Search Results for "binary options software"

Sub2API is an AI API gateway platform for distributing and managing API quotas from AI product subscriptions. It allows users to create platform-issued API keys while routing requests to upstream AI services behind the scenes. The platform handles authentication, quota allocation, billing logic, load balancing, and request forwarding, making it useful for shared or team-based access management. It is designed to unify access to services such as Claude, OpenAI, Gemini, and related AI tools...

KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis.

JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, FlyCapture, Spinnaker, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, flandmark, Leptonica, and Tesseract) and provides utility classes to make their functionality easier to use on the Java platform, including Android. JavaCV also comes with hardware accelerated full-screen image display (CanvasFrame and GLCanvasFrame),...

A speech-to-text library for React Native. Manually or automatically link the NativeModule. Drag the Voice.xcodeproj from the @react-native-voice/voice/ios folder to the Libraries group on Xcode in your project. Click on your main project file (the one that represents the .xcodeproj) select Build Phases and drag the static library, lib.Voice.a, from the Libraries/Voice.xcodeproj/Products folder to Link Binary With Libraries. The plugin provides props for extra customization. Every time you...

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...