[Software tool] Genie labeling assistant target detection data set format to VOC or yolo

Sometimes we get a data set and find that the xml file format is as follows:

<?xml version="1.0" ?>
<doc>
	<path>C:\Users\Administrator\Desktop\test\000000000074.jpg</path>
	<outputs>
		<object>
			<item>
				<name>dog</name>
				<bndbox>
					<xmin>64</xmin>
					<ymin>271</ymin>
					<xmax>361</xmax>
					<ymax>385</ymax>
				</bndbox>
			</item>
		</object>
	</outputs>
	<time_labeled>1692452783787</time_labeled>
	<labeled>true</labeled>
	<size>
		<width>640</width>
		<height>426</height>
		<depth>3</depth>
	</size>
</doc>

Or in the following json format

{"path":"C:\\Users\\Administrator\\Desktop\\test\\000000000042.jpg","outputs":{"object":[{"name":"dog","bndbox":{"xmin":228,"ymin":32,"xmax":576,"ymax":286}}]},"time_labeled":1692452770011,"labeled":true,"size":{"width":640,"height":478,"depth":3}}

Obviously the xml file format is not VOC format, the real VOC format is similar to the following

<annotation>
    <folder>VOC</folder>
    <filename>000000000074.jpg</filename>
    <path>C:\Users\Administrator\Desktop\test\000000000074.jpg</path>
    <source>
        <database>FIRC</database>
    </source>
    <size>
        <width>640</width>
        <height>426</height>
        <depth>3</depth>
    </size>
    <segmented>0</segmented>
        <object>
            <name>dog</name>
            <pose>Unspecified</pose>
            <truncated>0</truncated>
            <difficult>0</difficult>
            <bndbox>
                <xmin>64</xmin>
                <ymin>271</ymin>
                <xmax>361</xmax>
                <ymax>385</ymax>
            </bndbox>
        </object>
</annotation>

Everyone knows that VOC or yolo format is the most commonly used data set format for target detection. Obviously, the annotation wizard format cannot be directly used for training, and must be converted to VOC format or yolo format. Because a small tool has been developed to support VOC or yolo format conversion, first we open the software

Drag and drop the marked xml file or json file to the list and click start to convert automatically. For details, refer to the video tutorial explanation:

Genie Annotation Assistant format to VOC to YOLO format_哔哩哔哩_bilibili This software is used on windows, can convert Elf Annotation Assistant format xml files or json format files to VOC format or YOLO format, video playback volume 103, bounce 0 episodes, 4 likes, 0 coin tosses, 4 favorites, 0 reposts, video author Future Independent Research Center, author profile Future Independent Research Center, related videos: C# achieves the fastest winform target detection in the entire network yolov7 , based on yolov8+deepsort to achieve target tracking video demonstration, based on yolov8+bytetrack to achieve target tracking video demonstration, VOC dataset automatic pre-labeling and anti-labeling system video automatic tracking and labeling video demonstration, based on yolo-nas+bytetrack to achieve target tracking video demonstration, Video demonstration of target tracking based on yolo-nas+deepsort, use opencv and onnxruntime to deploy yolov5-7-8, click the tutorial at multiple positions with the mouse, [Dataset Introduction][Target Detection] river garbage surface floating objects dataset VOC format 1304 Zhang, encapsulate yolov5-6.2 into a class with a few lines of code to complete the semantic segmentation task https://www.bilibili.com/video/BV1qX4y1W7bW/