Language Models

A python tools for fine-tuning language models for a task

DataTuner You have just found the DataTuner. This repository provides tools for fine-tuning language models for a task. Installation Environment Creation Assuming you have an existing conda setup, you can setup the environment with the following script. In order to activate the conda environment within the bash script, you need the location of the conda.sh file: bash setup.sh ~/miniconda3/etc/profile.d/conda.sh You can update your existing environment: conda env update -f=environment.yml To start development, activate your environment: conda activate finetune Alternatively, you […]

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Face recognition

Pretrained Pytorch face detection and facial recognition models

Face Recognition Using Pytorch This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and CASIA-Webface. Pytorch model weights were initialized using parameters ported from David Sandberg’s tensorflow facenet repo. Also included in this repo is an efficient pytorch implementation of MTCNN for face detection prior to inference. These models are also pretrained. To our knowledge, this is the fastest MTCNN implementation available. Quick start Install: # With pip: pip install facenet-pytorch # or clone this […]

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Segmentation

A semantic segmentation toolbox based on PyTorch

vedaseg vedaseg is an open source semantic segmentation toolbox based on PyTorch. Features Modular Design We decompose the semantic segmentation framework into different components. The flexible and extensible design make it easy to implement a customized semantic segmentation project by combining different modules like building Lego. Support of several popular frameworks The toolbox supports several popular semantic segmentation frameworks out of the box, e.g. DeepLabv3+, DeepLabv3, U-Net, PSPNet, FPN, etc. High efficiency Multi-GPU data parallelism & distributed training. Multi-Class/Multi-Label segmentation […]

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Neural Network

Visualization toolkit for neural networks in PyTorch

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as “black box”. The lack of understanding on how neural networks make predictions enables unpredictable/biased models, causing real harm to society and a loss of trust in AI-assisted systems. Feature visualization is an area of research, which aims to understand how neural networks perceive images. However, implementing such techniques is often complicated. FlashTorch was created to solve this problem! You can apply […]

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Benchmark

OpenMMLab Semantic Segmentation Toolbox and Benchmark

MMSegmentation MMSegmentation is an open source semantic segmentation toolbox based on PyTorch. It is a part of the OpenMMLab project. The master branch works with PyTorch 1.3+. Major features Unified Benchmark We provide a unified benchmark toolbox for various semantic segmentation methods. Modular Design We decompose the semantic segmentation framework into different components and one can easily construct a customized semantic segmentation framework by combining different modules. Support of multiple methods out of box The toolbox directly supports popular and […]

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Images

OpenMMLab Image and Video Editing Toolbox in PyTorch

MMEditing Documentation actions codecov PyPI LICENSE Average time to resolve an issue Percentage of issues still open MMEditing is an open source image and video editing toolbox based on PyTorch. It is a part of the OpenMMLab project. The master branch works with PyTorch 1.3 to 1.6. Documentation: https://mmediting.readthedocs.io/en/latest/. Major features Modular design We decompose the editing framework into different components and one can easily construct a customized editor framework by combining different modules. Support of multiple tasks in editing […]

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Video

An open-source toolbox for video understanding based on PyTorch

MMAction2 MMAction2 is an open-source toolbox for video understanding based on PyTorch. It is a part of the OpenMMLab project. The master branch works with PyTorch 1.3+.Action Recognition Results on Kinetics-400 Spatio-Temporal Action Detection Results on AVA-2.1 Skeleton-base Action Recognition Results on NTU-RGB+D-120 Major Features Modular design We decompose the video understanding framework into different components and one can easily construct a customized video understanding framework by combining different modules. Support for various datasets The toolbox directly supports multiple datasets, […]

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Visualization

Python package for the analysis and visualisation of finite-difference fields

discretisedfield Marijan Beg1,2, Martin Lang1, Ryan A. Pepper1, Thomas Kluyver1,2, and Hans Fangohr1,2,3 1 Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom2 European XFEL GmbH, Holzkoppel 4, 22869 Schenefeld, Germany3 Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany About discretisedfield is a Python package, integrated with Jupyter, providing: definition of finite-difference regions, meshes, lines, and fields, analysis of finite-difference fields, visualisation using matplotlib and k3d, and […]

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