Search Results for "can=" - Page 14
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Showing 1301 open source projects for "can="
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bbox-visualizer
Make drawing and labeling bounding boxes easy as cake
...This package helps users draw bounding boxes around objects, without doing the clumsy math that you'd need to do for positioning the labels. It also has a few different types of visualizations you can use for labeling objects after identifying them. There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have full control over your visualizations. -
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AutoKeras
AutoML library for deep learning
...The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the best detailed configuration for you. Moreover, you can override the base classes to create your own block. -
3
Face Alignment
2D and 3D Face alignment library build using pytorch
...For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. While not required, for optimal performance(especially for the detector) it is highly recommended to run the code using a CUDA-enabled GPU. While here the work is presented as a black box, if you want to know more about the intrisecs of the method please check the original paper either on arxiv or my webpage. -
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CLI-Anything
Making ALL Software Agent-Native
CLI-Anything is a framework designed to transform traditional software applications into agent-native command-line interfaces that can be directly controlled by AI systems. It is built on the idea that the command-line interface is the most universal, structured, and composable interface for both humans and AI agents, enabling deterministic and predictable execution of workflows. The system provides a methodology and tooling for generating CLI wrappers around existing applications, allowing them to be controlled programmatically using natural language instructions interpreted by AI agents. ... -
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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GPT PILOT
The first real AI developer
GPT PILOT is an open-source AI developer assistant designed to build full applications by collaborating with a human developer throughout the software lifecycle. Unlike simple autocomplete tools, it aims to function as a true AI engineer that can generate features, set up environments, debug code, and request feedback when necessary. The system works by asking clarifying questions, producing product requirements, and then implementing the application step by step while the user supervises. It powers the Pythagora VS Code extension and relies on coordinated AI agents that mimic roles in a real development workflow. ... -
6
stt
Voice Recognition to Text Tool
...It leverages open-source speech models such as Faster-Whisper to recognize and transcribe human speech into plain text, structured JSON objects, or subtitle files with time codes, making it suitable for both personal and professional transcription tasks. The project is designed to be easy to deploy: you can run a local Python server that exposes an HTTP API for uploading audio/video files and retrieving transcriptions in different formats. It supports GPU acceleration if available, enabling faster processing on compatible hardware but still offers reliable performance on CPUs alone. -
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GELab-Zero
GUI Exploration Lab. One of the best GUI agent solutions
...The project provides a lightweight base model (4B parameters in its public release) that can run on modest hardware (depending on quantization), making it more accessible than many large-scale AI solutions. -
8
Anything to NotebookLM
Multi-source content processor for NotebookLM
...It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It supports multilingual material, with especially strong use cases for Chinese and English content. The tool can process files locally, extract or transcribe content when needed, and hand the cleaned material to NotebookLM for generation. ... -
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Datapizza AI
Build reliable Gen AI solutions without overhead
...The project focuses on simplicity and transparency, enabling developers to construct agent-based workflows without the heavy abstractions and dependencies often found in larger AI frameworks. It provides a flexible architecture where individual agents can be assigned specialized roles, such as web search, reasoning, or domain-specific expertise, and can communicate with each other to complete tasks collaboratively. The framework supports integration with external APIs and tools, allowing agents to perform actions like retrieving data, executing functions, or interacting with external services. ... -
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Elia
Terminal-based LLM chat tool with multi-model and local support
...Installation is straightforward via pipx, and users can customize themes, system prompts, and model settings. Elia is built for developers and power users who prefer a streamlined, terminal-first workflow for working with AI models. -
11
Chandra
OCR model for complex documents with layout-aware structured outputs
...Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. It is capable of handling over 40 languages and is optimized to read difficult inputs such as messy handwriting and multi-column layouts. Chandra can be run locally using transformer-based inference or deployed with a high-performance server setup for large-scale processing. It also includes command-line tools and optional web-based interfaces to simplify interaction and batch processing workflows. -
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TADA
Open Source Speech Language Model
...By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This approach can support applications such as conversational AI, speech synthesis, multimodal language modeling, and speech understanding systems. The project explores ways to treat speech and text as integrated data streams rather than separate pipelines, enabling more coherent interactions between language and audio. Because it operates as a generative framework, TADA can be used for research into advanced speech-language models and multimodal artificial intelligence systems. -
13
TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language interactions into structured representations that can be processed by deterministic software components. ... -
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VoxelMorph
Unsupervised Learning for Image Registration
VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so that it aligns with another. Once the model has been trained, it can rapidly compute the transformation required to register new image pairs, significantly reducing computational time compared to classical registration algorithms. ... -
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python-small-examples
Focus on creating classic Python small examples and cases
...The repository is organized as a large collection of small scripts and notes that can be browsed individually without needing to study a full project. -
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RecAI
Bridging LLM and Recommender System
...The project explores several approaches, including fine-tuning language models using user behavior data, building recommender agents, and using LLMs to explain recommendation results. RecAI also investigates how conversational interfaces powered by LLMs can improve the personalization and transparency of recommendation systems. -
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MiniOneRec
Minimal reproduction of OneRec
...The framework provides an end-to-end pipeline for building generative recommender systems, including semantic identifier construction, supervised fine-tuning, and reinforcement learning-based optimization. Semantic IDs are created using techniques such as quantized variational autoencoders to convert item features into token sequences that can be modeled by transformer architectures. Developers can train and evaluate recommendation models using different backbone language models while benefiting from the generative framework’s parameter efficiency and scalability. -
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RAPTOR
The official implementation of RAPTOR
...During inference, the system can navigate this hierarchical representation to retrieve information that best matches the user’s query while preserving broader contextual understanding. This approach improves question-answering performance on complex tasks that require reasoning across long documents or multiple sources. -
19
LlamaDeploy
Deploy your agentic worfklows to production
...It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports orchestrating multiple services, handling communication between agents, and managing workflow execution in distributed environments. Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. The design emphasizes scalability, modularity, and fault-tolerant execution so that agent systems can run reliably in production environments. -
20
nano-graphrag
A simple, easy-to-hack GraphRAG implementation
...The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of graph-based retrieval systems while remaining easy to modify and extend. The system extracts entities and relationships from documents using language models and organizes them into graph structures that can be queried during generation. Developers can integrate different storage backends and embedding engines, including vector databases and graph databases such as Neo4j, allowing flexible experimentation with hybrid retrieval methods. -
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JSON_REPAIR
A python module to repair invalid JSON from LLMs
...Instead of failing when encountering errors such as missing quotes, trailing commas, or incomplete objects, the library analyzes the malformed data and reconstructs it into valid JSON. The repair process can also be combined with optional JSON Schema validation to enforce structural constraints and ensure the output conforms to expected data types and formats. Developers can integrate the library into applications as a drop-in replacement for standard JSON parsing functions, allowing systems to tolerate imperfect structured data without crashing. -
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WeClone
One-stop solution for creating your digital avatar from chat history
...It is intended primarily as an experimental exploration of digital personality modeling and conversational AI personalization. By processing large volumes of conversation data, WeClone can build a profile of an individual’s writing tone, vocabulary preferences, and conversational tendencies. Developers can use the resulting model to create chatbots that simulate a specific user’s communication patterns for testing or research purposes. Overall, WeClone explores the idea of digital identity replication through machine learning and conversational modeling. -
23
Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
...By formalizing best practices and workflows, Skills helps transform general-purpose coding agents into domain-aware assistants that can execute complex ML pipelines with less manual prompting. The repository also includes ready-to-use skills for common Hugging Face operations and encourages teams to extend them with custom domain logic. -
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Cube Studio
Cube Studio open source cloud native one-stop machine learning
Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data scientists working at scale. The platform supports distributed training across multiple machines and GPUs, integrates tools for automated hyperparameter search and logging, and can serve models via inference services that include virtualized GPU support for efficient utilization. -
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A.I.G
Full-stack AI Red Teaming platform
...It brings together AI infrastructure vulnerability scanning, MCP server risk analysis, and jailbreak evaluation into a unified workflow so that enterprises and individuals can identify critical security issues without relying on external services. Users can deploy it via Docker or scripts to get a modern web UI that guides them through tasks like scanning third-party frameworks for known CVEs and experimenting with prompt security against attack vectors. The tool provides both a visual interface and a comprehensive API, making integration with internal security systems or CI/CD pipelines practical for ongoing risk management.
