Metadata-Version: 2.1
Name: agentclpr
Version: 1.1.0
Summary: An easy-to-use Chinese license plate recognition system.
Home-page: https://github.com/AgentMaker/AgentCLPR
Author: jm12138
License: Apache License 2.0
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: agentocr

# AgentCLPR

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## 简介

* 一个基于 [ONNXRuntime](https://github.com/microsoft/onnxruntime)、[AgentOCR](https://github.com/AgentMaker/AgentOCR) 和 [License-Plate-Detector](https://github.com/zeusees/License-Plate-Detector) 项目开发的中国车牌检测识别系统。

## 车牌识别效果

* 支持多种车牌的检测和识别（其中单层车牌识别效果较好）：

    * 单层车牌：

        ![](https://img-blog.csdnimg.cn/e5801d1a4d394d8ba7b50bed4b0a6b55.png)

            [[[[373, 282], [69, 284], [73, 188], [377, 185]], ['苏E05EV8', 0.9923506379127502]]]
            [[[[393, 278], [318, 279], [318, 257], [393, 255]], ['VA30093', 0.7386096119880676]]]
            [[[[[487, 366], [359, 372], [361, 331], [488, 324]], ['皖K66666', 0.9409016370773315]]]]
            [[[[304, 500], [198, 498], [199, 467], [305, 468]], ['鲁QF02599', 0.995299220085144]]]
            [[[[309, 219], [162, 223], [160, 181], [306, 177]], ['使198476', 0.9938704371452332]]]
            [[[[957, 918], [772, 920], [771, 862], [956, 860]], ['陕A06725D', 0.9791222810745239]]]

    * 双层车牌：

        ![](https://ai-studio-static-online.cdn.bcebos.com/05e35463f9984d7786bc644bfc1c1aef4f73ce1673eb4291a5d7e71513f40032)

            [[[[399, 298], [256, 301], [256, 232], [400, 230]], ['浙G66666', 0.8870148431461757]]]
            [[[[398, 308], [228, 305], [227, 227], [398, 230]], ['陕A00087', 0.9578166644088313]]]
            [[[[352, 234], [190, 244], [190, 171], [352, 161]], ['宁A66666', 0.9958433652812175]]]

## 快速使用

* 快速安装

    ```bash
    # 安装 AgentCLPR
    $ pip install agentclpr

    # 根据设备平台安装合适版本的 ONNXRuntime

    # CPU 版本（推荐非 win10 系统，无 CUDA 支持的设备安装）
    $ pip install onnxruntime

    # GPU 版本（推荐有 CUDA 支持的设备安装）
    $ pip install onnxruntime-gpu

    # DirectML 版本（推荐 win10 系统的设备安装，可实现通用的显卡加速）
    $ pip install onnxruntime-directml

    # 更多版本的安装详情请参考 ONNXRuntime 官网
    ```

* 简单调用：

    ```python
    # 导入 CLPSystem 模块
    from agentclpr import CLPSystem

    # 初始化车牌识别模型
    clp = CLPSystem()

    # 使用模型对图像进行车牌识别
    results = clp('test.jpg')
    ```

* 服务器部署：

    * 启动 AgentCLPR Server 服务

        ```shell
        $ agentclpr server
        ```

    * Python 调用

        ```python
        import cv2
        import json
        import base64
        import requests

        # 图片 Base64 编码
        def cv2_to_base64(image):
            data = cv2.imencode('.jpg', image)[1]
            image_base64 = base64.b64encode(data.tobytes()).decode('UTF-8')
            return image_base64

        # 读取图片
        image = cv2.imread('test.jpg')
        image_base64 = cv2_to_base64(image)

        # 构建请求数据
        data = {
            'image': image_base64
        }

        # 发送请求
        url = "http://127.0.0.1:5000/ocr"
        r = requests.post(url=url, data=json.dumps(data))

        # 打印预测结果
        print(r.json())
        ```


