Search Results for "visual code studio" - Page 5
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Showing 161 open source projects for "visual code studio"
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Taylorplot_Neptune
Creation of a Taylorplot for several machine learning models
Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list. -
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CodeFormer
Towards Robust Blind Face Restoration with Codebook Lookup Transformer
...It supports cropped face restoration, whole-image enhancement, video enhancement, face colorization, and face inpainting. The repository provides pretrained model download scripts, inference commands, training code, and configuration files. It is useful for research, restoration workflows, creative tooling, and applications that need robust face recovery from poor visual inputs. -
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TaskMatrix
Enable sending and receiving images during chatting
TaskMatrix is an experimental AI ecosystem designed to connect large language models with visual foundation models, APIs, and external systems in order to complete multimodal tasks collaboratively. The project expands beyond traditional chatbot behavior by enabling AI systems to process, generate, edit, and reason about images while coordinating multiple specialized models simultaneously. Originally introduced alongside the Visual ChatGPT concept, TaskMatrix acts as an orchestration framework where a central language model delegates subtasks to domain-specific AI systems such as image generators, segmentation tools, or recognition models. ... -
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SMC - The State Machine Compiler
Translates state machine into a target programming language.
SMC takes a state machine stored in a .sm file and generates a State pattern in 14 programming languages. Includes: default transitions, transition args, transition guards, push/pop transitions and Entry/Exit actions. See User Manual for more info. -
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Orchest
Build data pipelines, the easy way
Code, run and monitor your data pipelines all from your browser! From idea to scheduled pipeline in hours, not days. Interactively build your data science pipelines in our visual pipeline editor. Versioned as a JSON file. Run scripts or Jupyter notebooks as steps in a pipeline. Python, R, Julia, JavaScript, and Bash are supported. Parameterize your pipelines and run them periodically on a cron schedule. -
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Komodo Edit
Komodo Edit is a fast and free multi-language code editor
Code faster with the IDE for today’s web languages – Python, PHP, Perl, Golang, Ruby, and more. Powerful editor with syntax highlighting, autocomplete, code refactoring, and more. Visual debugger and more to debug, inspect, and test your code. Support for Git, Mercurial, Subversion, CVS, Perforce and Bazaar. Tons of add-ons for customizing and extending features. -
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AWS GameKit Plugin for Unreal
The AWS GameKit Plugin for Unreal
...Install before proceeding. Game projects created in Unreal versions later than 4.27 are not backward compatible. AWS GameKit supports Unreal Engine version 4.27. Create the Visual Studio Solution for your game. Build GameKit C++ and copy over the DLL/PDB files. Make sure to checkout the matching version from the .gkcpp_version file in this repository. -
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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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ConvNeXt
Code release for ConvNeXt model
ConvNeXt is a modernized convolutional neural network (CNN) architecture designed to rival Vision Transformers (ViTs) in accuracy and scalability while retaining the simplicity and efficiency of CNNs. It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure... -
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pyTorch Tutorials
Build your neural network easy and fast
pyTorch Tutorials is an open-source collection of hands-on tutorials designed to teach developers how to build neural networks with the PyTorch framework. It covers the fundamentals of PyTorch from basic tensor operations to constructing full neural network models, making it suitable for beginners and intermediate learners alike. The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks,... -
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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. -
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Unet
Source code for unet-pytorch, which can train its own model
Unet-pytorch is a PyTorch implementation of U-Net for semantic segmentation workflows. The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes... -
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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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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. 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... -
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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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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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Nerfies
This is the code for Deformable Neural Radiance Fields
Nerfies demonstrates deformation-aware neural radiance fields that reconstruct and render dynamic, real-world scenes from casual video. Instead of assuming a static world, the method learns a canonical space plus a deformation field that maps changing poses or expressions back to that space during training. This lets the system generate photorealistic novel views of nonrigid subjects—faces, bodies, cloth—while preserving fine detail and consistent lighting. The training pipeline handles... -
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vae
Simple vae and cvae from keras
...Separate scripts explore CelebA image generation, convolutional VAEs, clustering-oriented variants, hyperspherical latent spaces, and vector-quantized autoencoders. The repository includes sample output from a CelebA training run as a visual reference. Its documented environment uses Python 2.7 with TensorFlow 1.8 or 1.13 and Keras 2.2.4. The code is organized as standalone experiments rather than a unified library API. It is best suited for studying older Keras implementations of latent-variable generative modeling techniques. -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...This enables detailed understanding of human shape, motion, and surface appearance directly from images or videos. 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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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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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
...This alternating “cluster & train” scheme helps the model gradually discover meaningful structure without labels. DeepCluster was one of the early successes in unsupervised visual feature learning, demonstrating that clustering-based reformulation can rival supervised baselines for many downstream tasks. The repository includes code for feature extraction, clustering, training loops, and evaluation benchmarks like linear probes. Because of its simplicity and modular design, DeepCluster has inspired many later methods. -
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,... -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
...The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as composition, clarity, and visual appeal. Instead of relying on simple image statistics, the system learns patterns that correlate with human judgments about image aesthetics and technical quality. The repository includes code for training models, performing inference, and evaluating predicted scores against labeled datasets. It also provides utilities for image preprocessing and data management that help prepare datasets for training deep learning models.
