Skip to main content

End to end software to capture new objects using RGBD camera and augment them to get a annotated dataset to train deep nets.

Project description

Easy Augmentor

End to end software to capture new objects using RGBD camera and augment them to get a annotated dataset to train deep nets

  1. Pipeline to artificial generate annotated data for training deep learning models.
  2. Pipeline includes starting from capturing images using provided camera (Realsense), generate semantic labels of the captured image and then generate the artificial images.
  3. GUI required for the end user from capturing to labelling and generating new data.

Requirements

  1. Ubuntu 16.04 (Testing for Ubuntu 18.04)
  2. Intel Realsense Camera
  3. Processer intel i5 or higher
  4. libpcl-dev==1.7
  5. python 3.5

Limitations

  1. Number of classes captured should be more than or equal to 2.

Installation

Linux:

pip3 install easy-augmentor

Release History

  • 1.0.0
    • First release for crowd testing
  • 1.1.0
    • Now user can save RGB, pointcloud, depth, boundingbox, semantic label
    • Continous mode added

Contributors

Distributed under the MLP license. See LICENSE for more information.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

easy_augment-1.1.0-py3-none-any.whl (35.5 kB view details)

Uploaded Python 3

File details

Details for the file easy_augment-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: easy_augment-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 35.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.9.1 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.5.2

File hashes

Hashes for easy_augment-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 cfdcc20433a36b2757c17d857c84d7ea9ed6e6332b464d93606231eba7e4593e
MD5 8aeff4a28a73ec898b34cacae14d1c21
BLAKE2b-256 5e280acd1b251043c6ed39a8578a047176e21d49322660e0ac7cbffece19005d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page