Download the preprocessed NYU Depth V2 dataset in HDF5 format and place it under a data folder outside the repo .
The NYU dataset requires 32G of storage space. gz tar -xvf nyudepthv2. gz && rm -f nyudepthv2. It is meant to be performed on a host machine with a CUDA GPU, not on an embedded platform. Deployment on an embedded device is discussed in the next section.
Play as a shark or a diver in a dark aquatic world and overcome your enemies by employing cunning, teamwork, and stealth. Depth blends tension and visceral action as you team up against AI or be matched with other players in heart pounding combat. Key featuresPlay as a sharkAs any one of 7 shark species, speed and senses are your greatest weapons. Stalk your prey from across the ocean and tear them in half with your razor sharp teeth.
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.
Single-view depth prediction is a fundamental problem in computer vision. Current datasets based on 3D sensors have key limitations, including indoor-only images (NYU), small numbers of training examples (Make3D), and sparse sampling (KITTI)
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Depth blends tension and visceral action as you team up against AI or be matched with other players in heart pounding combat.
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