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Wild Berry image dataset collected in Finnish forests and peatlands using drones

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arxiv 2405.07550 v3 pith:4E4G5QDG submitted 2024-05-13 cs.CV

Luigi Riz , Sergio Povoli , Andrea Caraffa , Davide Boscaini , Mohamed Lamine Mekhalfi , Paul Chippendale , Marjut Turtiainen , Birgitta Partanen
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Laura Smith Ballester Francisco Blanes Noguera Alessio Franchi Elisa Castelli Giacomo Piccinini Luca Marchesotti Micael Santos Couceiro Fabio Poiesi
This is my paper · ORCID
classification cs.CV
keywords wildbeberrydronesberriescaptureddatasetdatasetsfinnish
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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. WildBe is publicly available on HuggingFace at https://huggingface.co/datasets/FBK-TeV/WildBe.

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