Search Results for "segmentation" - Page 6
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Showing 329 open source projects for "segmentation"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Mask2Former
Code release for "Masked-attention Mask Transformer
Mask2Former is a unified segmentation architecture that handles semantic, instance, and panoptic segmentation with one model and one training recipe. Its core idea is to cast segmentation as mask classification: a transformer decoder predicts a set of mask queries, each with an associated class score, eliminating the need for task-specific heads. A pixel decoder fuses multi-scale features and feeds masked attention in the transformer so each query focuses computation on its current spatial support. ... -
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Unet
Source code for unet-pytorch, which can train its own model
...Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. It is useful for developers and students who want a clear U-Net implementation for segmentation experiments, custom masks, and biomedical-style image analysis. -
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avio
Python version of ffplay with built-in AI
See the Files tab above for installation instructions -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
...The encoder processes only the visible patches, while a lightweight decoder reconstructs the full image—making pretraining computationally efficient. After pretraining, the encoder serves as a powerful backbone for downstream tasks like image classification, segmentation, and detection, achieving top performance with minimal fine-tuning. The repository provides pretrained models, fine-tuning scripts, evaluation protocols, and visualization tools for reconstruction quality and learned features. -
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Tensorflow Transformers
State of the art faster Transformer with Tensorflow 2.0
...These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Faster AutoReggressive Decoding, TFlite support, creating TFRecords is simple. Auto-Batching tf.data.dataset or tf.ragged tensors. Everything is dictionary (inputs and outputs) Multiple mask modes like causal, user-defined, prefix. tensorflow-text tokenizer support. ... -
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MeshCNN in PyTorch
Convolutional Neural Network for 3D meshes in PyTorch
...The framework introduces specialized layers such as edge-based convolution, mesh pooling, and mesh unpooling operations that enable hierarchical feature learning on mesh surfaces. These capabilities make the architecture well suited for tasks such as 3D object classification, segmentation, and geometric analysis. The project provides training pipelines, dataset preparation tools, and visualization utilities to support experiments with mesh-based neural networks. -
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Deep Learning course
Slides and Jupyter notebooks for the Deep Learning lectures
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris. This course is being taught at as part of Master Year 2 Data Science IP-Paris. Note: press "P" to display the presenter's notes that include some comments and additional references. This lecture is built and maintained by Olivier Grisel and Charles Ollion. -
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MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation
MaskFormer is a unified framework for image segmentation developed by Facebook Research, designed to bridge the gap between semantic, instance, and panoptic segmentation within a single architecture. Unlike traditional segmentation pipelines that treat these tasks separately, MaskFormer reformulates segmentation as a mask classification problem, enabling a consistent and efficient approach across multiple segmentation domains. -
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Detectron2
Next-generation platform for object detection and segmentation
...It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open source more research projects in this way. It trains much faster. Models can be exported to TorchScript format or Caffe2 format for deployment. With a new, more modular design, Detectron2 is flexible and extensible, and able to provide fast training on single or multiple GPU servers. ... -
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Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
...Later chapters explore classic neural network structures such as CNNs, RNNs, and GANs, as well as key applications in computer vision like object detection and image segmentation. The resource also delves into optimization methods, including transfer learning, network architecture design, hyperparameter tuning, model compression, and acceleration techniques. -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
...Unlike most existing methods that perform video matting frame-by-frame as independent images, our method uses a recurrent architecture to exploit temporal information in videos and achieves significant improvements in temporal coherence and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. Our method does not require any auxiliary inputs such as a trimap or a pre-captured background image, so it can be widely applied to existing human matting applications. RVM is specifically designed for robust human video matting. -
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VRN
Code for "Large Pose 3D Face Reconstruction
The VRN (Volumetric Regression Network) repository implements the “Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression” method. Instead of explicitly fitting a 3D model via landmark estimation and deformation, VRN treats the reconstruction task as volumetric segmentation: it learns a CNN to regress a 3D volume aligned to the input image, and then extracts a mesh via isosurface from that volume. The network is unguided (no 2D landmarks as intermediate). The mesh surfaces can be textured (in MATLAB branch) and colored. Docker container provided for easy CPU deployment. -
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MMMISA : a free, user-friendly tool for single/dual-modality DICOM file analysis MMMISA will be included as part of version 2 of DeepImageTranslator (https://sourceforge.net/projects/deepimagetranslator/) Citation: Ye RZ et al. DeepImageTranslator V2: analysis of multimodal medical images using semantic segmentation maps generated through deep learning.biorxiv.
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Mailtrain
Self-hosted newsletter app
...Whether you have a thousand or a million subscribers, Mailtrain can keep you on top of things by letting you add subscribers manually, through the API, or import from a CSV file. Built on Node.js (v7+) and MySQL (v5.5+ or MariaDB), Mailtrain comes with an excellent set of features, including a wide range of custom fields, list segmentation, template editors, automation and more. It also allows you to check click statistics of every link included in your campaign. -
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Semantic Segmentation in PyTorch
Semantic segmentation models, datasets & losses implemented in PyTorch
Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. -
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Nerfies
This is the code for Deformable Neural Radiance Fields
...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 imperfect captures by modeling camera poses, exposure variations, and background segmentation, producing stable geometry and appearance. A set of utilities manages dataset preparation, pose estimation, and checkpoints so researchers can reproduce results on their own footage. The work sits at the intersection of graphics and vision, showing how learned volumetric rendering can handle human motion without dense markers or studio rigs. -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
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TNN
Uniform deep learning inference framework for mobile
TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's... -
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Osclass_Fileuploadplugin
Here is my third contribution. I am glad to contribute to the Osclass
This plugin helps to upload any files from client to remote server so-called fileupload. An alternative to file attachement by email clients such as Gmail, Yahoo etc. Please visit https://walexconcepts.com/index.php?page=page&id=40 for demo. -
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Semantic Segmentation Editor
Web labeling tool for bitmap images and point clouds
A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js. -
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Slatwall Commerce
Slatwall Commerce is the eCommerce Platform you've always wanted
Slatwall is built from the ground up for maximum flexibility, because responding to new opportunities requires you to adapt quickly. We work with our clients to customize Slatwall and meet the needs of their growing eCommerce businesses or new eCommerce channels. If you're tired of solutions that only get you 80% of the way there, then Slatwall is the eCommerce platform you've been searching for! -
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Gluon CV Toolkit
Gluon CV Toolkit
...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework. -
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Synonyms
Chinese synonyms, chat robot, intelligent question and answer toolkit
Chinese Synonyms for natural language processing and understanding. Better Chinese synonyms, chatbot, intelligent question and answer toolkit. synonymsCan be used for many tasks in natural language understanding, text alignment, recommendation algorithms, similarity calculation, semantic shifting, keyword extraction, concept extraction, automatic summarization, search engines, etc. Print synonyms in a friendly way for easy debugging. "Synonyms Cilin" was compiled by Mei Jiaju and others in... -
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PaddlePaddle models
Pre-trained and Reproduced Deep Learning Models
Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification, target detection, image segmentation, text recognition, speech synthesis, etc. An end-to-end development kit that meets the needs of enterprises for low-cost development and rapid integration. The model library of Flying Paddle is an industrial-level model library tailored around the actual R&D process of domestic enterprises, serving enterprises in many fields such as energy, finance, industry, and agriculture.
