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一个自由转换图像标注格式的工具

Project description

图像标注格式转换器(image-annotations)

使用方法

标注文件说明

标注格式文件类型一张图片对应一个检测框对应
YOLOtxt一个txt文件txt文件中的一行
VOCxml一个xml文件xml文件中的一个object标签
COCOjsonjson文件中images的一项json文件中annotations的一项

YOLO格式

YOLO格式的目标检测标注文件通常以txt文件给出,一个txt标注文件对应一张图片,txt文件的一行对应一个目标检测框。标注格式如下:
class_id x_center/width y_center/height w/width h/height
其中,class_id表示类别ID,x_center表示标注框中心点x坐标,y_center表示标注框中心点y坐标,w表示标注框宽度,h表示标注框高度,width表示图片宽度,height表示图片高度。
txt标注文件示例如下:
2 0.079166666 0.6759259 0.090625 0.11666667
1 0.22552083 0.67314816 0.015625 0.048148148
1 0.21484375 0.6759259 0.0140625 0.04074074
1 0.1890625 0.6726852 0.016666668 0.047222223
1 0.17916666 0.67083335 0.014583333 0.049074072
1 0.15520833 0.6712963 0.015625 0.05

VOC格式

VOC格式的目标检测文件通常以xml文件给出,一个xml标注文件对应一张图片,xml文件的一个object标签对应一个目标检测框。
xml标注文件示例如下:
<annotation>
	<folder>Desktop</folder>
	<filename>test.jpg</filename>
	<path>/home/DrZon/test.jpg</path>
	<source>
		<database>Unknown</database>
	</source>
	<size>
		<width>194</width>
		<height>259</height>
		<depth>3</depth>
	</size>
	<segmented>0</segmented>
	<object>
		<name>categoryName</name>
		<pose>Unspecified</pose>
		<truncated>0</truncated>
		<difficult>0</difficult>
		<bndbox>
			<xmin>56</xmin>
			<ymin>22</ymin>
			<xmax>132</xmax>
			<ymax>229</ymax>
		</bndbox>
	</object>
</annotation>

COCO格式

COCO格式的目标检测标注文件通常以json文件给出,将所有图片的所有标注写在同一个文件里面,示例格式如下:
{
    "info": {
        "year": 2024,
        "version": "1.0",
        "description": "目标检测训练数据集",
        "contributor": "Your Name",
        "url": "",
        "date_created": "2024-06-15"
    },
    "licenses": [{
        "id": 1,
        "name": "Academic Use Only",
        "url": ""
    }],
    "images": [
        {
            "id": 1,
            "license": 1,
            "file_name": "000001.jpg",
            "height": 600,
            "width": 800,
            "date_captured": "2024-06-15 10:30:00"
        },
        {
            "id": 2,
            "license": 1,
            "file_name": "000002.jpg",
            "height": 480,
            "width": 640,
            "date_captured": "2024-06-15 10:31:00"
        }
    ],
    "annotations": [
        {
            "id": 1,
            "image_id": 1,
            "category_id": 1,
            "bbox": [120, 150, 80, 120],
            "area": 9600,
            "segmentation": [],
            "iscrowd": 0
        },
        {
            "id": 2,
            "image_id": 1,
            "category_id": 2,
            "bbox": [350, 200, 100, 60],
            "area": 6000,
            "segmentation": [],
            "iscrowd": 0
        },
        {
            "id": 3,
            "image_id": 2,
            "category_id": 1,
            "bbox": [50, 80, 60, 100],
            "area": 6000,
            "segmentation": [],
            "iscrowd": 0
        }
    ],
    "categories": [
        {
            "id": 1,
            "name": "person",
            "supercategory": "human"
        },
        {
            "id": 2,
            "name": "car",
            "supercategory": "vehicle"
        }
    ]
}

更新日志

版本更新内容更新日期
0.1.0实现YOLO、COCO、VOC三种格式的目标检测标注文件相互转换2026年1月6日
0.2.0新增获取全部类名的功能2026年1月7日
0.2.1Updated YOLO to VOC and COCO conversion functions to iterate over image files instead of annotation files, improving robustness for various image formats.2026年1月11日

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