Showing 84 open source projects for "inventory python project"

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  • 1
    Implicit

    Implicit

    Fast Python collaborative filtering for implicit feedback datasets

    This project provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets. All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding up...
    Downloads: 0 This Week
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  • 2
    Darts

    Darts

    A python library for easy manipulation and forecasting of time series

    ... be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper).
    Downloads: 0 This Week
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  • 3
    Katib

    Katib

    Automated Machine Learning on Kubernetes

    Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is a project that is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom...
    Downloads: 0 This Week
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  • 4
    MMAction2

    MMAction2

    OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

    OpenMMLab's next generation video understanding toolbox and benchmark. MMAction2 is an open-source toolbox for video understanding based on PyTorch. It is a part of the OpenMMLab project. Modular design: We decompose a video understanding framework into different components. One can easily construct a customized video understanding framework by combining different modules. Support four major video understanding tasks: MMAction2 implements various algorithms for multiple video understanding...
    Downloads: 0 This Week
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  • 5
    MMClassification

    MMClassification

    OpenMMLab Image Classification Toolbox and Benchmark

    MMClassification is an open-source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. Supports DenseNet, VAN and PoolFormer, and provide pre-trained models. Supports training on IPU. Supports a series of CSP networks, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods...
    Downloads: 0 This Week
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  • 6
    MetaTransformer

    MetaTransformer

    Meta-Transformer for Unified Multimodal Learning

    We're thrilled to present OneLLM, an ensembling Meta-Transformer framework with Multimodal Large Language Models, which performs multimodal joint training, supports more modalities including fMRI, Depth, and Normal Maps, and demonstrates very impressive performances on 25 benchmarks.
    Downloads: 0 This Week
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  • 7
    MMOCR

    MMOCR

    OpenMMLab Text Detection, Recognition and Understanding Toolbox

    MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the corresponding downstream tasks including key information extraction. It is part of the OpenMMLab project. The toolbox supports not only text detection and text recognition, but also their downstream tasks such as key information extraction. The toolbox supports a wide variety of state-of-the-art models for text detection, text recognition and key information extraction. The modular...
    Downloads: 0 This Week
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  • 8
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for graph...
    Downloads: 0 This Week
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  • 9
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with...
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    Downloads: 15 This Week
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  • 10
    T81 558

    T81 558

    Applications of Deep Neural Networks

    Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network...
    Downloads: 0 This Week
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  • 11
    ManimML

    ManimML

    ManimML is a project focused on providing animations

    ManimML is a project focused on providing animations and visualizations of common machine-learning concepts with the Manim Community Library. Please check out our paper. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine-learning concepts. Additionally, we want to provide a set of abstractions that allow users to focus on explanations instead of software engineering.
    Downloads: 0 This Week
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  • 12
    GNNePCSAFT

    GNNePCSAFT

    Smart Thermodynamic Modeling with Graph Neural Networks

    Embark on a cutting-edge journey with our project that harnesses the power of Graph Neural Networks to estimate pure-component parameters of the state-of-the-art Equation of State, ePC-SAFT. We aim to empower users to leverage this robust equation without the need for prior experimental data, revolutionizing the calculation of thermodynamic properties and enhancing process simulations. FeOS is used for the PC-SAFT calculations. The estimated parameters can be used in DWSIM and Aspen HYSYS...
    Downloads: 7 This Week
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  • 13
    Ubix Linux

    Ubix Linux

    The Pocket Datalab

    ... can find additional information, technical guidance, and user credentials on the project website https://ubix-linux.sourceforge.io/ or on the project subreddit https://reddit.com/r/UbixLinux.
    Downloads: 4 This Week
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  • 14
    Conscious Artificial Intelligence

    Conscious Artificial Intelligence

    It's possible for machines to become self-aware.

    This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3...
    Downloads: 3 This Week
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  • 15
    find-similar

    find-similar

    User-friendly library to find similar objects

    The mission of the FindSimilar project is to provide a powerful and versatile open source library that empowers developers to efficiently find similar objects and perform comparisons across a variety of data types. Whether dealing with texts, images, audio, or more, our project aims to simplify the process of identifying similarities and enhancing decision-making. https://github.com/findsimilar/find-similar - GitHub repo http://demo.findsimilar.org/ - Demo project and tutorial https...
    Downloads: 0 This Week
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  • 16
    LayoutParser

    LayoutParser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

    .... After several major updates, layoutparser provides various functionalities and deep learning models from different backends. But it still easy to install layoutparser, and we designed the installation method in a way such that you can choose to install only the needed dependencies for your project. LayoutParser is also a open platform that enables the sharing of layout detection models and DIA pipelines among the community.
    Downloads: 3 This Week
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  • 17
    TensorFlow Backend for ONNX

    TensorFlow Backend for ONNX

    Tensorflow Backend for ONNX

    ... purposes in the ONNX community. ONNX-TF requires ONNX (Open Neural Network Exchange) as an external dependency, for any issues related to ONNX installation, we refer our users to ONNX project repository for documentation and help. Notably, please ensure that protoc is available if you plan to install ONNX via pip.
    Downloads: 0 This Week
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  • 18
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what...
    Downloads: 3 This Week
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  • 19
    SageMaker Scikit-Learn Extension

    SageMaker Scikit-Learn Extension

    A library of additional estimators and SageMaker tools based on scikit

    A library of additional estimators and SageMaker tools based on scikit-learn. This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install...
    Downloads: 2 This Week
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  • 20
    Face Mask Detection

    Face Mask Detection

    Face Mask Detection system based on computer vision and deep learning

    Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential...
    Downloads: 2 This Week
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  • 21
    igel

    igel

    Machine learning tool that allows you to train and test models

    A delightful machine learning tool that allows you to train/fit, test, and use models without writing code. The goal of the project is to provide machine learning for everyone, both technical and non-technical users. I sometimes needed a tool sometimes, which I could use to fast create a machine learning prototype. Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML. I find myself often stuck writing boilerplate code and thinking too much about...
    Downloads: 2 This Week
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  • 22
    DeeProtGO

    DeeProtGO

    DeeProtGO is a deep learning model for predicting GO terms of proteins

    This project contains the source code of DeeProtGO as well as an example of its use when predicting GO terms of the biological process sub-ontology for eukaryotic proteins.
    Downloads: 0 This Week
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  • 23
    TorchGAN

    TorchGAN

    Research Framework for easy and efficient training of GANs

    The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to provide...
    Downloads: 0 This Week
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  • 24
    DeepMosaics

    DeepMosaics

    Automatically remove the mosaics in images and videos, or add mosaics

    Automatically remove the mosaics in images and videos, or add mosaics to them. This project is based on "semantic segmentation" and "Image-to-Image Translation". You can either run DeepMosaics via a pre-built binary package, or from source. Run time depends on the computer's performance (GPU version has better performance but requires CUDA to be installed). Different pre-trained models are suitable for different effects.[Introduction to pre-trained models].
    Downloads: 105 This Week
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  • 25
    TensorFlow.js models

    TensorFlow.js models

    Pretrained models for TensorFlow.js

    This repository hosts a set of pre-trained models that have been ported to TensorFlow.js. The models are hosted on NPM and unpkg so they can be used in any project out of the box. They can be used directly or used in a transfer learning setting with TensorFlow.js. To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts. New models should have a test NPM script. You can...
    Downloads: 0 This Week
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