Showing 8 open source projects for "image steganography code"

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  • 1
    Ralph

    Ralph

    Ralph is the CMDB / Asset Management system for data center

    Ralph is built on top of Django and Python 3 and is easy to extend and customize without writing boilerplate code. REST API, Workflows code extensions allow for easy customization. We've chosen the best features of DCIM, Asset Mgmt and CMDB systems to create one, easy and well-integrated system. One interface is easier than 3. Keep track of assets purchases and their life cycle. Flexible flow system for assets life cycle. Data center and back office support. DC visualization built-in. Ralph...
    Downloads: 14 This Week
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  • 2
    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    ...The framework is based on PyTorch and Transformers and offers a large collection of pre-trained models tuned for various tasks. Further, it is easy to fine-tune your own models. Our models are evaluated extensively and achieve state-of-the-art performance on various tasks. Further, the code is tuned to provide the highest possible speed.
    Downloads: 3 This Week
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  • 3
    Django Lifecycle Hooks

    Django Lifecycle Hooks

    Declarative model lifecycle hooks, an alternative to Signals

    This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django's built-in approach to offering lifecycle hooks is Signals. However, my team often finds that Signals introduce unnecessary indirection and are at odds with Django's "fat models" approach. Django Lifecycle Hooks supports Python 3.7, 3.8 and 3.9, Django 2.0.x, 2.1.x, 2.2.x, 3.0.x, 3.1.x, and 3.2.x. For simple cases, you might always want something to happen at a...
    Downloads: 3 This Week
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  • 4
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    ...The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. ...
    Downloads: 4 This Week
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  • 5
    uwsgi-nginx-flask

    uwsgi-nginx-flask

    Docker image with uWSGI and Nginx for Flask applications in Python

    Image with uWSGI and Nginx for Flask apps in Python running in a single container. Docker image with uWSGI and Nginx for Flask web applications in Python running in a single container. Optionally using Alpine Linux. This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container.
    Downloads: 2 This Week
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  • 6
    MMdnn

    MMdnn

    Tools to help users inter-operate among deep learning frameworks

    MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,...
    Downloads: 0 This Week
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  • 7
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
    Downloads: 0 This Week
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  • 8
    SPADE

    SPADE

    A toolkit for developing and deploying protein structure algorithms.

    The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE.
    Downloads: 0 This Week
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