isat-plugin-auto-annotate


Nameisat-plugin-auto-annotate JSON
Version 1.1.0 PyPI version JSON
download
home_pagehttps://github.com/yatengLG/ISAT_plugin_auto_annotate
SummaryISAT Plugin for auto annotate by yolo detect model.
upload_time2025-07-25 06:05:14
maintainerNone
docs_urlNone
authoryatengLG
requires_python>=3.8
licenseApache2.0
keywords isat-sam isat plugin auto annotate
VCS
bugtrack_url
requirements isat-sam onnxruntime
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # ISAT插件 - 自动标注

这是一个[ISAT](https://github.com/yatengLG/ISAT_with_segment_anything)的插件开发示例。

仅使用240行代码,开发一个带界面的ISAT插件,为ISAT提供基于yolo模型的自动标注功能。

该插件使用yolo计算目标框,然后通过sam框提示进行目标分割。

![auto_annotate.img](display/img.png)

## 功能

* 可导入其他模型(项目提供了yolo11n.onnx模型以及yolo11n-seg.onnx模型供测试)
* 兼容IAST,支持所有ISAT提供的sam模型

## 安装与使用

### 安装

```shell
pip install isat-plugin-auto-annotate
```

### 使用

- 运行isat
- 插件界面,激活AutoAnnotatePlugin,在插件界面选择提供的yolo11n.onnx模型与coco.csv类别文件
- 选择sam模型(经不严谨测试,原始sam模型对框提示效果最好)
- 每次切换图片后,自动开始标注当前图片

## 说明

### 模型文件
项目使用带**nms**的onnx模型。

对于目标检测模型,支持所有经nms后输出shape为[n, 6]格式数据的模型,具体表示n个[xmin, ymin, xmax, ymax, score, category_index]
对于图像分割模型,支持所有经nms后输出shape为[n, N]格式数据的模型,具体表示n个[xmin, ymin, xmax, ymax, score, category_index, ...]

以ultralytics导出yolov11模型为例:
```shell
yolo export model=path/to/yolo11n.pt format=onnx nms=True iou=0.45
yolo export model=path/to/yolo11n-seg.pt format=onnx nms=True iou=0.45
```

### 类别文件

类别文件使用cvs格式存储,每行一个类别,分别与category_index对应。

以coco数据集为例:

```text
person
bicycle
car
motorcycle
airplane
bus
train
truck
...
```

模型输出的category_index 0 对应person, 1对应bicycle, ...

            

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