Small Object Dataset

Images of small objects for small instance detections. Currently four object types are available. ![]() We collect four datasets of small objects from images/videos on the Internet (e.g.YouTube or Google). Fly Dataset: contains 600 video frames with an average of 86 ± 39 flies per frame (648×72 @ 30 fps). 32 images are used for training (1:6:187) and 50 images for testing (301:6:600). Honeybee Dataset: contains 118 images with an average of 28 ± 6 honeybees per image (640×480). The dataset is divided evenly for training and test sets. Only the first 32 images are used for training. Fish Dataset: contains 387 frames of video with an average of 56±9 fish per frame (300×410 @ 30 fps). 32 images are used for training (1:3:94) and 65 for testing (193:3:387). Seagull Dataset: contains three high-resolution images (624×964) with an average of 866±107 seagulls per image. The first image is used for training, and the res

本数据集收录了小型物体图像，旨在进行小型实例检测。目前包含四种物体类型。数据集来源于互联网上的图像及视频资源（例如YouTube或Google）。其中，苍蝇数据集包含600帧视频图像，平均每帧图像含有86 ± 39只苍蝇（分辨率为648×72，帧率为30 fps），用于训练的图像为32张（比例1:6:187），用于测试的图像为50张（比例301:6:600）。蜜蜂数据集包含118张图像，平均每张图像含有28 ± 6只蜜蜂（分辨率为640×480），训练集和测试集平均分配。鱼数据集包含387帧视频图像，平均每帧图像含有56±9条鱼（分辨率为300×410，帧率为30 fps），用于训练的图像为32张（比例1:3:94），用于测试的图像为65张（比例193:3:387）。海鸥数据集包含三张高分辨率图像（分辨率为624×964），平均每张图像含有866±107只海鸥，其中第一张图像用于训练。