Showing 11 open source projects for "speed test"

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  • 1
    HunyuanWorld-Mirror

    HunyuanWorld-Mirror

    Fast and Universal 3D reconstruction model for versatile tasks

    ...The model accepts combinations of images, camera intrinsics and poses, or even depth cues, then reconstructs consistent 3D geometry suitable for downstream rendering or editing. The pipeline emphasizes both speed and flexibility so creators can go from casual captures to assets without elaborate capture rigs. Outputs can include point clouds, estimated camera parameters, and other 3D representations that plug into typical graphics workflows. The project sits within a broader family of Hunyuan models that explore world generation and 3D-consistent understanding, and this mirror variant makes the reconstruction stack easier to test. ...
    Downloads: 0 This Week
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  • 2
    ChatRWKV

    ChatRWKV

    ChatRWKV is like ChatGPT but powered by RWKV

    ...The project focuses on making RWKV usable for interactive prompting, assistant behavior, developer demos, and local experimentation. It connects to the broader RWKV ecosystem, including newer RWKV model versions and compatible weights. ChatRWKV is useful for developers who want to test RWKV as a practical conversational model rather than only as a research architecture. Its main value is showing how RWKV can be applied to chatbot-style interfaces while preserving the speed and memory benefits of its model design.
    Downloads: 0 This Week
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  • 3
    CoStrict

    CoStrict

    Strict AI coder for enterprises, quality first

    CoStrict is an enterprise-focused, open-source AI coding assistant designed to standardize and elevate software development workflows through structured, high-quality automation. Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. ...
    Downloads: 0 This Week
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  • 4
    BoxMOT

    BoxMOT

    Pluggable SOTA multi-object tracking modules for segmentation

    BoxMOT is an open-source framework designed to provide modular implementations of state-of-the-art multi-object tracking algorithms for computer vision applications. The project focuses on the tracking-by-detection paradigm, where objects detected by vision models are continuously tracked across frames in a video sequence. It provides a pluggable architecture that allows developers to combine different object detectors with multiple tracking algorithms without modifying the core codebase....
    Downloads: 0 This Week
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  • 5
    Deta Surf

    Deta Surf

    Personal AI Notebooks. Organize files & webpages and generate notes

    Surf is an open-source AI-driven development tool designed to simplify the process of building and experimenting with artificial intelligence applications. The platform provides a streamlined development environment where developers can test models, run experiments, and deploy small AI services with minimal infrastructure overhead. It focuses on simplicity and speed, allowing developers to prototype ideas quickly without managing complex cloud configurations. Surf integrates modern AI workflows such as prompt-based applications, lightweight APIs, and automated deployment pipelines. ...
    Downloads: 0 This Week
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  • 6
    OpenFieldAI - AI Open Field Test Tracker

    OpenFieldAI - AI Open Field Test Tracker

    OpenFieldAI is an AI based Open Field Test Rodent Tracker

    OpenFieldAI use AI-CNN to track rodents movement with pretrained OFAI models , or user could create their own model with YOLOv8 for inferencing. The software generates Centroid graph, Heat map and Line path and a spreadsheet containing all calculated parameters like - Speed - Time in and out of ROI - Distance - Entries/Exits for single/multiple pre-recorded videos or live webcam video. The ROI is assigned automatically in multiple video input , and can be manually given in single...
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    Downloads: 8 This Week
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  • 7
    Pezzo

    Pezzo

    Open-source, developer-first LLMOps platform

    Pezzo enables you to build, test, monitor and instantly ship AI all in one platform, while constantly optimizing for cost and performance. Packed with powerful features to streamline your workflow, so you can focus on what matters. Pezzo is a fully cloud-native and open-source LLMOps platform. Seamlessly observe and monitor your AI operations, troubleshoot issues, save up to 90% on costs and latency, collaborate and manage your prompts in one place, and instantly deliver AI changes.
    Downloads: 0 This Week
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  • 8
    Coqui TTS

    Coqui TTS

    A deep learning toolkit for Text-to-Speech, battle-tested in research

    ...Efficient, flexible, and lightweight but feature complete Trainer API. Released and ready-to-use models. Tools to curate Text2Speech datasets underdataset_analysis. Utilities to use and test your models.
    Downloads: 24 This Week
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  • 9
    Defox text to speech and downloader

    Defox text to speech and downloader

    Written or imported text offline read or online download.

    This software design to convert text to speech and download the converted speech. Description : • Installation setup with two languages (English, French) • Two areas called text reading and speech downloading • Many languages supported to download center Note 1: I'm a student yet and I'm not in the software designing industry. Therefore maybe I haven't software making skills. I'm worried about that. ! Note 2 : When you double click on the software maybe it will get some seconds...
    Downloads: 0 This Week
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  • 10
    CRFChunker: Conditional Random Fields Phrase Chunker (Phrase Chunking Tool) for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (F1-score of 95.77). Chunking speed: 700 sentences/s
    Downloads: 0 This Week
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  • 11
    CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.
    Downloads: 0 This Week
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