The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. It features:

1449 densely labeled pairs of aligned RGB and depth images 464 new scenes taken from 3 cities 407,024 new unlabeled frames Each object is labeled with a class and an instance number. The dataset has several components: Labeled: A subset of the video data accompanied by dense multi-class labels. This data has also been preprocessed to fill in missing depth labels. Raw: The raw RGB, depth and accelerometer data as provided by the Kinect. Toolbox: Useful functions for manipulating the data and labels.

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect 1449 densely labeled pairs of aligned RGB and depth images 464 new scenes taken from 3 cities 407,024 new unlabeled frames Each object is labeled with a class and an instance number (cup1, cup2, cup3, etc) The dataset has several components: Labeled: A subset of the video data accompanied by dense multi-class labels. This data has also been preprocessed to fill in missing depth labels. Raw: The raw rgb, depth and accelerometer data as provided by the Kinect. Toolbox: Useful functions for manipulating the data and labels. The raw dataset contains the raw image and accelerometer dumps from the kinect. The RGB and Depth camera sampling rate lies between 20 and 30 FPS (variable over time). While the frames are not synchronized, the timestamps for each of the RGB, depth and accelerometer files are included as part of each filename

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. It features:

• 1449 densely labeled pairs of aligned RGB and depth images
• 464 new scenes taken from 3 cities
• 407,024 new unlabeled frames
• Each object is labeled with a class and an instance number (cup1, cup2, cup3, etc)

This dataset is useful for various computer vision tasks, including depth estimation, semantic segmentation, and instance segmentation.

This Hugging Face version of the dataset is unofficial. It downloads the data from the original source and converts it to the Hugging Face format.

"The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. It features:

1449 densely labeled pairs of aligned RGB and depth images 464 new scenes taken from 3 cities 407,024 new unlabeled frames Each object is labeled with a class and an instance number. The dataset has several components: Labeled: A subset of the video data accompanied by dense multi-class labels. This data has also been preprocessed to fill in missing depth labels. Raw: The raw RGB, depth and accelerometer data as provided by the Kinect. Toolbox: Useful functions for manipulating the data and labels."