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.

数据集及其目录的组织结构类似于 PASCAL VOC 数据集，从而避免了修改现有脚本的需求，并使得检测框架能够将 PASCAL VOC 标注解析为其自身格式。JPEGImages 子目录包含用于训练、测试和验证的 1730 张图像（612x512 像素分辨率），每张图像至少包含一个标注的果实。Annotations 子目录包含所有标注文件（记录每张图像的边界框坐标），并以 xml 格式存储，与图像名称保持一致。Main 子目录包含一个文本文件，其中记录了用于训练、测试和验证的图像名称（不带扩展名）。训练集（train.txt）列出了 1300 张训练图像，验证集（val.txt）列出了 130 张验证图像，测试集（test.txt）列出了 300 张测试图像。每张图像都对应一个 XML 标注文件（文件名与图像名称相同），每个图像集（包括训练集、验证集和测试集）都附有相应的文本文件（train.txt、val.txt 和 test.txt），其中包含了用于训练和测试的图像名称列表。XML 标注文件包含了图像属性（名称、宽度、高度），以及对象属性（类别名称、对象边界框坐标（xmin, ymin, xmax, ymax））。其中，（xmin, ymin）和（xmax, ymax）分别表示边界框左上角和右下角的像素坐标。