Showing 137 open source projects for "image"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

    Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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  • 1
    MuJoCo Playground

    MuJoCo Playground

    An open source library for GPU-accelerated robot learning

    ...The project includes classic control benchmarks from dm_control, advanced quadruped and bipedal locomotion systems, and dexterous as well as non-prehensile manipulation setups. It also offers optional vision-based training capabilities through integration with Madrona-MJX, allowing researchers to train policies directly from image input on GPUs. MuJoCo Playground supports both the MJX JAX implementation and the Warp physics engine, enabling flexible use across research pipelines. The environments are designed for fast training, compatibility with reinforcement learning libraries, and real-time trajectory visualization using rscope.
    Downloads: 3 This Week
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  • 2
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the validation set and the test set. Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. ...
    Downloads: 2 This Week
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  • 3
    SageMaker Spark Container

    SageMaker Spark Container

    Docker image used to run data processing workloads

    ...It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker.
    Downloads: 0 This Week
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  • 4
    AutoPkg

    AutoPkg

    Automating packaging and software distribution on macOS

    AutoPkg is a system that automatically prepares software for distribution to managed clients. Recipes allow you to specify a series of simple actions which combined together can perform complex tasks, similar to Automator workflows or Unix pipes.
    Downloads: 0 This Week
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  • Total Network Visibility for Network Engineers and IT Managers Icon
    Total Network Visibility for Network Engineers and IT Managers

    Network monitoring and troubleshooting is hard. TotalView makes it easy.

    This means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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  • 5
    Flask App Builder

    Flask App Builder

    Simple and rapid application development framework

    ...Labels and descriptions for each field. Automatic base validators from the model's definition. Custom validators, extra fields, and custom filters for related dropdown lists. Image and File support for upload and database field association. Field sets for Forms (Django style).
    Downloads: 1 This Week
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  • 6
    LINE Messaging API SDK for Python

    LINE Messaging API SDK for Python

    LINE Messaging API SDK for Python

    The LINE Messaging API SDK for Python makes it easy to develop bots using LINE Messaging API, and you can create a sample bot within minutes. You must upload a rich menu image and link the rich menu to a user for the rich menu to be displayed. You can create up to 1000 rich menus for one LINE Official Account with the Messaging API. The LINE Messaging API SDK for Python includes experimental asyncio support. (API may change without notice in a future version). Send push messages to multiple users at any time. ...
    Downloads: 2 This Week
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  • 7
    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,...
    Downloads: 2 This Week
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  • 8
    GIXY

    GIXY

    Nginx configuration static analyzer

    ...By default Gixy will try to analyze Nginx configuration placed in /etc/nginx/nginx.conf. Or something else, you can find all other gixy arguments with the help command: gixy --help. Gixy is available as a Docker image from the Docker hub. To use it, mount the configuration that you want to analyse as a volume and provide the path to the configuration file when running the Gixy image. If you have an image that already contains your nginx configuration, you can share the configuration with the Gixy container as a volume.
    Downloads: 0 This Week
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  • 9
    Attendedsysupgrade Server

    Attendedsysupgrade Server

    An image on demand server for OpenWrt based distributions

    The Attended Sysupgrade (ASU) is a service developed by OpenWrt to streamline the firmware upgrade process for devices running OpenWrt or its derivatives. It allows users to generate custom firmware images with a selected set of pre-installed packages, eliminating the need to manually reinstall packages after an upgrade. This service simplifies maintaining up-to-date and customized firmware across various devices.
    Downloads: 0 This Week
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  • Say goodbye to broken revenue funnels and poor customer experiences Icon
    Say goodbye to broken revenue funnels and poor customer experiences

    Connect and coordinate your data, signals, tools, and people at every step of the customer journey.

    LeanData is a Demand Management solution that supports all go-to-market strategies such as account-based sales development, geo-based territories, and more. LeanData features a visual, intuitive workflow native to Salesforce that enables users to view their entire lead flow in one interface. LeanData allows users to access the drag-and-drop feature to route their leads. LeanData also features an algorithms match that uses multiple fields in Salesforce.
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  • 10
    SageMaker TensorFlow Training Toolkit

    SageMaker TensorFlow Training Toolkit

    Toolkit for running TensorFlow training scripts on SageMaker

    ...After creating a SageMaker Model, you can use it to create SageMaker Batch Transform Jobs for offline inference, or create SageMaker Endpoints for real-time inference. A SageMaker Model contains references to a model.tar.gz file in S3 containing serialized model data, and a Docker image used to serve predictions with that model. A Batch Transform job runs an offline-inference job using your TensorFlow Serving model. Input data in S3 is converted to HTTP requests, and responses are saved to an output bucket in S3.
    Downloads: 0 This Week
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  • 11
    CO3D (Common Objects in 3D)

    CO3D (Common Objects in 3D)

    Tooling for the Common Objects In 3D dataset

    CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research in multi-view 3D reconstruction, novel view synthesis, and geometry-aware representation learning. Each of the thousands of sequences in CO3Dv2 captures a common object (from categories like cars, chairs, or plants) from multiple real-world viewpoints. ...
    Downloads: 1 This Week
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  • 12
    AWS SAM CLI

    AWS SAM CLI

    CLI tool to build, test, debug, and deploy Serverless applications

    The AWS Serverless Application Model (SAM) CLI is an open-source CLI tool that helps you develop serverless applications containing Lambda functions, Step Functions, API Gateway, EventBridge, SQS, SNS and more. The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and...
    Downloads: 2 This Week
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  • 13
    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    ...Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift.
    Downloads: 0 This Week
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  • 14
    Django Lifecycle Hooks

    Django Lifecycle Hooks

    Declarative model lifecycle hooks, an alternative to Signals

    ...For simple cases, you might always want something to happen at a certain point, such as after saving or before deleting a model instance. When a user is first created, you could process a thumbnail image in the background and send the user an email.
    Downloads: 0 This Week
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  • 15
    loonflow

    loonflow

    A workflow engine base on django python

    a workflow engine base on django The django-based workflow engine system (called through the http interface, can be used as a unified workflow engine within the enterprise, providing all workflows such as permission application, resource application, release application, leave, reimbursement, it service, etc. Scenario services), if there is a certain development capability, it is recommended to use only the back-end engine function, and the front-end customized development according to the...
    Downloads: 0 This Week
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  • 16
    GenAI Processors

    GenAI Processors

    GenAI Processors is a lightweight Python library

    GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which...
    Downloads: 0 This Week
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  • 17
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ...These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
    Downloads: 0 This Week
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  • 18
    Wagtail

    Wagtail

    A Django content management system focused on flexibility & UX

    Wagtail is a powerful, open source content management system that’s focused on flexibility and user experience. Built on Django, Wagtail offers precise control and flexibility for designers, developers and editors. Designed by developers for developers, Wagtail plays nicely with everything else in your tech stack so you can do more and focus on perfecting your site. Designers will find Wagtail’s simple templating system ideal for building beautiful websites just the way they want, without...
    Downloads: 0 This Week
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  • 19
    Lightly

    Lightly

    A python library for self-supervised learning on images

    ...We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. ...
    Downloads: 0 This Week
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  • 20
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    ...A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. ...
    Downloads: 0 This Week
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  • 21
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    ...Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP, GraphQL protocols with TLS. Intuitive design pattern for high-performance microservices. Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. ...
    Downloads: 0 This Week
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  • 22
    MMDeploy

    MMDeploy

    OpenMMLab Model Deployment Framework

    ...It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy.
    Downloads: 0 This Week
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  • 23
    Glumpy

    Glumpy

    Python+Numpy+OpenGL, scalable and beautiful scientific visualization

    Glumpy is a Python library that simplifies the development of high-performance, interactive OpenGL visualizations. It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and...
    Downloads: 0 This Week
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  • 24
    PyExe:YT thumbnail downloader (b) [ISA]

    PyExe:YT thumbnail downloader (b) [ISA]

    PyExe: YouTube thumbnail downloader (type-b) [I.S.A]

    PyExe: YouTube thumbnail downloader (type-b) [Improved.Simplified.Alternative] Download YouTube video thumbnails. Compatible only for windows OS.
    Downloads: 0 This Week
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  • 25
    UtilityHub

    UtilityHub

    UtilityHub is a lightweight, all-in-one desktop utility.

    UtilityHub is a lightweight, all-in-one desktop utility designed to simplify everyday document and image processing tasks. Built with a focus on speed, simplicity, and a clean dark-themed interface, UtilityHub bundles multiple essential tools into a single user-friendly application. User Interface • Clean & Intuitive GUI • Dark Theme for comfortable long-duration usage • Beginner-friendly design with minimal learning curve Technology Stack • Python • Tkinter (GUI) • SQLite (Local Storage) • Pillow / PDF Libraries • Packaged as a standalone Windows EXE System Requirements • Operating System: Windows 7 / 8 / 10 / 11 • No Internet Required • No External Dependencies ________________________________________ Installation 1. ...
    Downloads: 0 This Week
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