Showing 69 open source projects for "python imaging library"

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  • 1
    Detectron2

    Detectron2

    Next-generation platform for object detection and segmentation

    Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll...
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  • 2
    Tez

    Tez

    Tez is a super-simple and lightweight Trainer for PyTorch

    Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch. tez (तेज़ / تیز) means sharp, fast & active. This is a simple, to-the-point, library to make your PyTorch training easy. This library is in early-stage currently! So, there might be breaking changes. Currently, tez supports cpu, single gpu and multi-gpu & tpu training. More coming soon! Using tez is super-easy. We don't want you to...
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  • 3
    Surface Defect Detection Dataset Papers

    Surface Defect Detection Dataset Papers

    Constantly summarizing open source dataset and critical papers

    At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery manufacturing, semiconductors and electronics, chemical, pharmaceutical, aerospace, light industry and other industries. Traditional surface defect detection methods based on machine vision often use conventional image processing algorithms or artificially designed features plus classifiers. Generally...
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  • 4
    TensorLayer

    TensorLayer

    Deep learning and reinforcement learning library for scientists

    TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extensive collection of customizable neural layers to build advanced AI models quickly, based on this, the community open-sourced mass tutorials and applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. This project can also be found at OpenI and Gitee. 3.0.0 has been pre-released, the current version...
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    PaddlePaddle models

    PaddlePaddle models

    Pre-trained and Reproduced Deep Learning Models

    Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,...
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  • 6
    NLP Architect

    NLP Architect

    A model library for exploring state-of-the-art deep learning

    NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. ...
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  • 7
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency...
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  • 8
    SageMaker MXNet Training Toolkit

    SageMaker MXNet Training Toolkit

    Toolkit for running MXNet training scripts on SageMaker

    SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. ...
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  • 9
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
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  • 10
    PyText

    PyText

    A natural language modeling framework based on PyTorch

    PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly...
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  • 11

    FastoCloud PRO

    IPTV/NVR/CCTV/Video cloud https://fastocloud.com

    IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ...
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  • 12
    ChainerRL

    ChainerRL

    ChainerRL is a deep reinforcement learning library

    ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. ...
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  • 13
    MLBox

    MLBox

    MLBox is a powerful Automated Machine Learning python library

    MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation.
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  • 14
    ChainerCV

    ChainerCV

    ChainerCV: a Library for Deep Learning in Computer Vision

    ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes. ChainerCV supports dataset loaders, which can...
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  • 15
    DIGITS

    DIGITS

    Deep Learning GPU training system

    The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. 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...
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  • 16

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a folder of images from the command line. ...
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  • 17
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    A library for probabilistic modeling, inference, and criticism. Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets.
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  • 18
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
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  • 19
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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