Omkar2118/datasets huggingface dataset:
SemanticSpray Dataset

[Homepage](https://semantic-spray-dataset.github.io/) | [GitHub](https://github.com/aldipiroli/semantic_spray_dataset)

LiDARs are one of the main sensors used for autonomous driving applications, providing accurate depth estimation regardless of lighting conditions. However, they are severely affected by adverse weather conditions such as rain, snow, and fog.

This dataset provides semantic labels for a subset of the [Road Spray dataset](https://www.fzd-datasets.de/spray/), which contains scenes of vehicles traveling at different speeds on wet surfaces, creating a trailing spray effect. We provide semantic labels for over 200 dynamic scenes, labeling each point in the LiDAR point clouds as background (road, vegetation, buildings, ...), foreground (moving vehicles), and noise (spray, LiDAR artifacts). 

The SemanticSpray dataset contains scenes in wet surface conditions captured by Camera, LiDAR, and Radar.

The following label types are provided:

- **Camera**: 2D Boxes

- **LiDAR**: 3D Boxes, Semantic Labels

- **Radar**: Semantic Labels
10X PBMC (92k) Zheng et. al. 2017

The data is provided by 10x Genomics under "Single Cell 3' Paper: Zheng et al. 2017 (v1 Chemistry)" and consists of data from the following 9 cell types: CD4+/CD45RA+/CD25- naïve T cells, CD4+ helper T cells, CD4+/CD25+ regulatory T cells, CD4+/CD45RO+ memory T cells, CD8+/CD45RA+ naïve cytotoxic T cells, CD8+ cytotoxic T cells, CD56+ natural killer cells, CD34+ cells, and CD19+ B cells. The data contains 32738 genes and 92043 cells.