Showing 4 open source projects for "pyhook for python 3.6"

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    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

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  • 1
    Old Photo Restoration

    Old Photo Restoration

    Bringing Old Photo Back to Life (CVPR 2020 oral)

    We propose to restore old photos that suffer from severe degradation through a deep learning approach. Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize. Therefore, we propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs. Specifically, we train two...
    Downloads: 2 This Week
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  • 2
    Image Super-Resolution (ISR)

    Image Super-Resolution (ISR)

    Super-scale your images and run experiments with Residual Dense

    ...This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ISR is compatible with Python 3.6 and is distributed under the Apache 2.0 license.
    Downloads: 2 This Week
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  • 3
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    ...TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. For development, you can use make install-develop instead in order to install all the required dependencies for testing and code listing. ...
    Downloads: 0 This Week
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  • 4
    PyTorch pretrained BigGAN

    PyTorch pretrained BigGAN

    PyTorch implementation of BigGAN with pretrained weights

    An op-for-op PyTorch reimplementation of DeepMind's BigGAN model with the pre-trained weights from DeepMind. This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the...
    Downloads: 0 This Week
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  • Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight Icon
    Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum Knight

    Lock Down Any Resource, Anywhere, Anytime

    CLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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