This video dataset was created under NESTLER (oNe hEalth SusTainabiLity partnership between EU-AFRICA for food sEcuRity) Horizon Research Project, Funded by the European Union under Grant Agreement no.101060762. ------------------------------------------------------------------------------------------------------------------------------------------- The folder "Foxes-Vultures-Ravens-Jackals_Classification" contains videos of four animal classes, namely Foxes, Jackals, Ravens and Vultures. The videos were captured during day and night using RGB and InfraRed sensor cameras. It can be useful in identifying one of these four animals or it can be used along with other data utilizing each class as part of wider animal categories. The videos were captured at RAKOVO, Sliven region, Bulgaria, on 14-19 September 2024 by RINISOFT. For video capturing Foxes, Jackals and Ravens a HD Camera Balever BL480LP 4G was used and specifically for Foxes and Jackals videos were captured with a Night Vision mode. The video resolution for these categories was 1920x1080. For Vultures there was used a Digital Camera, Casio EX-H15 and a Fujifilm X-T4 with a video resolution set at 720p. -------------------------------------------------------------------------------------------------------------------------------------------- The dataset also contains videos of 12 classes of wild animals that can be found in Africa. Namely, the 12 classes are Baboons, Buffaloes, Elephant, Girafes, Gorillas, Hippopotamus, Impala, Lions, Rhinocerus, Topi, Warthog, Zebra. The importance of the dataset is obvious; it is a rare dataset since it is not easy to capture these wild animals at their natural environment. It may be dangerous to approach and visit these animals and also the road facilities are bad. The videos were captured with RGB cameras at Rwanda from RAB and Uganda from CTPH. -------------------------------------------------------------------------------------------------------------------------------------------- The folder "Elephants-Gorillas-Kobs_Detection_Dataset" contains the extracted frames which are accompanied by their respective bounding box annotations making this part of the dataset suitable for detection tasks. The videos were captured in Uganda at different periods of 2025 (January, February, June) using a HD camera (1920x1080) from CTPH. --------------------------------------------------------------------------------------------------------------------------------------------