v2.1.3

What's Changed

• 261 render lidar point clouds as images by @dpascualhe in #262
• Add functions to calculate Precision, Recall and F1score. by @Afreen-Kazi-1 in #255
• Add support for RUGD dataset by @dpascualhe in #264
• Update docs by @dpascualhe in #266
• Update metrics & improvements in datasets by @dpascualhe in #267

New Contributors

• @Afreen-Kazi-1 made their first contribution in #255

Full Changelog: v2.1.2...v2.1.3

v2.1.2

What's Changed

• Fixes #252- Add a How to Contribute Section by @vm7151810 in #250
• Add confusion matrix by @dpascualhe in #253
• Add image segmentation tutorial by @dpascualhe in #254
• Add support for native tensorflow and pytorch models by @dpascualhe in #260
• Computational cost estimation by @dpascualhe in #258

New Contributors

• @vm7151810 made their first contribution in #250

Full Changelog: v2.1.1...v2.1.2

v2.1.1

What's Changed

• Bump glob-parent and onchange in /docs by @dependabot in #227
• Add CLI by @dpascualhe in #249
• Increase version by @dpascualhe in #251

Full Changelog: v2.1.0...v2.1.1

v2.1.0

What's Changed

• Add support for LiDAR segmentation by @dpascualhe in #246. More specifically, added support for GOOSE and Rellis3D LiDAR segmentation datasets and PyTorch models (validated for RandLA-Net and KPConv from Open3D-ML.
• Update docs and increase version by @dpascualhe in #248

Full Changelog: v2.0.0...v2.1.0

v2.0.0

First release of DetectionMetrics v2. As stated in the new README:

DetectionMetrics has been redesigned with an expanded focus on image segmentation, with plans to extend support to object detection and LiDAR applications. As we move forward, v2 will be the actively maintained version, featuring continued updates and enhancements to keep pace with evolving AI and computer vision technologies.

Along with this release, we provide the detectionmetrics Python library packaged as sdist and wheel files.

v1.0.0

Original, published version of DetectionMetrics:

• 🎓 Open Source Assessment of Deep Learning Visual Object Detection (Paniego et al, 2022)
• 📖 https://jderobot.github.io/DetectionMetrics
• 🐳 https://hub.docker.com/r/jderobot/detection-metrics

@article{PaniegoOSAssessment2022,
  author = {Paniego, Sergio and Sharma, Vinay and Cañas, José María},
  title = {Open Source Assessment of Deep Learning Visual Object Detection},
  journal = {Sensors},
  volume = {22},
  year = {2022},
  number = {12},
  article-number = {4575},
  url = {https://www.mdpi.com/1424-8220/22/12/4575},
  pubmedid = {35746357},
  issn = {1424-8220},
  doi = {10.3390/s22124575},
  image = {/assets/img/pub_img/transformer_transform.png},
}

Continuous build

Travis CI build log: https://travis-ci.org/JdeRobot/DetectionSuite/builds/523148204

v0.1

Travis CI build log: https://travis-ci.org/JdeRobot/dl-DetectionSuite/builds/441099842/