Pytorch Libraries

152 Components & Libraries

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Pytorch Libraries

A library for training and deploying machine learning models on Amazon SageMaker

SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. The SageMaker Python SDK is built to PyPI and can be installed with pip as follo…

Demo for the "Talking Head Anime from a Single Image."

Also, the peppeteer tool requires a webcam. If you install these packages, you should be all good. This should download and install all the dependencies. Keep in mind, though, that this will require …

Open Machine Learning course

First semester of girafe-ai Machine Learning course Special thanks to:

Medical imaging toolkit for deep learning

If you like this repository, please click on Star! If you use this package for your research, please cite our paper: BibTeX entry: This project is supported by the following institutions:

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Contents For example to trigger installation of GPU version of tensorflow and opencv, use the following pip command: Petastorm supports extensible data codecs. These enable a user to use one of the s…

Torchmetrics - Machine learning metrics for distributed, scalable PyTorch applications.

Simple installation from PyPI Install using conda Pip from source Pip from archive Extra dependencies for specialized metrics: Install latest developer version TorchMetrics is a collection of 100+ Py…

Generate images from texts. In Russian

an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

This is a reference implementation of 3D Ken Burns Effect from a Single Image [1] using PyTorch. Given a single input image, it animates this still image with a virtual camera scan and zoom subject t…

CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch

This is a Python toolbox that implements the training and testing of the approach described in our papers: This code implements: In order to run this toolbox you will need: For detailed explanation o…

Machine learning metrics for distributed, scalable PyTorch applications.

Open source person re-identification library in python

Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different datasets, a full set of models and evaluation metrics, as wel…

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch The content of this document is organized as follows: Two simpler at…

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

Experiments are produced on MNIST, Fashion MNIST and CIFAR10 (both IID and non-IID). In case of non-IID, the data amongst the users can be split equally or unequally. Since the purpose of these exper…

Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.

Both programs were written in Python 3. To run the GUIs, the following software packages are required: This means that, in addition to the commands above, you also need to run: You can also use Anaco…

:computer: Learn to make machines learn so that you don't have to struggle to program them; The ultimate list

Machine Learning is a branch of Artificial Intelligence dedicated at making machines learn from observational data without being explicitly programmed. Machine learning and AI are not the same. Machi…

👁️ 🖼️ 🔥PyTorch Toolbox for Image Quality Assessment, including LPIPS, FID, NIQE, NRQM(Ma), MUSIQ, NIMA, DBCNN, WaDIQaM, BRISQUE, PI and more...

Example test script with input directory/images and reference directory/images. Results are calculated with: Basically, we use the largest existing datasets for training, and cross dataset evaluation…

Machine learning on FPGAs using HLS

A package for machine learning inference in FPGAs. We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source ma…

Machine learning metrics for distributed, scalable PyTorch applications.

A medical imaging framework for Pytorch

MedicalTorch is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets for medical imaging.

Pix In, Latex & Text Out. Recognize Chinese, English Texts, and Math Formulas from Images.

Major changes: Major changes: Pix2Text is very simple to use and the following is an example: Some examples: If you have successfully run the above example, the model has completed its automatic down…

Open Machine Learning course at MIPT

This course aims to introduce students to modern state of Machine Learning andArtificial Intelligence. It is designed to take one year (two terms at MIPT) -approximately 2 * 15 lectures and seminars.…

Demo Programs for the "Talking Head(?) Anime from a Single Image 3: Now the Body Too" Project

Both programs require a recent and powerful Nvidia GPU to run. I could personally ran them at good speed with the Nvidia Titan RTX. However, I think recent high-end gaming GPUs such as the RTX 2080, …

Code, exercises and tutorials of my personal blog ! 📝

The repository is organized the following way : For the moment, these cheat sheets are written manually. I'd like to create a visual content later that would both dive in the maths and illustrate cle…

Integrating the Best of TF into PyTorch, for Machine Learning, Natural Language Processing, and Text Generation. This is part of the CASL project: http://casl-project.ai/

Texar-PyTorch integrates many of the best features of TensorFlow into PyTorch, delivering highly usable and customizable modules superior to PyTorch native ones. Texar-PyTorch requires: To use cuttin…

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Test tube is a python library to track and parallelize hyperparameter search for Deep Learning and ML experiments. It's framework agnostic and built on top of the python argparse API for ease of use.…

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Change detection based on remote sensing (RS) data is an important method of detecting changes on the Earth’s surface and has a wide range of applications in urban planning, environmental monitoring,…

Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, Apptainer, and more.

This repository contains all the notebooks and mkdocs markdown files of the tutorials covering machine learning, deep learning, deep reinforcement learning, data engineering, general programming, and…

The fastest way to deploy AI apps and services on any infra. Unobtrusive, debuggable, PyTorch-like APIs.

Runhouse is built to do four things: The above env list is a shorthand, but you can create quite elaborate envs (even quite a bit more elaborate than the example below). Local folders are sent (rsync…

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