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Supported Media Formats#

Datumaro supports the following media types:

  • 2D RGB(A) images

  • Videos

  • KITTI Point Clouds

  • Tabular file (csv format)

To create an unlabelled dataset from an arbitrary directory with images use image_dir and image_zip formats:

cd </path/to/project>
datum project create
datum project import -f image_dir </path/to/directory/containing/images>

or, if you work with Datumaro API:

  • for using with a project:

    from datumaro.project import Project

project = Project.init('/path/to/project')
project.import_source('source1', format='image_dir', url='/path/to/directory/containing/images')
dataset = project.working_tree.make_dataset()

  • for using as a dataset:

    from datumaro import Dataset

dataset = Dataset.import_from('/path/to/directory/containing/images', 'image_dir')

This will search for images in the directory recursively and add them as dataset entries with names like <subdir1>/<subsubdir1>/<image_name1>. The list of formats matches the list of supported image formats in OpenCV:

.jpg, .jpeg, .jpe, .jp2, .png, .bmp, .dib, .tif, .tiff, .tga, .webp, .pfm,
.sr, .ras, .exr, .hdr, .pic, .pbm, .pgm, .ppm, .pxm, .pnm

Once there is a Dataset instance, its items can be split into subsets, renamed, filtered, joined with annotations, exported in various formats etc.

To import frames from a video, you can split the video into frames with the split_video command and then use the image_dir format described above. In more complex cases, consider using FFmpeg and other tools for video processing.

Alternatively, you can use the video_frames format directly:

Note, however, that it can produce different results if the system environment changes. If you want to obtain reproducible results, consider splitting the video into frames by any method.

cd </path/to/project>
datum project create
datum project import -f video_frames </path/to/video>

from datumaro import Dataset

dataset = Dataset.import_from('/path/to/video', 'video_frames')

Datumaro supports the following video formats:

.3gp, .3g2, .asf, .wmv, .avi, .divx, .evo, .f4v, .flv, .mkv, .mk3d,
.mp4, .mpg, .mpeg, .m2p, .ps, .ts, .m2ts, .mxf, .ogg, .ogv, .ogx,
.mov, .qt, .rmvb, .vob, .webm

Also, Daturamo supports a tabular format. A tabular dataset can be a single .csv file or a folder contains .csv files.

cd </path/to/project>
datum project create
datum project import -f tabular </path/to/tabular>

from datumaro import Dataset

dataset = Dataset.import_from('/path/to/tabular', 'tabular')
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