Search Results for "visual" - Page 11
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Showing 471 open source projects for "visual"
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Machine Learning Glossary
Machine learning glossary
Machine Learning Glossary is an open educational project that provides clear explanations of machine learning terminology and concepts through visual diagrams and concise definitions. The goal of the repository is to make machine learning topics easier to understand by presenting definitions alongside examples, visual illustrations, and references for further learning. It covers a wide range of topics including neural networks, regression models, optimization techniques, loss functions, and evaluation metrics. ... -
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pyTorch Tutorials
Build your neural network easy and fast
...Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side. -
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ELECHEM & FARADAY (Electrochemical)
Simulation tool for electrochemical / electroplating parameters
FARADAY and ELECHEM are the two portable computer programs, find useful for electrochemical researchers, electroplating units, battery as well as supercapacitor industries, process engineers, materials scientists & engineers, electroplaters, hobbyists, and students to evaluate various electrochemical deposition parameters. These computational tools can be used to simulate various electrochemical deposition data or electroplating parameters for metals, alloys, composites as well as energy... -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase in their native Python libraries. ... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the full image—making pretraining computationally efficient. ... -
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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. GLIDE includes advanced techniques such as classifier-free guidance, which improves the quality and alignment of generated images with the input text. The project also offers sampling scripts and utilities for exploring how diffusion models can be applied to multimodal tasks. ... -
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Scylla
Intelligent proxy pool for collecting and managing public proxies
...Scylla also runs a built-in HTTP forward proxy server that can dynamically select a recently validated proxy whenever a request is made. In addition to the API, the system provides a web-based interface where users can view available proxies and monitor their global distribution through a visual dashboard. It is commonly used by developers who need scalable proxy management when gathering data from the internet or building datasets for machine learning. -
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GANformer
Generative Adversarial Transformers
...The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of each in light of the other and encourage the emergence of compositional representations of objects and scenes. In contrast to the classic transformer architecture, it utilizes multiplicative integration that allows flexible region-based modulation and can thus be seen as a generalization of the successful StyleGAN network. ... -
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Deep Feature Rotation Multimodal Image
Implementation of Deep Feature Rotation for Multimodal Image
...Our approach is a representative of the many ways of augmentation for intermediate feature embedding without consuming too much computational expense. Prepare your content image and style image. I provide some in the data/content and data/style and you can try to use them easily. We provide a visual comparison between other rotation angles that do not appear in the paper. The rotation angles will produce a very diverse number of outputs. This has proven the effectiveness of our method with other methods. -
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DeepDanbooru
AI based multi-label girl image classification system
DeepDanbooru is a deep learning system designed to automatically tag anime-style images using neural networks trained on datasets derived from the Danbooru imageboard. The project focuses on multi-label image classification, where a model predicts multiple descriptive tags that represent visual elements in an image. These tags may include characters, styles, clothing, emotions, or other attributes associated with anime artwork. The system uses convolutional neural networks trained on large datasets of tagged images to learn relationships between visual features and textual labels. Because the Danbooru dataset contains millions of images with extensive annotations, it provides a valuable training resource for machine learning models specializing in illustration analysis. ... -
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Lines
Lines a game written in Python two players through internet
Lines is an old game that I had programed in python (pygame). I usually prefer to use visual c# as a programing language. However, I wrote this game in python in a time period, I was learning python. Here, I want to thank all people who have training videos in youtube, they helped me a lot to make this program. Some of the code of the program is from these videos. The game can be played from one or two persons through internet. -
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BPYTOP
Linux/OSX/FreeBSD resource monitor
BPYTOP is a feature-rich, terminal-based resource monitor written in Python 3 that provides a highly visual overview of system performance. It displays real-time usage and statistics for CPU, memory, disks, network, and processes, with colorful graphs and widgets that update at configurable intervals. Users can drill into a process list, sort by various metrics, view tree hierarchies, and quickly spot heavy resource consumers. The tool is highly configurable through both an in-app options menu and a detailed configuration file, allowing customization of themes, update frequency, graph types, temperature sensors, and which “boxes” (CPU, memory, network, processes) are shown. ... -
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MoCo v3
PyTorch implementation of MoCo v3
MoCo v3 is a PyTorch reimplementation of Momentum Contrast v3 (MoCo v3), Facebook Research’s state-of-the-art self-supervised learning framework for visual representation learning using ResNet and Vision Transformer (ViT) backbones. Originally developed in TensorFlow for TPUs, this version faithfully reproduces the paper’s results on GPUs while offering an accessible and scalable PyTorch interface. MoCo v3 introduces improvements for training self-supervised ViTs by combining contrastive learning with transformer-based architectures, achieving strong linear and end-to-end fine-tuning performance on ImageNet benchmarks. ... -
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Battery Life Saver
Battery Life Saver can extend the life span of laptop batteries.
Battery Life Saver can extend the life span of laptop batteries. Using a Laptop Battery continuously by overcharging above 90% or by below 15%, reduces its life span. This light-weight .exe program, Battery Life Saver will alarm, on excess charging or discharging. Set the desired Battery Limit Percentage using the slider, say 50% and allow the Battery Life Saver to give alarm. It automatically detects, charging and battery status. For more advanced options, contact the... -
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HostHunter
OSINT reconnaissance tool for discovering hostnames from IP addresses
HostHunter is an open source reconnaissance tool designed to discover and extract hostnames associated with a large set of IPv4 or IPv6 addresses. It helps security professionals map IP addresses to virtual hostnames using a combination of OSINT data sources and active reconnaissance techniques. This approach enables users to identify hidden or additional services that may be hosted behind a single IP address. By correlating hostname information from certificates, APIs, HTTP headers, and... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows. -
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MurExpo
Software to create an exhibition wall and hang artworks on it.
This application provides exhibition walls on which you can hang artworks (works by visual artists, student work, ...) in order to put them in a situation as in an exhibition hall. It's not software that uses 3D technology, but rather a layer-based device that you load and move around as you please. Once arranged, the works can be framed live on the wall and the exhibition space can be decorated with objects and characters. -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...The repository includes the DensePose network architecture, training code, pretrained models, and dataset tools for annotation and visualization. DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
...These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. Many of the notebooks integrate with tools like folium, ipyleaflet, and geemap to bridge Earth Engine data with Python’s rich ecosystem for plotting and analysis. Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab. -
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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... -
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NH Folder Hider and Locker
NH Folder Hider and Locker 1.0 is a powerful application which provide
NH Folder Hider and Locker 1.0 is a powerful application which provides you the means to protect your PC files from the unauthorized access. As we all know that nowadays every computer is connected with the Internet so there is always a threat for your personal data to be accessed. There is always danger if you are having the confidential files in your PC so this software offers that extra sense of security. It has a well-organized and very interactive interface which provides you the... -
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BeaEngine 5
BeaEngine disasm project
...If you want to analyze malicious codes and more generally obfuscated codes, BeaEngine sends back a complex structure that describes precisely the analyzed instructions. You can use it in C/C++ (usable and compilable with Visual Studio, GCC, MinGW, DigitalMars, BorlandC, WatcomC, SunForte, Pelles C, LCC), in assembler (usable with masm32 and masm64, nasm, fasm, GoAsm) in C#, in Python3, in Delphi, in PureBasic and in WinDev. You can use it in user mode and kernel mode. -
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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. ... -
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BasicSR
Winning Solution in NTIRE19 Challenges on Video Restoration
...The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and Temporal Spatial Attention fusion) that align information across frames and emphasize important features for restoration, enabling state-of-the-art performance on benchmarks such as the REDS challenge. By fusing spatial and temporal context, EDVR produces significantly improved visual quality in restored videos compared with approaches that treat each frame independently.
