Training dataset for object detection - Penguins from UAV

On February 8, 2021, Deception Island Chinstrap penguin colonies were photographed during the PiMetAn Project XXXIV Spanish Antarctic campaign using unmanned aerial vehicles (UAV) at a height of 30m. From the obtained imagery, a training dataset for penguin detection from aerial perspective was generated. The penguin species is the Chinstrap penguin (Pygoscelis antarcticus).The dataset consists of three folders: "train", containing 531 images, intended for model training; "valid", containing 50 images, intended for model validation; and "test", containing 25 images, intended for model testing. In each of the three folders, an additional .csv file is located, containing labels (x,y positions and class names for every penguin in the images), annotated in Tensorflow Object Detection format.There is only one annotation class: Penguin.All 606 images are 224x224 px in size, and 96 dpi. The following augmentation was applied to create 3 versions of each source image:* Random shear of between -18° to +18° horizontally and -11° to +11° verticallyThis dataset was annotated and exported via www.roboflow.comThe model Faster R-CNN64 with ResNet-101 backbone was used to perform object detection tasks. Training and evaluation tasks were performed using the TensorFlow 2.0 machine learning platform by Google.

2021年2月8日，在西班牙南极考察项目PiMetAn XXXIV期间，研究人员使用无人驾驶飞行器（UAV）从30米高度拍摄了欺骗岛（Deception Island）的帽带企鹅（Chinstrap penguin）栖息地。基于获取的影像，研究人员构建了一个用于从空中视角检测企鹅的训练数据集。该数据集针对的企鹅物种为帽带企鹅（学名Pygoscelis antarcticus）。数据集包含三个文件夹："train"（含531张图像，用于模型训练）、"valid"（含50张图像，用于模型验证）和"test"（含25张图像，用于模型测试）。每个文件夹中均包含一个额外的.csv文件，其中记录了图像中所有企鹅的标注信息（包括坐标位置（x,y）和类别名称），标注格式遵循TensorFlow Object Detection规范。标注类别仅有一种：企鹅。所有606张图像的尺寸均为224×224像素，分辨率为96 dpi。为生成每张源图像的3个版本，研究人员对图像进行了以下数据增强操作：* 水平方向-18°至+18°的随机剪切，以及垂直方向-11°至+11°的随机剪切。该数据集的标注和导出通过www.roboflow.com完成。研究人员使用基于ResNet-101骨干网络的Faster R-CNN64模型执行目标检测任务，训练和评估任务通过谷歌（Google）的TensorFlow 2.0机器学习平台完成。