DeepFish: A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis

The dataset consists of approximately 40 thousand images collected underwater from 20 habitats in the marine-environments of tropical Australia.
The dataset originally contained only classification labels. Thus, we collected point-level and segmentation labels to have a more comprehensive fish analysis benchmark.
Videos for DeepFish were collected for 20 habitats from remote coastal marine environments of tropical Australia. These videos were acquired using cameras mounted on metal frames, deployed over the side of a vessel to acquire video footage underwater. The cameras were lowered to the seabed and left to record the natural fish community, while the vessel maintained a distance of 100 m. The depth and the map coordinates of the cameras were collected using an acoustic depth sounder and a GPS, respectively. Video recording was carried out during daylight hours and in relatively low turbidity periods. The video clips were captured in full HD resolution (1920 × 1080 pixels) from a digital camera. In total, the number of video frames taken is 39,766. 
The DeepFish dataset and code are publicly available at https://alzayats.github.io/DeepFish/ and https://github.com/alzayats/DeepFish, respectively.
The full methodology is available in the Open Access publication from the Related publications link below.

本数据集包含约4万张水下采集图像，采集自澳大利亚热带海域的20个海洋生境。
该数据集最初仅包含分类标签，因此我们补充采集了点级标签与分割标签，以构建更全面的鱼类分析基准测试集。
DeepFish数据集的视频采集自澳大利亚热带海域的20个远岸海洋生境。视频采集采用安装于金属支架上的相机，将支架部署于船舶舷侧以获取水下视频素材。相机被下放至海床，用于记录自然鱼类群落，此时船舶与相机保持100米的间距。相机的水深与地图坐标分别通过声学测深仪与GPS采集。视频录制于日间且选择浊度相对较低的时段进行，采用全高清（1920×1080像素）的数码相机拍摄视频片段。最终采集的视频帧总数为39766张。
DeepFish数据集与代码分别公开于以下网址：https://alzayats.github.io/DeepFish/ 与 https://github.com/alzayats/DeepFish。
完整的研究方法可通过下方「相关出版物」链接指向的开放获取论文获取。