Published September 13, 2023 | Version v1
Dataset Open

Sim2real flower detection towards automated Calendula harvesting

  • 1. Technology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO)
  • 2. AIRO - IDLab, Ghent University - imec

Description

This dataset serves as supplementary material for the research paper titled 'Sim2real flower detection towards automated Calendula harvesting', which was published in the October 2023 issue of Biosystems Engineering. Within this upload, you will find a collection of both authentic and computer-generated images featuring Calendula (Calendula officinalis L.) flowers. Additionally, we have included the resources and original data utilized in generating the synthetic images. This dataset proves instrumental in demonstrating the successful transference of a deep neural network from simulation to real-world applications.

The contents of this upload includes:

  1. Original RGB and depth images of Calendula flowers captured in a natural flower field, complete with bounding box annotations.
  2. The test data employed in our experiments.
  3. Unedited RGB images that were used in the photogrammetry pipeline.
  4. Three-dimensional models representing Calendula flowers.
  5. The resulting dataset of synthetic images.

The synthetic dataset follows the Synthetic Optimized Labeled Objects (SOLO) Dataset Schema, as defined in the Unity Perception package. For completeness, the data scheme is also included in the upload.

For more comprehensive details regarding this dataset and its associated metadata, we invite you to consult the published article in Biosystems Engineering, available at the following link: https://doi.org/10.1016/j.biosystemseng.2023.08.016

Files

1_real_images.zip

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Additional details

Related works

Is supplement to
Journal article: 10.1016/j.biosystemseng.2023.08.016 (DOI)