MangoYOLO data set

Datasets and directories are structured similar to the PASCAL VOC dataset, avoiding the need to change scripts already available, with the detection frameworks ready to parse PASCAL VOC annotations into their format.

The sub-directory JPEGImages consist of 1730 images (612x512 pixels) used for train, test and validation. Each image has at least one annotated fruit.
The sub-directory Annotations consists of all the annotation files (record of bounding box coordinates for each image) in xml format and have the same name as the image name.
The sub-directory Main consists of the text file that contains image names (without extension) used for train, test and validation.
Training set (train.txt) lists 1300 train images
Validation set (val.txt) lists 130 validation images
Test set (test.txt) lists 300 test images

Each image has an XML annotation file (filename = image name) and each image set (training validation and test set) has associated text files (train.txt, val.txt and test.txt) containing the list of image names to be used for training and testing.
The XML annotation file contains the image attributes (name, width, height), the object attributes (class name, object bounding box co-ordinates (xmin, ymin, xmax, ymax)). (xmin, ymin) and (xmax, ymax) are the pixel co-ordinates of the bounding box’s top-left corner and bottom-right corner respectively.

本数据集的目录结构与PASCAL VOC数据集保持一致，无需修改现有可用脚本，且各类检测框架均可直接将PASCAL VOC格式的标注解析为适配该数据集的格式。

子目录JPEGImages包含1730张分辨率为612×512像素的图像，用于训练、测试与验证流程。每张图像均标注有至少一种水果。

子目录Annotations存储所有标注文件，所有标注均采用XML格式，且文件名与对应图像的文件名完全一致，用于记录每张图像的边界框坐标信息。

子目录Main包含若干文本文件，其中存储了用于训练、测试与验证的图像文件名（不含扩展名）。

训练集对应文本文件train.txt，共包含1300张训练图像；验证集对应val.txt，共包含130张验证图像；测试集对应test.txt，共包含300张测试图像。

每张图像均对应一个XML格式的标注文件，文件名与对应图像完全一致；而训练、验证与测试集分别配套有对应的文本文件（train.txt、val.txt与test.txt），其中存储了对应数据集所用的图像文件名列表。

XML标注文件包含图像属性（文件名、宽度、高度）以及目标属性（类别名称、边界框坐标(xmin, ymin, xmax, ymax)）。其中(xmin, ymin)与(xmax, ymax)分别为边界框左上角与右下角的像素坐标。