『怀旧小屋』
@PainlessDestiny · Post #2587 · 02/10/2025, 04:07 AM
#相册3.8.2.11 #Bokeh 2.0.19.0.0 解锁文档编辑（包含去屏纹、曲面矫正和笔迹消除） 解锁提取表格（需要小爱视觉/AI扫描）
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Source channel @githubtrending · Post #14919 · Jul 6
#cplusplus#aes#avx#avx_instructions#chrome#chrome_devtools#chromedriver#chromium#chromium_browser#content_shell#jpeg_xl#jpegxl#jxl#libjxl#linux#thorium#thorium_browser#thoriumos#web_browser#web_platform#webbrowser Thorium is a fast, optimized web browser based on Chromium, designed to work well on modern CPUs with advanced instruction sets like AVX and SSE4. It offers better performance than standard Chromium and Chrome, opening tabs and rendering pages quickly. Thorium includes enhanced privacy features such as DNS over HTTPS and Do Not Track enabled by default, plus support for modern media formats like HEVC and JPEG XL. It keeps the familiar Chrome interface and supports all Chrome extensions, making it easy to switch. Available on Windows, Linux, macOS, Android, and Raspberry Pi, it suits users wanting speed, privacy, and compatibility across devices[3][5][1]. https://github.com/Alex313031/thorium
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djangoproject
@djangoproject · Post #468 · 10/16/2017, 08:30 AM
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Bokeh_Cheat_Sheet.pdf Python For #Data_Science Cheat Sheet The Python interactive visualization library #Bokeh enables high-performance visual presentation of large datasets in modern #web browsers.
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@ThemesM8 · Post #85 · 07/20/2021, 04:48 PM
https://t.me/addtheme/pfsIJiYasr0juhEB 🌈@ThemesM8✨ #dark#purple#blue#android#desktop#oled#amoled#night#bokeh
『怀旧小屋』
@PainlessDestiny · Post #2611 · 02/28/2025, 01:30 PM
#小米相册#相册#小米相册编辑 #小米澎湃AI引擎#文件管理#Bokeh 来自小米15Ultra的App们 不建议在MIUI或者HyperOS上用 不接收来自MIUI/HyperOS/低于安卓14的反馈 相册和文件管理在高分辨率的屏幕上显示异常，暂时不知道怎么修 对于小米相册： 功能应该是解锁全了 对于小米相册编辑： 水印还是和之前一样，你想要正常的显示，可以手动改照片的EXIF 如果你发现你拍的照片点不进画框，但是截图可以，建议你打开EXIF随便改一个数字他就可以点进画框了，暂时还不知道是咋回事 部分AI功能可能失效（因为小米服务器Boom了） 其他的功能也基本解锁全了 对于文件管理： 没啥说的，就是移植包 小米澎湃引擎和Bokeh是相关组件，建议安装
djangoproject
@djangoproject · Post #352 · 06/25/2017, 08:57 AM
https://stxnext.com/blog/2017/04/12/most-popular-python-scientific-libraries/ The most popular Python scientific libraries: #Astropy #Biopython #Cubes #DEAP #SCOOP #PsychoPy #Pandas #Mlpy #matplotlib #NumPy #NetworkX #TomoPy #Theano #SymPy #SciPy #scikit_learn #scikit_image #ScientificPython #SageMath #Veusz #graph_tool #SunPy #Bokeh