mask_32.npy
0.173438	0.292169	0.278125	0.587349	mask_33.npy
0.235938	0.25	0.2625	0.379167	mask_34.npy
0.440281	0.740625	0.236534	0.075	mask_35.npy
0.616495	0.382813	0.179381	0.214063	mask_36.npy
0.053125	0.344262	0.765625	0.449649	mask_37.npy
0.457813	0.595833	0.220313	0.302083	mask_38.npy
0.413146	0.179688	0.342723	0.376563	mask_39.npy
0	0	1	0.997653	mask_40.npy
0.40625	0.4125	0.067188	0.275	mask_41.npy
0.903125	0.69375	0.01875	0.072917	mask_42.npy
0	0.16875	0.9274	0.829688	mask_43.npy
0.495313	0.4125	0.0375	0.210417	mask_44.npy
0.066	0.602667	0.502	0.394667	mask_45.npy
0.181373	0.405229	0.20915	0.140523	mask_46.npy
0	-0.001916	1	1	mask_47.npy
0.790625	0	0.057813	0.223005	mask_48.npy
0.476563	0.527316	0.078125	0.472684	mask_49.npy
0.468384	0.03125	0.461358	0.967188	mask_50.npy
0.282813	0.147887	0.41875	0.849765	mask_51.npy
0.334895	0.423438	0.156909	0.059375	mask_52.npy
0.270313	0	0.089063	0.125	mask_53.npy
0.476563	0.489583	0.332813	0.289583	mask_54.npy
0.106667	0.014	0.84	0.664	mask_55.npy
0.090625	0.4375	0.28125	0.26875	mask_56.npy
0.082813	0.149883	0.346875	0.772834	mask_57.npy
0.490625	0.666667	0.2	0.166667	mask_58.npy
0	0.232	0.576	0.548	mask_59.npy
0.365625	0.172917	0.528125	0.391667	mask_60.npy
0.874183	0.480392	0.120915	0.156863	mask_61.npy
0.126563	0.400468	0.10625	0.12178	mask_62.npy
0.129688	0.521127	0.7125	0.399061	mask_63.npy
0.066946	0.20625	0.922594	0.63125	mask_64.npy
0.453125	0.504167	0.05625	0.147917	mask_65.npy
0.20625	0.41841	0.217188	0.257322	mask_66.npy
0.106024	0.308	0.498795	0.682	mask_67.npy
0.478	0.270463	0.06	0.434164	mask_68.npy
0.334375	0.385417	0.25	0.252083	mask_69.npy
0.425	0.513834	0.21875	0.411067	mask_70.npy
0.48125	0.341333	0.492188	0.648	mask_71.npy
0.53125	0.660422	0.23125	0.128806	mask_72.npy
0	0.43125	0.060938	0.0875	mask_73.npy
0.039063	0.176955	0.940625	0.72428	mask_74.npy
0	0.258333	0.998438	0.5125	mask_75.npy
0.214	0.521084	0.296	0.36747	mask_76.npy
0.455399	0.467188	0.028169	0.046875	mask_77.npy
0.332	0.372372	0.1	0.264264	mask_78.npy
0.140625	0.126953	0.740625	0.392578	mask_79.npy
0.165625	0.58548	0.276563	0.309133	mask_80.npy
0	0.091335	0.632813	0.906323	mask_81.npy
0.28103	0.545313	0.421546	0.215625	mask_82.npy
0.466	0.241791	0.322	0.564179	mask_83.npy
0.098	0.275689	0.254	0.679198	mask_84.npy
0.6125	0.50625	0.266667	0.176563	mask_85.npy
0	0.032787	0.360938	0.964871	mask_86.npy
0.142188	0.379958	0.701563	0.574113	mask_87.npy
0.145313	0.504695	0.023438	0.032864	mask_88.npy
0.072	0.227545	0.506	0.658683	mask_89.npy
0.751563	0.518868	0.048438	0.058962	mask_90.npy
0.09375	0.835509	0.296875	0.164491	mask_91.npy
0	0.057813	0.654167	0.940625	mask_92.npy
0.206	0.408	0.616	0.504	mask_93.npy
0	0	0.534375	0.841667	mask_94.npy
0.665625	0.203349	0.107813	0.349282	mask_95.npy
0.129688	0.474057	0.515625	0.363208	mask_96.npy
0.810938	0.216667	0.1875	0.485417	mask_97.npy
0.264	0.645333	0.036	0.133333	mask_98.npy
0.311111	0.440828	0.071111	0.177515	mask_99.npy

End of preview.