Search Results for "matlab project for image processing with source code" - Page 2
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Showing 90 open source projects for "matlab project for image processing with source code"
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This is an image registration plug-in for Gimp. Image registration (also known as image alignment) is the process of transforming one image so that it best matches another image. This is especially useful when you want to combine two or more images that are similar but geometrically misaligned. Visit the project web page at https://gimp-image-reg.sourceforge.io for detailed information on installing and using the plug-in. Starting with version 3.0.0, this project is licensed under...
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Dolphin
Document Image Parsing via Heterogeneous Anchor Prompting”
Dolphin — maintained by ByteDance — is a project aimed at providing a high-performance, robust, and extensible media or multimedia framework / player infrastructure (or possibly a streaming media solution), intended to meet modern demands for efficiency, flexibility, and integration in media-heavy applications. It seeks to combine performant media playback or handling (audio/video decoding, streaming, buffering) with a modular, developer-friendly API that allows easy embedding into larger... -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. ... -
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UNO
A Universal Customization Method for Single and Multi Conditioning
UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is... -
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Imaging Instruments Lite
Image processing App for Windows Desktop
...website: https://agustintortolero.pythonanywhere.com/ Source code: https://github.com/agustinTortolero/Imaging-Instruments-lite -
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itom
itom - an Open Source Measurement, Automation and Evaluation Software
itom is an open source software suite for operating measurement systems, laboratory automation and data evaluation. One main application of itom is the development and operation of sensor and measurement system for instance in a laboratory environment. Therefore, the software has to be able to communicate with a wide range of different hardware systems, such as cameras or actuators and should provide a diversified and as complete as possible set of evaluation and data processing methods.... -
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Weak-to-Strong
Implements weak-to-strong learning for training stronger ML models
Weak-to-Strong is an OpenAI research codebase that implements the concept of weak-to-strong generalization, as described in the accompanying paper. The project provides tools for training larger “strong” models using labels or guidance generated by smaller “weak” models. Its core functionality focuses on binary classification tasks, with support for fine-tuning pretrained language models and experimenting with different loss functions, including confidence-based auxiliary losses. The... -
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Django Lifecycle Hooks
Declarative model lifecycle hooks, an alternative to Signals
This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django's built-in approach to offering lifecycle hooks is Signals. However, my team often finds that Signals introduce unnecessary indirection and are at odds with Django's "fat models" approach. Django Lifecycle Hooks supports Python 3.7, 3.8 and 3.9, Django 2.0.x, 2.1.x, 2.2.x, 3.0.x, 3.1.x, and 3.2.x. For simple cases, you might always want something to happen at a... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a... -
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Lightly
A python library for self-supervised learning on images
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... -
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SAM 2
The repository provides code for running inference with SAM 2
SAM2 is a next-generation version of the Segment Anything Model (SAM), designed to improve performance, generalization, and efficiency in promptable image segmentation tasks. It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and... -
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
DAE Tools is a cross-platform equation-based object-oriented modelling, simulation and optimisation software. It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as... -
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Madagascar is a software package for geophysical data processing and reproducible numerical experiments. The package mission is to provide a convenient environment for researchers working with digital image and data processing in geophysics and related fields.
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PixelToPath
Convert PNG to SVG with a simple GUI tool.
PixelToPath is an open-source application that converts PNG images into scalable vector graphics (SVG) using the Potrace engine. Designed with simplicity in mind, it provides an intuitive graphical interface to adjust vectorization settings such as smoothing, threshold, and curve precision. PixelToPath is available as a standalone executable for Windows (no Python or installation required) and as a source version for Linux and Windows users who prefer customization. Potrace is fully... -
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis... -
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This software project provides a set of tools developed by Nicolas Saunier at Polytechnique Montreal and his collaborators for transportation data processing, in particular road traffic, motorized and non-motorized. The project consists in particular in tools for the most typical transportation data type, trajectories, i.e. temporal series of positions.
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pfeMAME
Python front end for MAME that can run in Linux, Windows, and MacOS
pfeMAME is a front end for the Multiple Arcade Game Emulator (MAME) written in (wx)Python. It is cross platform (tested on Linux (Ubuntu), Windows (7, 8, 10, 11), and MacOS. ). It also includes a graphical Tile View designed for MAME cabinets which allows control using joystick / gamepad. It supports favourite game flagging, MESS systems, Software Lists (for systems), per-rom input mapping, and launching of other emulation engines. pfeMAME was written by Gareth Finch and the development... -
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smolOS
A tiny and simple research operating system
smolOS is a minimalist 16-bit operating system written in pure Assembly for x86 real mode. Its goal is to demonstrate the fundamentals of how an OS boots, handles input, and displays output using only the most essential code. smolOS fits in a single boot sector and runs directly on BIOS-compatible hardware or emulators like QEMU. It’s ideal for those seeking to understand bootloaders, BIOS interrupts, and ultra-low-level system programming through a practical and tiny project. -
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GXSM
Scanning Probe Microscopy Controller and Data Visualization Software
...Based on several hardware options it supports a commercially available DSP hardware and provided also Open Source Code for all the low level signal processing tasks and instrument controls in a most flexible and adaptable manner. All latest software is available via SVN only or Live Demo/Install CD: http://www.ventiotec.de/linux/GXSM-Linux.iso -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is... -
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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... -
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GLIDE (Text2Im)
GLIDE: a diffusion-based text-conditional image synthesis model
glide-text2im is an open source implementation of OpenAI’s GLIDE model, which generates photorealistic images from natural language text prompts. It demonstrates how diffusion-based generative models can be conditioned on text to produce highly detailed and coherent visual outputs. The repository provides both model code and pretrained checkpoints, making it possible for researchers and developers to experiment with text-to-image synthesis. -
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LayoutParser
A Unified Toolkit for Deep Learning Based Document Image Analysis
With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser.... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing...
