Published: 12 April 2022| Version 2 | DOI: 10.17632/y5npsm3gkj.2
The TimberSeg 1.0 dataset is composed of 220 images showing wood logs in various environments and conditions in Canada. The images are densely annotated with segmentation masks for each log instance, as well as the corresponding bounding box and class label. This dataset aim towards enabling autonomous forestry forwarders, therefore it contains nearly 2500 instances of wood logs from an operators' point-of-view. Images were taken in the forest, near the roadside, in lumberyards and above timber-filled trailers. The logs were annotated considering a grasping perspective, meaning that only the logs above the piles and accessible are segmented.
Steps to reproduce
Check the paper's official repository for how to use the dataset.
Forestry, Deep Learning, Instance Segmentation