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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现
| Date | Stars |
|---|---|
| 2026-07-24 | 547 |
| 2026-07-25 | 547 |
| 2026-07-28 | 547 |
| 2026-07-30 | 547 |
| 2026-08-06 | 547 |
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# End-to-end-for-chinese-plate-recognition ## 基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现 ## 环境：python:3.6, tensorflow:1.15.2, opencv: 4.1.0.25, keras: 2.3.1 ### 整体思路：1. 利用u-net图像分割得到二值化图像，2. 再使用cv2进行边缘检测获得车牌区域坐标，并将车牌图形矫正，3. 利用卷积神经网络cnn进行车牌多标签端到端识别，具体描述可见CSDN博客：https://blog.csdn.net/qq_32194791/article/details/106748685 ### 实现效果：拍摄角度倾斜、强曝光或昏暗环境等都能较好地识别，甚至有些百度AI车牌识别未能识别的图片也能识别 ### 注意：若是直接识别类似下图的无需定位的完整车牌，那么请确保图片尺寸小于等于240 * 80，否则会被认为图片中含其余区域而进行定位，反而识别效果不佳  ### 其余的没什么问题，正常识别都可以 ### 部分效果图：        
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:dadddc46d8e7c0d2, topic:computer-vision, topic:image-segmentation, topic:opencv