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Showing 12 open source projects for "android arm"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
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.... -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing... -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR... -
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Porcupine
On-device wake word detection powered by deep learning
...It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. Self-service. Developers can train custom wake word models using Picovoice Console. ... -
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Dead Deer 3.14.82.2025
3D modeler, 3D game maker, 3D demo maker
...Scripting language allows you to code interactions in pseudo-C with the animation and synthesize your own rendering with own-made shaders. Import FBX, BLEND, GLTF, OBJ, 3DS, DAE, X, XML, STL, PCB, ASC, PLY, GSPLATS. Cross-platform project WINDOWS 32/64 /MACOSX 10.6/ 10.8+/APPLSilicon /LINUX/iOS/ANDROID/WINDOWS PHONE/GOOGLE VR/OPEN VR/OCULUS VR/WEBASM/UWP8/10/OPENXR, PIs (ARM32/64), RISCV Players and Editors. Android .NED Player (install APK and "open with" with file managers) APK generator for Android. Support for: Direct3D9 (SM3) Direct3D10 (SM4) Direct3D11 (SM5) Direct3D12 (SM5) OpenGL and GLSL OpenGLES 2/3 Apple METAL Retina, UHD. ... -
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GnoppixNG
Gnoppix Linux
Gnoppix is a Linux distribution based on Debian Linux available in for amd64 and ARM architectures. Gnoppix is a great choice for users who want a lightweight and easy-to-use with security in mind. Gnoppix was first announced in June 2003. Currently we're working on a Gnoppix version for WSL, Mobile devices like smartphones and tablets as well. -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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NanoDet-Plus
Lightweight anchor-free object detection model
Super fast and high accuracy lightweight anchor-free object detection model. Real-time on mobile devices. NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss. In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. We also introduce a... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes... -
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Simd
High performance image processing library in C++
...In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems.
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