YOLACT/YOLACT++ Docker images available

The first Docker images are available for the YOLACT (You Only Look At CoefficienTs) image segmentation model, using the 1.2 release:

github.com/waikato-datamining/yolact

YOLACT/YOLACT++, like MMDetection, is based on PyTorch. In contrast to MMDetection it is not a divers framework, but just a single model, which can make use of various base models (e.g., ResNet50). Similar to Mask R-CNN, it generates a mask with probabilities for each identified object, which requires post-processing to determine a polygon or minimal rectangle. However, it is much faster than the Mask R-CNN implementation that TensorFlow's Object Detection API offers (roughly 3x faster on 1000x300 images).

MMDetection Docker image available

The first Docker images are available for the MMDetection object detection framework, using the 2019-11-30 code base (close to 1.0rc1) of MMDetection:

github.com/waikato-datamining/mmdetection/tree/master/2019-11-30

MMDetection is based on PyTorch rather than TensorFlow and offers a larger number of pre-trained models and example configurations than TensorFlow's Object Detection API. It is developed by the Multimedia Laboratory of the Chinese University of Hong Kong.

First Releases

First release of our open-source Python library wai.annotations for converting various image annotation formats (licensed under Apache 2.0).

Our django plugin for managing teams and their projects, called simple-django-teams, is now publicly available as well (licensed under BSD-3).