Fine-grained automated visual analysis of herbarium specimens for phenological data extraction: an annotated dataset of reproductive organs in Strepanthus herbarium specimens

This dataset contains annotations of 31 herbarium specimens of Streptanhus tortuosus Kellogg for which we have we carefully and manually drew and annotated the contours of four reproductive organs: “bud”, “flower”, “immature fruit” and “mature fruit”.

The dataset can be used to assess the ability of automated methods to count and detect precisely the shapes of these reproductive organs, with a view to conducting phenological studies.

The annotations are formatted in accordance with the COCO data format, a usual format for object detection tasks in the field of Computer Vision. The annotations are divided into two files:

train_21_full_masks.json contains the mask coordinates and labels of 21 herbarium sheets that can be used for training models

test_10_full_masks.json contains the mask coordinates and labels of 10 other herbarium that can be used as a groundtruth file for evaluating the predictions, typically with the COCO evaluation scripts (https://github.com/cocodataset/cocoapi)

Please refer to the following publication for a first assessment of this dataset with a Mask-RCNN approach:

H. Goëau, A. Mora-Fallas, J. Champ, N. Love, S. Mazer, E. Mata-Montero, A. Joly, P. Bonnet. 2020. New fine-grained method for automated visual analysis of herbarium specimens: a case study for phenological data extraction. Applications in Plant Sciences