支持DirectML等其他ONNX能识别的后端使用GPU加速执行 - #380
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以下部分经过小程序线上大量验证
✅使用官方的PaddleOCR (2.9.1)， 跟随官方线上更新
✅支持DirectML for windows（基于ONNX），让其他独显集显（比如Intel/AMD/其他）也能高速处理字幕，实测在快速/自动模式下RyzenAI PC集显效率>=Nvidia 20系独立显卡效率
✅基于ONNX，同步支持AMD ROCm(Windows环境部署太过苛刻，需要Linux）
✅升级至Paddle 3.0.0rc1
✅修复识别性能问题，移除2行无效的代码，来自#372
✅完善相关文档说明
✅主界面标题显示版本号，方便定位问题
✅由于PySimpleGUI作者故意移除免费的旧版本，改用PySimpleGUI-4-foss，已计划抛弃
以上内容在Windows 11（RyzenAI PC) 以及 Windows 10 (CUDA 10.2/11.8/12.3) 测试通过
合并这个PR请优先合并#379
完，可以使用CI打出来的整合包进行测试 https://github.com/eritpchy/video-subtitle-extractor/releases
PS: 根据Github政策，开源项目可以大量使用Action不会产生额外扣费, 详见: 使用限制、计费和管理以及Plans and usage, 同时设置Spending Limit 也是非常有必要的
PS: 往后发布版本请先修改config.py里面的版本号再做提交，否则CI会将已发布版本的TAG给覆盖，为了避免手误覆盖TAG也可以手动启用每个action里面的“检查 tag 是否已存在”部分，当然启用了会给测试CI带来麻烦
PS: 不需要CI的提交只需添加[skip ci]