Search Results for "library"

whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently.

Allows you to emulate an Android native library, and an experimental iOS emulation. This is an educational project to learn more about the ELF/MachO file format and ARM assembly. Emulation of the JNI Invocation API so JNI_OnLoad can be called. Support JavaVM, JNIEnv. Emulation of syscalls instruction. Support ARM32 and ARM64. Inline hook, thanks to Dobby. Android import hook, thanks to xHook. iOS fishhook and substrate and whale hook. unicorn backend support simple console debugger, gdb stub, instruction trace, memory read/write trace. ...

iOS, android, raspberry pi, windows store, windows desktop, linux, macOS etc. Multiple toolchains support, include gcc, clang, vs2013, vs2015, vs2017. Hardware accelerated decoders and encoders support. Source code: https://github.com/wang-bin/avbuild

Asphyre, also known as Platform eXtended Library, is a cross-platform framework for developing video games and scientific applications in Delphi, and FreePascal/Lazarus. The framework provides facilities for real-time rendering of graphics (using DirectX, OpenGL or Software Renderer), text output, mathematics (including vectors and matrices) and networking communication, among other features.

This library is being created as I have a need to do very fast FFTs on low end devices not supporting the NEON instruction set. The Raspberry Pi is an ideal candidate for developing in gcc before porting to JNI for low spec Android devices, hence it's inclusion. Fixed point 16/32 integer FFT library suitable for the Raspberry Pi and Android devices.