DSLR and Smartphone Camera-Based Plastic Waste Detection Dataset from Cox’s Bazar Sea Beach, Bangladesh

The Cox’s Bazar Beach Plastic Waste Detection Dataset (CoxPWD 2025) is an object detection dataset of 4,195 RGB images collected from Cox’s Bazar, Bangladesh. Images were captured at Kolatoli Beach, Sugandha Beach and Laboni Beach using an iPhone 15 Pro Max, Google Pixel 6 and Canon 650D under sunny, cloudy and rainy conditions during morning, noon and afternoon, with camera heights of approximately 1 m and 6 m and viewpoints of approximately 15° and 45° from the left and right to capture realistic variation in scale, occlusion, lighting and background. All images are stored as 640×640 JPEG files and annotated for bounding box object detection in COCO format with 14 plastic waste classes which are packet, polythene, cup, spoon, straw, rope, bag, bottle, bottle_cap, net, sunglass, toy, fishing_item and others. The dataset is split into 80 percent training (3,367 images), 10 percent validation (414 images) and 10 percent test (414 images) with a separate _annotations.coco.json file for each subset, making it directly usable for YOLOv8 and other deep learning models for coastal plastic waste monitoring and benchmarking.科克斯巴扎尔海滩塑料废弃物检测数据集（CoxPWD 2025）是一款目标检测数据集，共包含4195张RGB图像，采集自孟加拉国科克斯巴扎尔地区。图像分别在科拉托利海滩、苏甘达海滩与拉博尼海滩拍摄，拍摄设备涵盖苹果iPhone 15 Pro Max、谷歌Pixel 6及佳能650D（Canon 650D）；拍摄场景涵盖晴天、阴天与雨天，时段覆盖上午、中午及下午，相机高度设置为约1米与6米，从左右两侧以约15°和45°的视角进行拍摄，以真实还原尺度、遮挡、光照及背景的多样性变化。所有图像均存储为640×640的JPEG文件，采用COCO格式的边界框进行目标检测标注，共包含14类塑料废弃物：包装袋、聚乙烯薄膜、杯子、勺子、吸管、绳索、袋子、瓶子、瓶盖、渔网、太阳镜、玩具、渔具及其他。该数据集按80%训练集（3367张图像）、10%验证集（414张图像）、10%测试集（414张图像）的比例划分，每个子集均配有独立的_annotations.coco.json标注文件，可直接用于YOLOv8及其他深度学习模型的海岸塑料废弃物监测与基准测试。