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+++ b/.gitattributes
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 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
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diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..25290ec7155c883e30c4d62b01abaca6ae63eb33
--- /dev/null
+++ b/README.md
@@ -0,0 +1,50 @@
+# 数据集介绍
+  ## 简介
+  nuScenes数据集是一个大规模的自动驾驶数据集。该数据集具有用于在波士顿和新加坡收集的1000场景的3D边界框。每个场景长20秒，注释为2Hz。这导致总共28130个用于训练的样本，6019个用于验证的样本和6008个用于测试的样本。该数据集具有完整的自动驾驶车辆数据套件: 32光束激光雷达，6个摄像头和具有完整360 ° 覆盖的雷达。3D对象检测挑战评估10个类别的性能: 汽车，卡车，公共汽车，拖车，建筑车辆，行人，摩托车，自行车，交通锥和障碍物。
+  ## 类定义
+  ```
+animal
+human.pedestrian.adult
+human.pedestrian.child
+human.pedestrian.construction_worker
+human.pedestrian.personal_mobility
+human.pedestrian.police_officer
+human.pedestrian.stroller
+human.pedestrian.wheelchair
+movable_object.barrier
+movable_object.debris
+movable_object.pushable_pullable
+movable_object.trafficcone
+static_object.bicycle_rack *
+vehicle.bicycle
+vehicle.bus.bendy
+vehicle.bus.rigid
+vehicle.car
+vehicle.construction
+vehicle.emergency.ambulance
+vehicle.emergency.police
+vehicle.motorcycle
+vehicle.trailer
+vehicle.truck
+flat.driveable_surface
+flat.other
+flat.sidewalk
+flat.terrain
+static.manmade
+static.other
+static.vegetation
+vehicle.ego
+noise
+```
+  ## 引文
+  ```
+@article{nuscenes2019,
+  title={nuScenes: A multimodal dataset for autonomous driving},
+  author={Holger Caesar and Varun Bankiti and Alex H. Lang and Sourabh Vora and 
+          Venice Erin Liong and Qiang Xu and Anush Krishnan and Yu Pan and 
+          Giancarlo Baldan and Oscar Beijbom},
+  journal={arXiv preprint arXiv:1903.11027},
+  year={2019}
+}
+```
+  ‌​‌‌​​​​‌​​​‌‌‌‌‌​​‌‌​‌​‌​​‌​​​‌‌​‌‌‌​‌‌‌​​‌‌‌‌​‌​​​‌​‌‌‌​​‌‌‌‌​‌​‌‌​​‌‌‌​​‌‌‌‌​‌​​‌‌‌​‌
\ No newline at end of file
diff --git a/metafile.yaml b/metafile.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7c384ce1c7482e009da387cca62cf4f5e6248835
--- /dev/null
+++ b/metafile.yaml
@@ -0,0 +1,19 @@
+displayName: nuScenes
+labelTypes:
+- Box3d
+license:
+- nuScenes Custom
+mediaTypes:
+- Image
+- PointCloud
+paperUrl: https://arxiv.org/pdf/1903.11027v5.pdf
+publishDate: "2020"
+publishUrl: https://www.nuscenes.org/
+publisher:
+- APTIV Company
+tags:
+- Pedestrian
+- Vehicle
+taskTypes:
+- 3D Object Detection
+‌​‌‌​​​​‌​​​‌‌‌‌‌​​‌‌​‌​‌​​‌​​​‌‌​‌‌‌​‌‌‌​​‌‌‌‌​‌​​​‌​‌‌‌​​‌‌‌‌​‌​‌‌​​‌‌‌​​‌‌‌‌​‌​​‌‌‌​‌
\ No newline at end of file
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