Search Results for "delphi runtime code"
Sort By:
Showing 32 open source projects for "delphi runtime code"
View related business solutions-
Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
1
Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate... -
2
Emscripten
Emscripten: An LLVM-to-WebAssembly Compiler
Emscripten is a complete open-source compiler toolchain that transforms C, C++, and other LLVM-based source code into WebAssembly (and JavaScript), enabling native‑like applications to run in web browsers, Node.js, and other Wasm environments. -
3
Vercel AI SDK
Build AI-powered applications with React, Svelte, Vue, and Solid
The Vercel AI SDK is a library for building AI-powered streaming text and chat UIs. -
4
Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed... -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
-
5
E2B
Secure open source cloud runtime for AI apps & AI agents
E2B's Code Interpreter SDK allows you to add code-interpreting capabilities to your AI apps. E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long-running cloud secure environments. In these environments, large language models can use the same tools as humans do. -
6
CTranslate2
Fast inference engine for Transformer models
CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many advanced... -
7
SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime... -
8
Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
9
langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Chidori
A reactive runtime for building durable AI agents
A reactive runtime for building durable AI agents. Chidori is an open-source orchestrator, runtime, and IDE for building software in symbiosis with modern AI tools. When using Chidori, you author code with python or javascript, we provide a layer for interfacing with the complexities of AI models in long-running workflows. We have avoided the need for declaring a new language or SDK in order to provide these capabilities so that you can leverage software patterns that you are already familiar with. -
11
AWS Neuron
Powering Amazon custom machine learning chips
... continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization. -
12
td
Telegram client, in Go. (MTProto API)
Telegram MTProto API client in Go for users and bots. -
13
omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
14
SageMaker Inference Toolkit
Serve machine learning models within a Docker container
Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where... -
15
MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning... -
16
WebLLM
Bringing large-language models and chat to web browsers
... with UI, and is designed in a modular way to hook to any of the UI components. The following code snippet demonstrates a simple example that generates a streaming response on a webpage. -
17
React Native Voice
React Native Voice Recognition library for iOS and Android
... change the props or plugins, you'll need to rebuild (and prebuild) the native app. If no extra properties are added, defaults will be used. While the included VoiceTest app works without explicit permissions checks and requests, it may be necessary to add a permission request for RECORD_AUDIO for some configurations. Since Android M (6.0), user need to grant permission at runtime (and not during app installation). -
18
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... -
19
Delphi Face Recognizer
Delphi Face Recognizer
Delphi Face Recognizer Full Source code of ListBox Bitmap Load and Save from SQLite Database. Binary contains Delphi powerful face recognition. Donate $184 for FULL SOURCE CODE of the Project. mail: dbinXecod@gmail.com if the link is broken here: https://www.paypal.me/dBinXecod/184 Added Feature: X. IP Camera RTSP Connections Real RTSP url link test Real MJPEG url link test Y. Capture faces from Video File Last bug FIXED April_08_2019_12.24pm, X. Recognized Faces... -
20
Delphi Face Recognition March_01_2019
Delphi Face Recognition
Donate $108 for FULL source code of the project. Donate and message or mail at dbinxecod@gmail.com RTSP url link updated BUG FIXED! MEMORY LEAK! ADDED 64BIT + TBB HARD BOILED FACE RECOGNITION: https://sourceforge.net/projects/delphi-face-recognizer/ Gate ID Multi Face Recognition: $384 https://sourceforge.net/projects/opencv-multi-face-detect/ Delphi Face Detection: FREE Source code! https://sourceforge.net/projects/delphi-opencv-face-detection/ Works on IP Camera using... -
21
Delphi Face Detection
Delphi face detection
Delphi Face Detection Live Web Camera Delphi Face Recognition: https://sourceforge.net/projects/delphi-face-recognition/ For Live: Face Attendance System, Facial Emotion, Gender Recognition Security Application. Ethnicity/Nationality Recognition(Maybe Soon) Age? Works on IP Camera using RTSP. Runs on Windows XP to Windows 10 Available on MsAcceSS or SQLite Dataface! Depending on Request! You can reprogram / setup / configure / scale the Face Recognition accuracy... -
22
C++Builder Face Recognition March01_2019
C++Builder Face Recognition
RTSP url link updated Donote $108 for FULL source code of the project. BUG FIXED! MEMORY LEAK! ADDED 64_BIT + TBB HARD BOILED FACE RECOGNITION: https://sourceforge.net/projects/cbuilder-face-recognizer/ page not found for hard core c++Builder, contact author! https://sourceforge.net/projects/delphi-face-recognizer/ C++Builder Face Detection: FREE Source code! https://sourceforge.net/p/cbuilder-opencv-face-detection/ For Live: Face Attendance System, Facial Emotion... -
23
C++Builder with OpenCv345 face detect
C++Builder face detection
Embarcadero C++ Builder Face Detection FREE Source Code! Delphi and C++Builder FACE RECOGNITION,.... here: C++Builder: https://sourceforge.net/projects/c-builder-face-recognition/ Delphi: https://sourceforge.net/projects/delphi-face-recognition/ -
24
Tangent
Source-to-source debuggable derivatives in pure Python
Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools. As a result, you can finally read your automatic derivative code... -
25
eANN
eANN is an implementation of several kind of neural networks.
eANN is an implementation of several kind of neural networks written with the intention of providing a (hopefully) easy to use, and easy to modify, OOP source code. It is possible to have several different sized networks running simultaneously, each functioning independently of the others or acting as inputs between them. It also easy to modify the structure so that neurons (or even whole layers) can be created/pruned during simulation allowing dynamic expansion/contraction of the network.
