资源列表
XIANGDA
- fscommand( fullscreen , true ) //全屏 fscommand( allowscale , false ) //禁止缩放true fscommand( showmenu , false ) //右键菜单-fscommand( fullscreen , true ) fscommand( allowscale , false ) fscommand( showmenu , false )
fifo
- 适合初学者实现数据共享和fifo传输，以便于多线程或者多进程之间数据共享-Suitable for beginners fifo data sharing and transfer, so that data shared between multiple threads or multiple processes
openVP-master-20150120
- 声纹识别程序，文本无关，由Dake写的，实现话者辨认，Visual Studio编写-Voiceprint recognition program, text independent, written by Dake, the realization of speaker recognition, Visual Studio prepared
filter.mixing_auds.v13
- 这是一个DirectShow过滤器，已经编译并且运行良好，它可以把最多16路输入音频信号混合为1路输出音频信号；（对于不同的采样率，采用线性重采样算法；其内部混合运算达到24Bits精度；支持立体声、5.1环绕、7.1环绕输出）-This is a DirectShow filter, has been compiled and run well, it can be up to 16 input audio signal to an output mixed audio signal (fo
filter.parser_ssif.vs8
- 这是一个DirectShow过滤器，它可以解析3D蓝光影碟里面的SSIF文件，并且将各个视频流、音频流、字幕流分别输出；已经编译并且运行良好，运行效率极高；-This is a DirectShow filter, which can be resolved inside the 3D Blu-ray SSIF files, and the various video streams, audio streams, subtitle streams are output has been co
filter.resamp_cdda.vs8
- 这是一个DirectShow过滤器，它专门用于CD音频重采样（把44100Hz采样率的音频信号 转化为 48000Hz的）；采用了高精度的奈奎斯特重采样算法，品质极佳；已经编译并且运行良好；-This is a DirectShow filter, it specifically for CD audio resampling (the audio signal into 44100Hz to 48000Hz sampling rate) and the use of a high-preci
nehe
- qt下opengl 三维图形显示，使用键盘可以旋转，初学opengl开发的的小程序，利用贴图，纹理。-Qt under opengl 3 d graphics display, keyboard can rotate, beginners opengl developed small procedures, use of texture, texture.
62788
- my experiments which are very useful
attiny2313-lm1036-ton-kontrol
- digita audio processor
video_cap
- video_cap 摄像头利用程序 另有VC++版 网上收集整理-Vide_cap camera using the program attached VC++ version, online collection
AutoBot
- muautokliker to get free zen , jewls , or picks free!
aranduka
- 用python编写的mockups程序 ，功能完善可以直接使用，也可以查看代码学习研究-Python prepared using mockups program, the perfect function can be used directly, you can also view the code learning research