Showing 8 open source projects for "libtogl.so.2"

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    Track time for payroll, billing and productivity

    Flexible time and billing software that enables teams to easily track time and expenses for payroll, projects, and client billing.

    Because time is money, and we understand how challenging it can be to keep track of employee hours. The constant reminder to log timesheets so your business can increase billables, run an accurate payroll and remove the guesswork from project estimates – we get it.
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    Electronic Lab Notebook (ELN) Software

    Ideal for any lab. Whether you’re just starting up, a small or large academic institution, or a globally operating company.

    eLabJournal is an all-in-one Electronic Lab Notebook (ELN) software that includes sample tracking and protocol management modules.
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  • 1
    LTX-2

    LTX-2

    Python inference and LoRA trainer package for the LTX-2 audio–video

    LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch.
    Downloads: 71 This Week
    Last Update:
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  • 2
    Wan2.2

    Wan2.2

    Wan2.2: Open and Advanced Large-Scale Video Generative Model

    Wan2.2 is a major upgrade to the Wan series of open and advanced large-scale video generative models, incorporating cutting-edge innovations to boost video generation quality and efficiency. It introduces a Mixture-of-Experts (MoE) architecture that splits the denoising process across specialized expert models, increasing total model capacity without raising computational costs. Wan2.2 integrates meticulously curated cinematic aesthetic data, enabling precise control over lighting,...
    Downloads: 136 This Week
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  • 3
    LTX-2.3

    LTX-2.3

    Official Python inference and LoRA trainer package

    LTX-2 is designed for both research and production workflows and can generate high-resolution video clips with precise control over structure, motion, and camera behavior.
    Downloads: 177 This Week
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  • 4
    Phenaki - Pytorch

    Phenaki - Pytorch

    Implementation of Phenaki Video, which uses Mask GIT

    Implementation of Phenaki Video, which uses Mask GIT to produce text-guided videos of up to 2 minutes in length, in Pytorch. It will also combine another technique involving a token critic for potentially even better generations. A new paper suggests that instead of relying on the predicted probabilities of each token as a measure of confidence, one can train an extra critic to decide what to iteratively mask during sampling.
    Downloads: 1 This Week
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  • Cloud-hosted construction project information management for improved communication, and increased efficiency. Icon
    Cloud-hosted construction project information management for improved communication, and increased efficiency.

    Ideal for on-premise project information management.

    Newforma empowers over 4M professionals and 1,500 AECO firms worldwide by revolutionizing Project Information Management. We transform vast amounts of project data into a meticulously organized, easily accessible, and fully searchable resource—all from a single, centralized platform. From pre-construction to years after completion, Newforma ensures you have the critical information you need at every stage of your projects.
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  • 5
    AI YouTube Shorts Generator

    AI YouTube Shorts Generator

    A python tool that uses GPT-4, FFmpeg, and OpenCV

    AI-YouTube-Shorts-Generator is a Python-based tool that automates the creation of short-form vertical video clips (“shorts”) from longer source videos — ideal for adapting content for platforms like YouTube Shorts, Instagram Reels, or TikTok. It analyzes input video (whether a local file or a YouTube URL), transcribes audio (with optional GPU-accelerated speech-to-text), uses an AI model to identify the most compelling or engaging segments, and then crops/resizes the video and applies...
    Downloads: 7 This Week
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  • 6
    Make-A-Video - Pytorch (wip)

    Make-A-Video - Pytorch (wip)

    Implementation of Make-A-Video, new SOTA text to video generator

    Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch. They combine pseudo-3d convolutions (axial convolutions) and temporal attention and show much better temporal fusion. The pseudo-3d convolutions isn't a new concept. It has been explored before in other contexts, say for protein contact prediction as "dimensional hybrid residual networks". The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning...
    Downloads: 0 This Week
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  • 7
    Recurrent Interface Network (RIN)

    Recurrent Interface Network (RIN)

    Implementation of Recurrent Interface Network (RIN)

    ...Additionally, we will try adding an extra linear attention on the main branch as well as self-conditioning in the pixel space. The insight of being able to self-condition on any hidden state of the network as well as the newly proposed sigmoid noise schedule are the two main findings.
    Downloads: 1 This Week
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  • 8
    DCVGAN

    DCVGAN

    DCVGAN: Depth Conditional Video Generation, ICIP 2019.

    ...The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical information. To add appropriate color to the geometrical information of the scene, the domain translation from depth to color is performed for each image. This model has three networks in the generator. In addition, the model has two discriminators.
    Downloads: 0 This Week
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