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38 مستودعات

Awesome GitHub RepositoriesPixel Normalizers

Utilities for scaling pixel intensity values to specific ranges for neural network input.

Distinct from Image Preprocessing Utilities: Focuses on pixel-level intensity scaling rather than general image dimension standardization.

Explore 38 awesome GitHub repositories matching data & databases · Pixel Normalizers. Refine with filters or upvote what's useful.

Awesome Pixel Normalizers GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • d2l-ai/d2l-enالصورة الرمزية لـ d2l-ai

    d2l-ai/d2l-en

    29,001عرض على GitHub↗

    This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex

    Scales pixel values to specific ranges to ensure compatibility with activation functions during training.

    Pythonbookcomputer-visiondata-science
    عرض على GitHub↗29,001
  • yaronn/blessed-contribالصورة الرمزية لـ yaronn

    yaronn/blessed-contrib

    15,745عرض على GitHub↗

    blessed-contrib is a terminal user interface framework and a Node.js console widget library designed for building data-driven command line interfaces. It serves as an ASCII data visualization toolkit and a dashboard framework for organizing grid-based layouts and interactive elements within a console. The project provides a collection of reusable terminal components, including a command line image renderer and tools for text-based graphic rendering. It specifically enables the creation of terminal dashboards through a system for positioning multiple widgets across rows and columns and a mecha

    Converts image pixel data into characters to enable graphical image display within a text-only terminal.

    JavaScript
    عرض على GitHub↗15,745
  • imagemagick/imagemagickالصورة الرمزية لـ ImageMagick

    ImageMagick/ImageMagick

    15,742عرض على GitHub↗

    ImageMagick is a comprehensive software suite for the creation, editing, composition, and conversion of digital images. It functions as both a command-line utility for batch processing and automation, and as a programming library that allows developers to integrate advanced image manipulation capabilities into external applications. The project is distinguished by its modular architecture, which supports hundreds of image formats through a pluggable coder system and external delegate libraries. It is designed for high-performance environments, utilizing memory-mapped pixel caching, stream-ori

    Forces pixels below or above a specific value to black or white to create high-contrast masks.

    Ccommand-line-image-tooldigital-image-editingimage-conversion
    عرض على GitHub↗15,742
  • oliver-moran/jimpالصورة الرمزية لـ oliver-moran

    oliver-moran/jimp

    14,621عرض على GitHub↗

    Jimp is a JavaScript image processing library and Node.js manipulation tool designed to perform image transformations and edits entirely within a JavaScript environment. It is a zero-dependency image library that operates without requiring native binaries or external system software dependencies. The project provides a programmatic interface for automated image transformations, including resizing, cropping, and filtering. It supports the creation of custom image pipelines and server-side image editing by processing data without relying on native system tools.

    Provides a direct interface for reading and writing raw pixel data via a coordinate-based grid.

    TypeScript
    عرض على GitHub↗14,621
  • hammerspoon/hammerspoonالصورة الرمزية لـ Hammerspoon

    Hammerspoon/hammerspoon

    14,497عرض على GitHub↗

    Hammerspoon is a programmable automation engine for macOS that enables deep system-level control through a Lua scripting environment. By bridging high-level scripts with native Objective-C APIs, it allows users to interact with the operating system's accessibility tree, intercept hardware input streams, and manage the lifecycle of running applications. The project distinguishes itself through an event-driven architecture that registers asynchronous hooks for system notifications and hardware events. This allows for real-time automation, such as remapping keyboard and mouse inputs, managing wi

    Reads pixel colors and converts image data for programmatic inspection.

    Objective-Cautomationhammerspoonirc
    عرض على GitHub↗14,497
  • paddlepaddle/paddledetectionالصورة الرمزية لـ PaddlePaddle

    PaddlePaddle/PaddleDetection

    14,243عرض على GitHub↗

    PaddleDetection is an object detection framework designed for the end-to-end development, training, and deployment of computer vision models. It provides a comprehensive library of modular neural network architectures and pipelines that support object detection, instance segmentation, and multi-object tracking tasks. The project distinguishes itself through a configuration-driven approach that decouples model components like backbones and heads, allowing for the flexible assembly of custom vision workflows. It incorporates advanced techniques such as anchor-free detection logic, joint detecti

    Standardizes image pixel values and bounding box coordinates to ensure consistent model input.

    Pythonblazefacedeepsortdetr
    عرض على GitHub↗14,243
  • rivo/tviewالصورة الرمزية لـ rivo

    rivo/tview

    13,928عرض على GitHub↗

    tview is a library for building interactive text-based user interfaces in Go. It functions as a toolkit for managing event loops, user input, and screen rendering, providing a framework of pre-built widgets and an integrated layout engine for creating command-line applications. The project distinguishes itself through a comprehensive layout system that uses grid and flexbox models to create responsive designs. It also supports UI layer stacking to manage multiple screens and modal overlays. The framework includes a diverse suite of interactive components for data display, such as tables and

    A process for displaying images in the terminal by approximating pixels with graphical characters and applying dithering.

    Gogolangterminal-baseduser-interface
    عرض على GitHub↗13,928
  • wangshub/wechat_jump_gameالصورة الرمزية لـ wangshub

    wangshub/wechat_jump_game

    13,833عرض على GitHub↗

    This project is a Python-based game automation bot and computer vision assistant designed to automate gameplay on Android devices. It functions as a controller that identifies game elements via pixel color scanning and simulates touch inputs to execute gameplay without manual intervention. The system distinguishes itself through the use of anti-detection measures, implementing interaction coordinate management and timing offsets to avoid being flagged by security systems. It also employs resolution-dependent scaling coefficients to maintain jump accuracy across different device screen sizes.

    Analyzes pixel-level color data to identify and locate game objects on the screen.

    Pythonadbpythonwechat-app
    عرض على GitHub↗13,833
  • python-pillow/pillowالصورة الرمزية لـ python-pillow

    python-pillow/Pillow

    13,637عرض على GitHub↗

    Pillow is a Python image processing library and digital image manipulation toolkit used for opening, manipulating, and saving various image file formats. It serves as a multi-format image codec wrapper that enables the reading and writing of diverse standards such as JPEG, PNG, TIFF, and BMP. The library provides tools for programmatic image manipulation, including resizing, cropping, rotating, and transforming visual content through direct pixel data modification. It supports pixel data analysis to extract and modify raw information for custom visual processing and data transformations. The

    Provides interfaces for extracting and modifying raw pixel information for custom visual processing.

    Pythonccross-platformimage
    عرض على GitHub↗13,637
  • octalmage/robotjsالصورة الرمزية لـ octalmage

    octalmage/robotjs

    12,740عرض على GitHub↗

    Robotjs is a native Node.js automation library and desktop input simulator. It uses C++ bindings to provide low-level access to operating system functions, allowing for the programmatic control of the mouse and keyboard and the analysis of screen pixels. The library functions as a toolkit for automating user interfaces and desktop workflows, including those within Electron applications. It enables the simulation of key presses and mouse movements to automate interactions with desktop software and perform automated data entry. Its capabilities extend to screen pixel analysis, where it capture

    Inspects pixel-level color data to monitor and detect visual changes on the display.

    C
    عرض على GitHub↗12,740
  • marcotcr/limeالصورة الرمزية لـ marcotcr

    marcotcr/lime

    12,142عرض على GitHub↗

    This project is an agnostic model interpretability framework and explainability tool designed to provide local interpretable explanations for individual predictions. It functions as a local surrogate model that approximates the behavior of any machine learning classifier or regression model to identify the most influential features for a specific instance. The framework is designed to be model-agnostic, meaning it can explain predictions across tabular, text, and image data regardless of the underlying architecture. It employs local linear approximations and feature importance visualization t

    Groups pixels into contiguous regions to treat blocks of pixels as single features during model analysis.

    JavaScript
    عرض على GitHub↗12,142
  • soumith/ganhacksالصورة الرمزية لـ soumith

    soumith/ganhacks

    11,619عرض على GitHub↗

    This project is a PyTorch-based generative framework and implementation template for building Generative Adversarial Networks. It provides a collection of foundational toolkits and architectural patterns designed to synthesize high-quality artificial data while focusing on the stability of adversarial neural networks. The framework distinguishes itself through a specialized toolkit for conditional image generation, which integrates discrete labels and auxiliary classification into the training process. It utilizes specific mechanisms to guide the generative process toward target classes by co

    Provides utilities to scale input data and apply activation functions for consistent distribution.

    عرض على GitHub↗11,619
  • android/ndk-samplesالصورة الرمزية لـ android

    android/ndk-samples

    10,513عرض على GitHub↗

    The Android NDK samples provide a comprehensive collection of code examples demonstrating how to integrate C and C++ native code into Android applications. This repository serves as a practical guide for developers utilizing the Android Native Development Kit to implement performance-critical application components that require direct hardware access and low-level system interaction. The project highlights the use of the Java Native Interface to bridge managed code with native modules, enabling cross-language function calls and efficient data exchange. It demonstrates how to manage native act

    Retrieves and modifies raw pixel data from image objects to perform custom image processing.

    C++
    عرض على GitHub↗10,513
  • openvinotoolkit/openvinoالصورة الرمزية لـ openvinotoolkit

    openvinotoolkit/openvino

    10,414عرض على GitHub↗

    OpenVINO is an AI inference engine and model serving platform designed to execute optimized deep learning models across CPUs, GPUs, and NPUs through a unified API. It includes a model optimization toolkit for converting, quantizing, and compressing models from various frameworks, alongside a specialized generative AI runtime for large language models. The project distinguishes itself through a plugin-based hardware acceleration layer that maps neural network operations to vendor-specific drivers. It features advanced execution mechanisms such as continuous batching, speculative decoding, and

    Subtracts mean values and divides by standard deviations to normalize tensors for model inference.

    C++aicomputer-visiondeep-learning
    عرض على GitHub↗10,414
  • cadene/pretrained-models.pytorchالصورة الرمزية لـ Cadene

    Cadene/pretrained-models.pytorch

    9,102عرض على GitHub↗

    This project is a pretrained model library for PyTorch, providing a collection of convolutional neural network architectures and weights. It serves as a computer vision model zoo for image classification and feature extraction, offering a framework for transfer learning where pretrained networks are adapted for custom image recognition tasks. The library focuses on transforming images into high-level numerical representations and calculating class probability scores. It includes utilities for downloading and initializing standard architectures such as ResNet, Inception, and Xception. Capabil

    Includes utilities to normalize image pixels using mean and standard deviation values specific to each architecture.

    Pythonimagenetinceptionpretrained
    عرض على GitHub↗9,102
  • bishopfox/unredacterالصورة الرمزية لـ BishopFox

    BishopFox/unredacter

    8,351عرض على GitHub↗

    Unredacter هو أداة لرؤية الحاسوب لإعادة بناء النصوص وأداة للطب الشرعي للصور مصممة لاستعادة الأحرف المخفية من الصور المنقطة (pixelated). تعمل كأداة لعكس التنقيط لتحديد النص داخل الكتل المرئية المحجوبة. يستخدم النظام عملية مقارنة كتل الصور المنقطة مقابل أحرف مرشحة مُصيّرة تطابق الأنماط الطباعية للنص المستهدف. يسمح هذا بإعادة بناء المعلومات المحجوبة من خلال التحليل المرئي الآلي. يغطي المشروع قدرات لتحليل الطب الشرعي الرقمي، واختبار تنقيح الصور، وتقييم تسريب المعلومات للتحقق من فعالية تقنيات الإخفاء القائمة على الصور.

    Maps pixelated image data back to characters by comparing blocks against rendered templates.

    TypeScript
    عرض على GitHub↗8,351
  • vietnh1009/ascii-generatorالصورة الرمزية لـ vietnh1009

    vietnh1009/ASCII-generator

    8,270عرض على GitHub↗

    ASCII-generator is a tool for converting images and videos into text-based ASCII art. It functions as an image-to-ASCII converter and a video-to-ASCII processor that maps pixel intensity and color to specific alphanumeric characters. The system generates stylized visual representations by transforming visual files into grayscale or colored ASCII art text files. It can render static images into text art or process video files into a sequence of ASCII art frames for animation. The rendering process involves translating image pixels into text grids and mapping brightness values to characters ba

    Maps pixel brightness values to a predefined set of ASCII characters based on visual density.

    Pythonasciiascii-artascii-generator
    عرض على GitHub↗8,270
  • mic-dkfz/nnunetالصورة الرمزية لـ MIC-DKFZ

    MIC-DKFZ/nnUNet

    8,041عرض على GitHub↗

    nnU-Net is a PyTorch-based deep learning framework for the supervised semantic segmentation of 2D and 3D biomedical images. It functions as an automated medical imaging pipeline that generates predicted masks and labels from clinical images. The system distinguishes itself by using dataset-driven auto-configuration to automatically select the optimal network architecture, preprocessing steps, and training hyperparameters based on the specific properties of the input medical dataset. The framework covers a broad range of capabilities including medical dataset preparation, intensity normalizat

    Provides utilities for scaling pixel intensity values using dataset-specific statistics to ensure consistent distributions across modalities.

    Pythonsegmentation
    عرض على GitHub↗8,041
  • tingsongyu/pytorch_tutorialالصورة الرمزية لـ TingsongYu

    TingsongYu/PyTorch_Tutorial

    8,018عرض على GitHub↗

    This project is a comprehensive collection of educational examples and reference implementations for building vision and language models using PyTorch. It serves as a deep learning tutorial covering the end-to-end process of developing neural networks, from initial architecture definition to final production deployment. The repository provides detailed guides on implementing a wide range of domain-specific models, including convolutional neural networks for object detection and segmentation, as well as transformer and recurrent architectures for natural language processing. It emphasizes gene

    Standardizes image pixel values and coordinates to ensure they meet required normalization standards.

    Python
    عرض على GitHub↗8,018
  • sixlabors/imagesharpالصورة الرمزية لـ SixLabors

    SixLabors/ImageSharp

    7,954عرض على GitHub↗

    ImageSharp is a .NET image processing library and manipulation framework used for decoding, encoding, and modifying digital images. It functions as a comprehensive toolkit for resizing, cropping, and applying pixel-level filters while managing color profiles and pixel data across various file formats. The project integrates a 2D vector graphics engine and a typography rendering engine to draw geometric shapes, paths, and complex stylized text onto images. It also includes a geometry boolean operation library for calculating intersections, unions, and differences between complex polygons and c

    Provides direct read and write access to raw pixel data via indexers and row-based buffers.

    C#bmpc-sharpdrawing
    عرض على GitHub↗7,954
السابق12التالي
  1. Home
  2. Data & Databases
  3. Image Preprocessing Utilities
  4. Pixel Normalizers

استكشف الوسوم الفرعية

  • Histogram-Based ScalersScales pixel values to a 0-1 range using frequency-based histogram binning. **Distinct from Pixel Normalizers:** Distinct from Pixel Normalizers: uses histogram binning rather than min-max or z-score normalization.
  • Input Normalizers3 وسوم فرعيةUtilities for standardizing image pixel values and bounding box coordinates for model input. **Distinct from Pixel Normalizers:** Distinct from Pixel Normalizers: focuses on both pixel-level and coordinate-level normalization for computer vision models.
  • Intensity Thresholders1 وسم فرعيUtilities for binarizing pixel intensity values to create high-contrast masks. **Distinct from Pixel Normalizers:** Distinct from Pixel Normalizers: focuses on thresholding rather than range normalization.
  • Pixel Analyzers3 وسوم فرعيةTools for inspecting pixel-level color data and converting image content into text-based representations. **Distinct from Pixel Normalizers:** Distinct from Pixel Normalizers: focuses on inspection and conversion rather than intensity scaling for neural networks.
  • Pixel Removal UtilitiesTools for deleting interior rows or columns and shifting pixels to close gaps. **Distinct from Pixel Normalizers:** Distinct from pixel normalizers: focuses on structural pixel removal.