Search Results for "active shape model" - Page 3
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Showing 71 open source projects for "active shape model"
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Ultimate Media Downloader
An Open source media downloader for downloading videos and audios
...Whether you're downloading a single YouTube video, extracting audio from Spotify playlists, archiving TikTok content, or batch-processing entire music libraries, UMD handles it all with elegance and efficiency. IT CONSISTS OF : 1. Unified Interface: One command, 1000+ platforms. No tool shopping, no mental model switching. 2. Production-Ready, Zero Friction Installation: Most users go from hearing about the tool to downloading content in under 5 minutes. 3. Active Maintenance: Codeberg hosting (after GitHub suspension) demonstrates commitment to long-term availability -
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Hiera
A fast, powerful, and simple hierarchical vision transformer
Hiera is a hierarchical vision transformer designed to be fast, simple, and strong across image and video recognition tasks. The core idea is to use straightforward hierarchical attention with a minimal set of architectural “bells and whistles,” achieving competitive or superior accuracy while being markedly faster at inference and often faster to train. The repository provides installation options (from source or Torch Hub), a model zoo with pre-trained checkpoints, and code for evaluation... -
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DeathStar
RESTful API to automate gaining Domain Enterprise Admin rights
DeathStar is a Python-based red-team automation project that integrates with the Empire REST API for Active Directory security assessment. Its main purpose is to demonstrate how common Active Directory misconfigurations can be chained together in automated attack-path scenarios. The project focuses on controlled assessment workflows that model privilege escalation paths in enterprise Windows environments. Version 0.2.0 introduced a full rewrite with asynchronous execution, multi-domain and multi-forest support, a plugin system, and active monitoring behavior. ... -
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GPT-2 Output Dataset
Dataset of GPT-2 outputs for research in detection, biases, and more
...The repository provides scripts and metadata for working with the dataset, with the goal of supporting research in areas like detection, evaluation of text coherence, and analysis of generative models. While no active development is expected, the dataset remains a useful benchmark for tasks involving text classification, style analysis, and generative model evaluation. -
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EmotiVoice
Multi-Voice and Prompt-Controlled TTS Engine
EmotiVoice is a multi-voice, prompt-controlled text-to-speech engine designed to generate highly expressive speech across thousands of voices. It supports both English and Chinese and ships with over 2,000 preset voices, making it suitable for everything from characters and virtual anchors to narration and dialogue. The core idea is prompt-based emotional and style control: you can ask the engine to speak “happy,” “sad,” “excited,” or with other high-level style prompts that shape prosody,... -
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DragGAN
Official Code for DragGAN (SIGGRAPH 2023)
...DragGAN has gained attention for making complex image edits, such as pose changes or shape adjustments, accessible through an intuitive interface. The repository provides code and GUI tooling that allow researchers and advanced users to experiment with this next-generation controllable image manipulation technique. -
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OGB
Benchmark datasets, data loaders, and evaluators for graph machine
The Open Graph Benchmark (OGB) is a collection of realistic, large-scale, and diverse benchmark datasets for machine learning on graphs. OGB datasets are automatically downloaded, processed, and split using the OGB Data Loader. The model performance can be evaluated using the OGB Evaluator in a unified manner. OGB is a community-driven initiative in active development. We expect the benchmark datasets to evolve. OGB provides a diverse set of challenging and realistic benchmark datasets that are of varying sizes and cover a variety graph machine learning tasks, including prediction of node, link, and graph properties. ... -
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jiant
jiant is an nlp toolkit
Jiant is a multitask NLP framework for fine-tuning transformer-based models on multiple natural language understanding (NLU) tasks. -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
DensePose is a computer vision system that maps all human pixels in an RGB image to the 3D surface of a human body model. It extends human pose estimation from predicting joint keypoints to providing dense correspondences between 2D images and a canonical 3D mesh (such as the SMPL model). 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. ... -
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
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Baselines
High-quality implementations of reinforcement learning algorithms
...Historically, “baselines” repositories are often used for baseline implementations of reinforcement learning algorithms or reference models (e.g. in the RL domain). If there was an OpenAI “baselines” repo, it might have contained reference implementations for reinforcement learning or model policy baselines to compare new work against. However, I couldn’t locate an active “openai/baselines” in the latest OpenAI repos, so it may have been archived, removed, or merged into other projects. If you meant a different “baselines” (e.g. OpenAI Baselines for reinforcement learning), I can look up that specific one. -
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Active Learning
Framework and examples for active learning with machine learning model
...The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks. -
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MLBox
MLBox is a powerful Automated Machine Learning python library
...Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone. -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse... -
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unite.vim
Unite and create user interfaces
...It can display and search items such as files, buffers, recently used files, registers, and other source-defined candidates. Users can then run actions on the selected items directly from the Unite interface. The plugin is designed around a source-and-action model, which makes it flexible for navigation, selection, filtering, and workflow automation inside Vim. It became influential because it turned many editor tasks into a unified candidate-selection experience. Although active development has shifted toward newer successors, unite.vim remains a notable reference point for extensible Vim user-interface design. -
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HYBRYD
Library written in C with Python API for IPv6 networking
...I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as possible so that you can download pieces of codes. The aim of that coding was to use primary linux commands easily codable and make an object of an IPv6 connection. Moreover, the model is full-state! -
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WISP
Weighted Implementation of Suboptimal Paths (WISP)
UPDATE: LATEST VERSION AT http://git.durrantlab.com//jdurrant/wisp Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site often many angstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. ... -
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GUI for game development. Written on Python. Model-View-Controller interface. Powerfull skinning support. Now under active development.
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Nemotron 3 Super
Open language model developed by NVIDIA as part of Nemotron-3 family
NVIDIA-Nemotron-3-Super-120B-A12B-FP8 is a large-scale open language model developed by NVIDIA as part of the Nemotron-3 family of generative AI systems designed for advanced reasoning, conversational interaction, and agent-based workflows. The model contains approximately 120 billion parameters, but employs a Mixture-of-Experts architecture that activates only a smaller subset of parameters during inference, improving computational efficiency while maintaining high capability. Its... -
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gpt-oss-20b
OpenAI’s compact 20B open model for fast, agentic, and local use
GPT-OSS-20B is OpenAI’s smaller, open-weight language model optimized for low-latency, agentic tasks, and local deployment. With 21B total parameters and 3.6B active parameters (MoE), it fits within 16GB of memory thanks to native MXFP4 quantization. Designed for high-performance reasoning, it supports Harmony response format, function calling, web browsing, and code execution. Like its larger sibling (gpt-oss-120b), it offers adjustable reasoning depth and full chain-of-thought visibility for better interpretability. ... -
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pflexible
A python tool for data analysis of FLEXPART transport modeling.
This software is being created to work with FLEXPART and other atmospheric transport model ouput. FLEXPART is a Lagrangian particle dispersion model written by Andreas Stohl. It is in active development at NILU and by Sabine Eckhardt, John Burkhart and numerous other research groups worldwide. For more information on FLEXPART visit the homepage Contact A maillist has been set up for users at sourceforge. Please direct inquiries via the pflexible_maillist Direct inquiries may be sent to:: John F Burkhart, University of Oslo [john.burkhart](mailto://john.burkhart@geo.uio.no) Get the Code: BitBucket Clone the bitbucket repository: %hg clone https://bitbucket.org/jfburkhart/pflexible pflexible