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Here we list the different releases of the nuImages dataset. Please register and login to download the nuImages dataset free of charge for non-commercial use, so that we can better track its usage. This dataset is also available at Registry of Open Data on AWS (as a part of nuScenes).
nuImages is a large-scale autonomous driving dataset with image-level 2d annotations. It features: 93k video clips of 6s each (150h of driving) 93k annotated and 1.1M un-annotated images. Two diverse cities: Boston and Singapore. The same proven sensor suite as in nuScenes. Images mined for diversity.
Dataset nuImages can be downloaded in Supervisely format: Download • 15.39 GB Download Sample • 425.37 MB As an alternative, it can be downloaded with dataset-tools package: pip install --upgrade dataset-tools … using following python code: import dataset_tools as dtools dtools.download(dataset= 'nuImages', dst_dir= '~/dataset-ninja/')
To download nuImages you need to go to the Download page, create an account and agree to the nuScenes Terms of Use. For the devkit to work you will need to download at least the metadata and samples, the sweeps are optional. Please unpack the archives to the /data/sets/nuimages folder
# !mkdir -p /data/sets/nuimages # Make the directory to store the nuImages dataset in. # !wget https://www.nuscenes.org/data/nuimages-v1.0-mini.tgz # Download the nuImages mini split. # !tar -xf nuimages-v1.0-mini.tgz -C /data/sets/nuimages # Uncompress the nuImages mini split. # !pip install nuscenes-devkit &> /dev/null # Install nuImages.
nuImages Also in 2020, we released nuImages, a brand new dataset. It comprises nearly 100,000 annotated images, carefully selected to generate a wide range of unpredictable, challenging driving conditions.
In nuImages, we annotate objects with 2d boxes, instance masks and 2d segmentation masks. All the labels and attributes from nuScenes are carried over into nuImages. We have also added more attributes in nuImages.
