SEMFIRE forest dataset for semantic segmentation and data augmentation

SEMFIRE Datasets (Forest environment dataset)

These datasets are used for semantic segmentation and data augmentation and contain various forestry scenes. They were collected as part of the research work conducted by the Institute of Systems and Robotics, University of Coimbra team (https://www.isr.uc.pt/) within the scope of the Safety, Exploration and Maintenance of Forests with Ecological Robotics (SEMFIRE, ref. CENTRO-01-0247-FEDER-03269; http://semfire.ingeniarius.pt/) research project coordinated by Ingeniarius Ltd. (https://ingeniarius.pt/).

The semantic segmentation algorithms attempt to identify various semantic classes (e.g. background, live flammable materials, trunks, canopies etc.) in the images of the datasets.

The datasets include diverse image types, e.g. original camera images and their labeled images. In total the SEMFIRE datasets include about 1700 image pairs.

Description of each dataset:

1. 2019_2020_quinta_do_bolao_coimbra: Robot moving on a path through a forest environment
2. 2021_ctcv_parking_lot_coimbra: Robot moving in a circle in a parking lot for testings
3. 2021_sete_fontes_forest: A set of forest images acquired by hand-held apparatus

All datasets include a detailed description as a text file.

Description of directories in each dataset:

• img: includes original camera images
• lbl: single channel images (ground truth) with corresponding labels for each image in img
• lbl_colored: camera images in lbl colorized according to different semantic classes (for more details see the datasets descriptions)
• lbl_overlaid: camera images in img overlaid with corresponding labels (colored)

The following table shows the statistical description of typical portuguese woodland configurations with structured plantations of Pinus pinaster (Pp, pine trees) and Eucalyptus globulus (Eg, eucalyptus).