A dataset of floating waste and river vegetation images collected from turbid rivers in Banjarmasin, Indonesia.

This dataset contains images of floating waste and river vegetation collected from several turbid river locations in Banjarmasin, South Kalimantan, Indonesia. The dataset combines still photographs and image frames extracted from video recordings, with video frames extracted at approximately one frame per second. The collected images were manually screened to remove images that did not contain relevant objects before annotation. The final dataset consists of 1,577 unique RGB images containing two object categories, namely floating waste and river vegetation. Each image was manually annotated using bounding boxes and stored in YOLO annotation format with object class identifiers and normalized bounding box coordinates. The dataset contains 5,792 annotated object instances, comprising 3,718 floating waste instances and 2,074 river vegetation instances. The dataset is partitioned into training, validation, and testing subsets containing 1,104, 315, and 158 images, respectively. The partitioning was performed using a group-aware strategy to ensure that images originating from the same video source were kept within the same subset. The dataset is intended to support computer vision, object detection, and environmental monitoring research under challenging turbid river conditions.