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° vertically

This dataset was annotated and exported via www.roboflow.com

The 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，在西班牙南极科考行动PiMetAn第XXXIV次任务中，科研人员使用高度为30米的无人机（unmanned aerial vehicle, UAV）对欺骗岛的帽带企鹅（Chinstrap penguin, Pygoscelis antarcticus）聚居群落开展航拍作业。从获取的航拍影像中，构建了面向航拍视角的企鹅检测训练数据集。

该数据集的标注对象仅为帽带企鹅（Chinstrap penguin, Pygoscelis antarcticus）。

数据集包含三个文件夹："train"（内含531张图像，用于模型训练）、"valid"（内含50张图像，用于模型验证）以及"test"（内含25张图像，用于模型测试）。三个文件夹下均附带一个.csv格式文件，其中存储了以TensorFlow（Tensorflow）目标检测格式标注的标签信息，包含图像中每只企鹅的x、y坐标位置及类别名称。

仅设有一个标注类别：企鹅（Penguin）。

所有606张图像的尺寸均为224×224像素，分辨率为96 dpi。

为扩充数据集规模，对每张源图像生成3种变体，所采用的数据增强方式如下：
* 水平方向随机剪切角度范围为-18°至+18°，垂直方向随机剪切角度范围为-11°至+11°

本数据集通过www.roboflow.com平台完成标注与导出。

本次目标检测任务采用搭载ResNet-101骨干网络的Faster R-CNN64模型完成。模型的训练与评估工作基于谷歌开发的TensorFlow 2.0机器学习平台开展。