Package: nvdu
Nvidia Dataset Utilities (NVDU)This project is a collection of Python scripts to help work with datasets for deep learning.  For example, visualizing annotation data associated with captured sensor images generated by NVIDIA Deep learning Dataset Synthesizer (NDDS)https://github.com/NVIDIA/Dataset_Synthesizer.This module depends on OpenCV-python which currently doesn't work with Python 3.7.Example of a dataset frame visualized using NVDU, showing axes and 3D cuboids for annotated objects.Table of ContentsNvidia Dataset Utilities (NVDU)Table of ContentsInstallInstall from pip:Install from source code git repo:nvdu_ycbUsagenvdu_vizUsageExamplesVisualize a dataset generated by NDDS:Visualize a set of images using different annotation data:ControlsVisualization options:Other:InstallInstall from pip:pip install nvduInstall from source code git repo:Clone the repoUsing ssh path:git clone ssh://git@github.com:12051/NVIDIA/Dataset_Utilities.gitUsing https path:git clone https://github.com/NVIDIA/Dataset_Utilities.gitGo inside the cloned repo's directorycd Dataset_UtilitiesInstall locallypip install -e .nvdu_ycbnvdu_ycbcommand help download, extract and align the YCB 3d models (which are used in the FAT dataset:http://research.nvidia.com/publication/2018-06_Falling-Things).Usageusage: nvdu_ycb [-h] [-s] [-l] [ycb_object_name]

NVDU YCB models Support

positional arguments:
  ycb_object_name  Name of the YCB object to check.

optional arguments:
  -h, --help       show this help message and exit
  -s, --setup      Setup the YCB models for the FAT dataset
  -l, --list       List all the supported YCB objectsNOTE: If you don't run thenvdu_ycb --setupbefore trying to use nvdu_viz, the visualizer will not be able to find the 3d models of the YCB object to overlay.nvdu_viznvdu_vizcommand visualizes the annotated datasets using the NDDS format.Usagenvdu_viz [-h] [-a DATA_ANNOT_DIR] [-s SIZE SIZE]
                [-o OBJECT_SETTINGS_PATH] [-c CAMERA_SETTINGS_PATH]
                [-m MODEL_DIR] [-n [NAME_FILTERS [NAME_FILTERS ...]]]
                [--fps FPS] [--auto_change] [-e EXPORT_DIR] [--auto_export]
                [--ignore_fixed_transform]
                [dataset_dir]

NVDU Data Visualiser

positional arguments:
  dataset_dir           Dataset directory. This is where all the images
                        (required) and annotation info (optional) are.
                        Defaults to the current directory.

optional arguments:
  -h, --help            show this help message and exit.
  -a DATA_ANNOT_DIR, --data_annot_dir DATA_ANNOT_DIR
                        Directory path - where to find the annotation data.
                        Defaults to be the same directory as the dataset
                        directory.
  -s SIZE SIZE, --size SIZE SIZE
                        Window's size: [width, height]. If not specified then
                        the window is sized to fit the resolution of the camera.
  -o OBJECT_SETTINGS_PATH, --object_settings_path OBJECT_SETTINGS_PATH
                        Object settings file path.
  -c CAMERA_SETTINGS_PATH, --camera_settings_path CAMERA_SETTINGS_PATH
                        Camera settings file path.
  -n [NAME_FILTERS [NAME_FILTERS ...]], --name_filters [NAME_FILTERS [NAME_FILTERS ...]]
                        The name filter of each frame. e.g: *.png.
  --fps FPS             How fast to automatically change frame.
  --auto_change         When using this flag, the visualizer will automatically
                        change the frame.
  -e EXPORT_DIR, --export_dir EXPORT_DIR
                        Directory path - where to store the visualized images.
                        If this is set, the script will automatically export
                        the visualized image to the export directory.
  --auto_export         When using this flag, the visualizer will automatically
                        export the visualized frame to an image file in the
                        `export_dir` directory.
  --ignore_fixed_transform
                        When using this flag, the visualizer will not use the
                        fixed transform matrix for the 3d model.NOTE: Thenvdu_vizscript can work from any directoryExamplesVisualize a dataset generated by NDDS:Visualize the current directory:nvdu_vizVisualize a relative path:nvdu_viz ../a_datasetVisualize an absolute path:nvdu_viz ~/data/datasetVisualize different aspect of a frame using a filter:nvdu_viz dataset_path --name_filters *.left.png *.right.pngVisualize a set of images using different annotation data:The camera and object settings files are in the image directory:nvdu_viz image_directory_here -a annotation_directory_hereThe camera and object settings files are NOT in the image directory:nvdu_viz image_directory_here -a annotation_directory_here -c camera_setting_path_here -o object_setting_path_hereControlsVisualization options:F3 - Toggle the 2d cuboid
F4 - Toggle the 3d cuboid
F5 - Toggle the 3d models
F6 - Toggle the axes
F7 - Toggle the overlay frame name
1 - Render the 3d models normally
2 - Render the 3d models using only the edge lines
3 - Render the 3d models as point cloudsOther:ESC - Quit the visualizer
Right - Go to the next frame
Left - Go to the previous frame
Up - Go to the next 100 frame
Down - Go to the previous 100 frame
Space - Toggle frame auto-changing
F12 - Toggle exporting the visualized frame to file