Showing 24 open source projects for "model-builder"

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  • 1
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    ...ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that automates the process of building best performing models for your Machine Learning scenario. All you have to do is load your data, and AutoML takes care of the rest of the model building process. ...
    Downloads: 5 This Week
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  • 2
    Raster Vision

    Raster Vision

    Open source framework for deep learning satellite and aerial imagery

    ...Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training models, creating predictions, evaluating models, and bundling the model files and configuration for easy deployment. The input to a Raster Vision pipeline is a set of images and training data, optionally with Areas of Interest (AOIs) that describe where the images are labeled. The output of a Raster Vision pipeline is a model bundle that allows you to easily utilize models in various deployment scenarios.
    Downloads: 1 This Week
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  • 3
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). ...
    Downloads: 0 This Week
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  • 4
    Transformers

    Transformers

    State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX

    ...Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments.
    Downloads: 2 This Week
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  • 5
    Label Studio

    Label Studio

    Label Studio is a multi-type data labeling and annotation tool

    ...Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models. The frontend part of Label Studio app lies in the frontend/ folder and written in React JSX. Multi-user labeling sign up and login, when you create an annotation it's tied to your account. Configurable label formats let you customize the visual interface to meet your specific labeling needs. ...
    Downloads: 21 This Week
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  • 6
    CutLER

    CutLER

    Code release for Cut and Learn for Unsupervised Object Detection

    ...The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to benchmarking results that report large gains over prior unsupervised baselines. It’s intended for researchers exploring self-supervised and unsupervised recognition, offering a practical path to scale beyond costly labeled corpora. The README links papers and gives a high-level overview of components and expected outputs, with pointers to demos and assets. ...
    Downloads: 0 This Week
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  • 7
    SAHI

    SAHI

    A lightweight vision library for performing large object detection

    A lightweight vision library for performing large-scale object detection & instance segmentation. Object detection and instance segmentation are by far the most important fields of applications in Computer Vision. However, detection of small objects and inference on large images are still major issues in practical usage. Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. Detection of small objects and objects far away in the scene is a major...
    Downloads: 0 This Week
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  • 8
    MediaPipe Face Detection

    MediaPipe Face Detection

    Detect faces in an image

    The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis.
    Downloads: 2 This Week
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  • 9
    MobileNetV2

    MobileNetV2

    SSD-based object detection model trained on Open Images V4

    MobileNetV2 is a highly efficient and lightweight deep learning model designed for mobile and embedded devices. It is based on an inverted residual structure that allows for faster computation and fewer parameters, making it ideal for real-time applications on resource-constrained devices. MobileNetV2 is commonly used for image classification, object detection, and other computer vision tasks, achieving high accuracy while maintaining a small memory footprint.
    Downloads: 7 This Week
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  • 10
    MoveNet

    MoveNet

    A CNN model that predicts human joints from RGB images of a person

    The MoveNet model is an efficient, real-time human pose estimation system designed for detecting and tracking keypoints of human bodies. It utilizes deep learning to accurately locate 17 key points across the body, providing precise tracking even with fast movements. Optimized for mobile and embedded devices, MoveNet can be integrated into applications for fitness tracking, augmented reality, and interactive systems.
    Downloads: 0 This Week
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  • 11
    Blazeface

    Blazeface

    Blazeface is a lightweight model that detects faces in images

    Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions.
    Downloads: 3 This Week
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  • 12
    SOD

    SOD

    An Embedded Computer Vision & Machine Learning Library

    SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well as commercial products. SOD implements state-of-the-art computer vision algorithms found to be mandatory in real-world application areas. ...
    Downloads: 0 This Week
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  • 13
    ImageAI

    ImageAI

    A python library built to empower developers

    ...ImageAI is widely used around the world by professionals, students, research groups and businesses. ImageAI provides API to recognize 1000 different objects in a picture using pre-trained models that were trained on the ImageNet-1000 dataset. The model implementations provided are SqueezeNet, ResNet, InceptionV3 and DenseNet. ImageAI provides API to detect, locate and identify 80 most common objects in everyday life in a picture using pre-trained models that were trained on the COCO Dataset.
    Downloads: 8 This Week
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  • 14
    PyTorch Transfer-Learning-Library

    PyTorch Transfer-Learning-Library

    Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.

    TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please...
    Downloads: 0 This Week
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  • 15
    playqt

    playqt

    GUI version of ffplay for Windows

    playqt is a Windows GUI version of the well known ffplay program and has been enhanced with Object Detection capabilities. It can process multiple types of media including real time streams. An integrated camera control feature allows control over the camera parameters as well as automatic network configuration and connection. See the README under the files tab for configuration info. Real time object counting is implemented using YOLO detection algorithm. The program can be used...
    Downloads: 1 This Week
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  • 16
    UniVL

    UniVL

    Official implementation for UniVL video and language training models

    UniVL is a video-language pretrain model. It is designed with four modules and five objectives for both video language understanding and generation tasks. It is also a flexible model for most of the multimodal downstream tasks considering both efficiency and effectiveness.
    Downloads: 0 This Week
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  • 17
    YOLO ROS

    YOLO ROS

    YOLO ROS: Real-Time Object Detection for ROS

    ...You'll have to have an Nvidia GPU and you'll have to install CUDA. The CMakeLists.txt file automatically detects if you have CUDA installed or not. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia.
    Downloads: 0 This Week
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  • 18
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    ...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework.
    Downloads: 0 This Week
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  • 19
    Turi Create

    Turi Create

    Simplifies the development of custom machine learning models

    ...You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app. If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code. Turi Create supports macOS 10.12+, Linux (with glibc 2.10+), Windows 10 (via WSL). Turi Create requires Python 2.7, 3.5, 3.6, 3.7, 3.8. Also, x86_64 architecture, and at least 4 GB of RAM. We recommend using virtualenv to use, install, or build Turi Create. The package User Guide and API Docs contain more details on how to use Turi Create. ...
    Downloads: 9 This Week
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  • 20
    Computer Vision Pretrained Models

    Computer Vision Pretrained Models

    A collection of computer vision pre-trained models

    A pre-trained model is a model created by someone else to solve a similar problem. Instead of building a model from scratch to solve a similar problem, we can use the model trained on other problem as a starting point. A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self-learning car. You can spend years building a decent image recognition algorithm from scratch or you can take the inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures. ...
    Downloads: 0 This Week
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  • 21
    VoTT

    VoTT

    Visual Object Tagging Tool, an electron app for building models

    Visual Object Tagging Tool: An electron app for building end-to-end Object Detection Models from Images and Videos. An open source annotation and labeling tool for image and video assets. VoTT is a React + Redux Web application, written in TypeScript. This project was bootstrapped with Create React App. VoTT can be installed as a native application or run from source. VoTT is also available as a stand-alone Web application and can be used in any modern Web browser. VoTT is available for...
    Downloads: 4 This Week
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  • 22
    TensorNets

    TensorNets

    High level network definitions with pre-trained weights in TensorFlow

    High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and end-point. Also, it is easy to deploy and expand a collection of pre-processing and pre-trained weights. ...
    Downloads: 0 This Week
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  • 23
    DIGITS

    DIGITS

    Deep Learning GPU training system

    ...DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. DIGITS is available as a free download to the members of the NVIDIA Developer Program. DIGITS is available on NVIDIA GPU Cloud (NGC) as an optimized container for on-demand usage. ...
    Downloads: 0 This Week
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  • 24

    ObjectDetector

    Car Detection,Face Detectiom,Object Detection

    Machine learning: This project is used for training new object like Car,Motor Cycle and so on and we use this model(xml file) for detecting in images.In this project we use viola jones algorithm.
    Downloads: 0 This Week
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