Showing 8 open source projects for "computer based training"

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  • 1
    PaddleNLP

    PaddleNLP

    Easy-to-use and powerful NLP library with Awesome model zoo

    PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities...
    Downloads: 5 This Week
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  • 2
    Free AI Watermark Remover - FreeRepair

    Free AI Watermark Remover - FreeRepair

    AI-powered tool to quickly remove watermarks from images flawlessly

    AI Watermark Remover (Free And Open-Source) & Make Blurry Images Clearer Or Larger Tool - FreeRepair, Simulation IOPaint Based On The Django Of Python With No Sign-Up. As a free, open-source, AI-powered tool, FreeRepair makes it easy to remove watermarks, logos, text or clutter from images, and blurry images can be made clearer or larger. No installation, no internet connection, it works out of the box, safe and secure, unlimited.
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    Downloads: 33 This Week
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  • 3
    DALL-E 2 - Pytorch

    DALL-E 2 - Pytorch

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis

    ...Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP.
    Downloads: 6 This Week
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  • 4
    CogView

    CogView

    Text-to-Image generation. The repo for NeurIPS 2021 paper

    ...The repository provides pretrained models, inference scripts, and training examples, along with a Docker environment for reproducibility.
    Downloads: 1 This Week
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  • 5
    texturize

    texturize

    Generate photo-realistic textures based on source images

    Generate photo-realistic textures based on source images. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture. A command-line tool and Python library to automatically generate new textures similar to a source image or photograph. It's useful in the context of computer graphics if you want to make variations on a theme or expand the size of an existing texture.
    Downloads: 2 This Week
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  • 6
    GLIDE (Text2Im)

    GLIDE (Text2Im)

    GLIDE: a diffusion-based text-conditional image synthesis model

    glide-text2im is an open source implementation of OpenAI’s GLIDE model, which generates photorealistic images from natural language text prompts. It demonstrates how diffusion-based generative models can be conditioned on text to produce highly detailed and coherent visual outputs. The repository provides both model code and pretrained checkpoints, making it possible for researchers and developers to experiment with text-to-image synthesis. GLIDE includes advanced techniques such as...
    Downloads: 2 This Week
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  • 7
    GANformer

    GANformer

    Generative Adversarial Transformers

    ...The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of each in light of the other and encourage the emergence of compositional representations of objects and scenes. In contrast to the classic transformer architecture, it utilizes multiplicative integration that allows flexible region-based modulation and can thus be seen as a generalization of the successful StyleGAN network. Using the pre-trained models (generated after training for 5-7x less steps than StyleGAN2 models! Training our models for longer will improve the image quality further).
    Downloads: 0 This Week
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  • 8
    Deep Exemplar-based Video Colorization

    Deep Exemplar-based Video Colorization

    The source code of CVPR 2019 paper "Deep Exemplar-based Colorization"

    The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization". End-to-end network for exemplar-based video colorization. The main challenge is to achieve temporal consistency while remaining faithful to the reference style. To address this issue, we introduce a recurrent framework that unifies the semantic correspondence and color propagation steps. Both steps allow a provided reference image to guide the colorization of every frame, thus reducing accumulated propagation...
    Downloads: 7 This Week
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