Wild Berry image dataset collected in Finnish forests and peatlands using drones
CoRR(2024)
Abstract
Berry picking has long-standing traditions in Finland, yet it is challenging
and can potentially be dangerous. The integration of drones equipped with
advanced imaging techniques represents a transformative leap forward,
optimising harvests and promising sustainable practices. We propose WildBe, the
first image dataset of wild berries captured in peatlands and under the canopy
of Finnish forests using drones. Unlike previous and related datasets, WildBe
includes new varieties of berries, such as bilberries, cloudberries,
lingonberries, and crowberries, captured under severe light variations and in
cluttered environments. WildBe features 3,516 images, including a total of
18,468 annotated bounding boxes. We carry out a comprehensive analysis of
WildBe using six popular object detectors, assessing their effectiveness in
berry detection across different forest regions and camera types. We will
release WildBe publicly.
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