Showing 72 open source projects for "batch scanning software"

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  • 1
    Jianying Headless

    Jianying Headless

    Native Jianying drafts, isolated editing/export

    Jianying Headless is a local automation toolkit for creating and editing Jianying Pro video projects on macOS. Structured editing plans can generate editable drafts with multiple video, audio, text, and overlay tracks. Existing projects can be modified inside isolated copies so the original draft is not overwritten. The system supports local media, fonts, keyframes, selected masks, transitions, and native MP4 export through an installed Jianying engine. A Python command-line interface and...
    Downloads: 0 This Week
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  • 2
    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: 1 This Week
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  • 3
    Imagen - Pytorch

    Imagen - Pytorch

    Implementation of Imagen, Google's Text-to-Image Neural Network

    Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
    Downloads: 4 This Week
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  • 4
    SageMaker Spark Container

    SageMaker Spark Container

    Docker image used to run data processing workloads

    Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. 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...
    Downloads: 0 This Week
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  • 5
    TextTest is an application-independent tool for text-based functional testing. This means running a batch-mode binary in lots of different ways, and using the text output produced as a means of controlling the behaviour of that application.
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    Downloads: 24 This Week
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  • 6

    tacklelib

    The C++11 library, msvc2015u3/gcc5.4 + cmake,python,bash,vbs modules

    https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README.md https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.deps.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.linux_x86_64.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/changelog.txt
    Downloads: 0 This Week
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  • 7

    contools

    console tools, batch scripts, vbs scripts

    Downloads: 0 This Week
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  • 8

    Ultimate Media Downloader

    An Open source media downloader for downloading videos and audios

    Ultimate Media Downloader (UMD) is a professional-grade, open-source command-line tool that consolidates media downloading across 1000+ platforms into a single, intuitive interface. Built with Python and powered by industry-standard extraction engines, it delivers enterprise-level capabilities with consumer-friendly simplicity. Whether you're downloading a single YouTube video, extracting audio from Spotify playlists, archiving TikTok content, or batch-processing entire music libraries, UMD...
    Downloads: 0 This Week
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  • 9
    Mythril

    Mythril

    Security analysis tool for EVM bytecode. Supports smart contracts

    Mythril is a security analysis tool for EVM bytecode. It detects security vulnerabilities in smart contracts built for Ethereum, Hedera, Quorum, Vechain, Roostock, Tron and other EVM-compatible blockchains. It uses symbolic execution, SMT solving and taint analysis to detect a variety of security vulnerabilities. It's also used (in combination with other tools and techniques) in the MythX security analysis platform. If you are a smart contract developer, we recommend using MythX tools which...
    Downloads: 2 This Week
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  • 10
    TorchQuantum

    TorchQuantum

    A PyTorch-based framework for Quantum Classical Simulation

    A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing.
    Downloads: 1 This Week
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  • 11
    ControlNet for Stable Diffusion WebUI

    ControlNet for Stable Diffusion WebUI

    WebUI extension for ControlNet

    Stable Diffusion WebUI ControlNet is an extension that adds ControlNet and related image-conditioning systems to AUTOMATIC1111’s Stable Diffusion WebUI. It injects control models dynamically without requiring them to be merged into the base Stable Diffusion checkpoint. Users can guide generation with structures such as edges, depth, poses, line art, segmentation maps, and other preprocessed inputs. Multiple ControlNet units can influence the same generation with independent weights and...
    Downloads: 0 This Week
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  • 12
    Transformers4Rec

    Transformers4Rec

    Transformers4Rec is a flexible and efficient library

    Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation...
    Downloads: 8 This Week
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  • 13
    Wifipumpkin3

    Wifipumpkin3

    Powerful framework for rogue access point attack

    wifipumpkin3 is powerful framework for rogue access point attack, written in Python, that allow and offer to security researchers, red teamers and reverse engineers to mount a wireless network to conduct a man-in-the-middle attack.
    Downloads: 6 This Week
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  • 14
    S3cmd

    S3cmd

    Command line tool for managing Amazon S3 and CloudFront services

    S3cmd (s3cmd) is a free command line tool and client for uploading, retrieving and managing data in Amazon S3 and other cloud storage service providers that use the S3 protocol, such as Google Cloud Storage or DreamHost DreamObjects. It is best suited for power users who are familiar with command-line programs. It is also ideal for batch scripts and automated backup to S3, triggered from cron, etc. S3cmd is written in Python. It's an open-source project available under GNU Public License v2...
    Downloads: 4 This Week
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  • 15
    fastMRI

    fastMRI

    A large open dataset + tools to speed up MRI scans using ML

    fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data...
    Downloads: 0 This Week
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  • 16
    iJEPA

    iJEPA

    Official codebase for I-JEPA

    i-JEPA (Image Joint-Embedding Predictive Architecture) is a self-supervised learning framework that predicts missing high-level representations rather than reconstructing pixels. A context encoder sees visible regions of an image and predicts target embeddings for masked regions produced by a slowly updated target encoder, focusing learning on semantics instead of texture. This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer...
    Downloads: 1 This Week
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  • 17
    Real-ESRGAN

    Real-ESRGAN

    Real-ESRGAN aims at developing Practical Algorithms

    Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The...
    Downloads: 150 This Week
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  • 18
    YOLOV4 Pytorch

    YOLOV4 Pytorch

    This is a source code for YoloV4-pytorch that can be used to train you

    YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU...
    Downloads: 4 This Week
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  • 19
    YOLOV3 Pytorch

    YOLOV3 Pytorch

    This is a source code for yolo3-pytorch

    YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target...
    Downloads: 17 This Week
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  • 20
    Jraph

    Jraph

    A Graph Neural Network Library in Jax

    Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time...
    Downloads: 0 This Week
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  • 21
    Faster-Rcnn

    Faster-Rcnn

    This is a pytorch implementation library of faster-rcnn

    Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature...
    Downloads: 4 This Week
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  • 22
    DeepLabv3 Plus

    DeepLabv3 Plus

    Encoder-Decoder with Atrous Separable Convolution

    DeepLabv3 Plus is a PyTorch implementation of DeepLabv3+ for semantic segmentation. It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2...
    Downloads: 3 This Week
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  • 23
    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...
    Downloads: 0 This Week
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  • 24
    ReconSpider

    ReconSpider

    Most Advanced Open Source Intelligence (OSINT) Framework

    ReconSpider is most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Addresses, Emails, Websites, and Organizations and find out information from different sources. ReconSpider can be used by Infosec Researchers, Penetration Testers, Bug Hunters, and Cyber Crime Investigators to find deep information about their target. ReconSpider aggregate all the raw data, visualize it on a dashboard, and facilitate alerting and monitoring on the data. Recon Spider also combines the...
    Downloads: 3 This Week
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  • 25
    PyTorch SimCLR

    PyTorch SimCLR

    PyTorch implementation of SimCLR: A Simple Framework

    For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the...
    Downloads: 0 This Week
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