跨平臺 C++ 通用庫，Dlib 18.15 發布

Dlib是一個使用現代C++技術編寫的跨平臺的通用庫，遵守Boost Software licence.

主要特點如下：

1.完善的文檔：每個類每個函數都有詳細的文檔，并且提供了大量的示例代碼，如果你發現文檔描述不清晰或者沒有文檔，告訴作者，作者會立刻添加。

2.可移植代碼：代碼符合ISO C++標準，不需要第三方庫支持，支持win32、Linux、Mac OS X、Solaris、HPUX、BSDs 和 POSIX 系統

3.線程支持：提供簡單的可移植的線程API

4.網絡支持：提供簡單的可移植的Socket API和一個簡單的Http服務器

5.圖形用戶界面：提供線程安全的GUI API

6.數值算法：矩陣、大整數、隨機數運算等

7.機器學習算法：

8.圖形模型算法：

9.圖像處理：支持讀寫Windows BMP文件，不同類型色彩轉換

10.數據壓縮和完整性算法：CRC32、Md5、不同形式的PPM算法

11.測試：線程安全的日志類和模塊化的單元測試框架以及各種測試assert支持

12.一般工具：XML解析、內存管理、類型安全的big/little endian轉換、序列化支持和容器類Dlib 18.15 發布，此版本更新內容如下：

新特性
   - Added a number of tools for working with 3D data:
      - Added the perspective_window which is a tool for displaying 3D point clouds.
      - Added camera_transform.  It performs the 3D to 2D mapping needed to visualize 3D
        data.
      - Added point_transform_affine3d as well as functions for creating such transforms:
        rotate_around_x(), rotate_around_y(), rotate_around_z(), and translate_point().
   - Added draw_solid_circle() for drawing on images.
   - Added get_best_hough_point() to the hough_transform.
   - Thanks to Jack Culpepper, the python API for object detection now outputs detection
     confidences.  
   - Added lspi, an implementation of the least-squares policy iteration algorithm.
      
非向后兼容特性
   - The shape_predictor and shape_predictor_trainer had a non-optimal behavior when used
     with objects that have non-square bounding boxes. This has been fixed but will cause
     models that were trained with the previous version of dlib to not work as accurately if
     they used non-square boxes. So you might have to retrain your models when updating dlib.

Bug 修復
   - Fixed a bug which prevented add_image_rotations() from compiling.

其他改進
   - The imglab tool now allows the user to click and drag annotations around by holding
     shift and right clicking.