#javascript #annotate_images #annotation_tool #audio #classification #computer_vision #dataset #deep_learning #desktop #entity_recognition #image_labeling_tool #image_segmentation #imagenet #named_entity_recognition #semantic_segmentation #text_annotation #text_labeling #udt

https://github.com/UniversalDataTool/universal-data-tool

#python #ade20k #image_classification #imagenet #mask_rcnn #mscoco #object_detection #semantic_segmentation #swin_transformer

https://github.com/microsoft/Swin-Transformer

#python #pytorch #semantic_segmentation #pspnet #deeplabv3

https://github.com/open-mmlab/mmsegmentation

#python #transformer #semantic_segmentation #cityscapes #ade20k

https://github.com/NVlabs/SegFormer

#python #autonomous_driving #human_segmentation #image_matting #image_segmentation #interactive_segmentation #lane_detection #panoptic_segmentation #semantic_segmentation #transformer #video_segmentation

https://github.com/PaddlePaddle/PaddleSeg

#typescript #annotation #annotation_tool #annotations #boundingbox #computer_vision #computer_vision_annotation #dataset #deep_learning #image_annotation #image_classification #image_labeling #image_labelling_tool #imagenet #labeling #labeling_tool #semantic_segmentation #tensorflow #video_annotation

https://github.com/openvinotoolkit/cvat

#jupyter_notebook #ade20k #cityscapes #coco #image_segmentation #instance_segmentation #oneformer #panoptic_segmentation #semantic_segmentation #transformer #universal_segmentation

https://github.com/SHI-Labs/OneFormer

#jupyter_notebook #computer_vision #deep_learning #image_classification #imagenet #neural_network #object_detection #pretrained_models #pretrained_weights #pytorch #semantic_segmentation #transfer_learning

https://github.com/Deci-AI/super-gradients

#python #deeplab_v3_plus #deeplabv3 #fpn #hacktoberfest #image_processing #image_segmentation #imagenet #linknet #models #pretrained_backbones #pretrained_models #pretrained_weights #pspnet #pytorch #segmentation #segmentation_models #semantic_segmentation #unet #unet_pytorch #unetplusplus

https://github.com/qubvel/segmentation_models.pytorch

#python #3d_perception #camera #lidar #object_detection #pytorch #semantic_segmentation #sensor_fusion

https://github.com/mit-han-lab/bevfusion

#javascript #annotation #annotation_tool #annotations #boundingbox #computer_vision #data_labeling #dataset #datasets #deep_learning #image_annotation #image_classification #image_labeling #image_labelling_tool #label_studio #labeling #labeling_tool #mlops #semantic_segmentation #text_annotation #yolo

Label Studio is a free, open-source tool that helps you label different types of data like images, audio, text, videos, and more. It has a simple and user-friendly interface that makes it easy to prepare or improve your data for machine learning models. You can customize it to fit your needs and export labeled data in various formats. It supports multi-user labeling, multiple projects, and integration with machine learning models for pre-labeling and active learning. You can install it locally using Docker, pip, or other methods, or deploy it in cloud services like Heroku or Google Cloud Platform. This tool streamlines your data labeling process and helps you create more accurate ML models.

https://github.com/HumanSignal/label-studio

#python #deeplabv3 #image_segmentation #medical_image_segmentation #pspnet #pytorch #realtime_segmentation #retinal_vessel_segmentation #semantic_segmentation #swin_transformer #transformer #vessel_segmentation

MMSegmentation is an open-source semantic segmentation toolbox based on PyTorch, part of the OpenMMLab project. It offers a unified benchmark for various semantic segmentation methods, a modular design allowing easy customization, and support for multiple popular segmentation frameworks like PSPNet and DeepLabV3+. The toolbox is highly efficient and provides detailed tutorials, advanced guides, and support for numerous datasets and backbones. This makes it a powerful tool for researchers and developers to implement and develop new semantic segmentation methods efficiently. By using MMSegmentation, you can leverage its flexibility, extensive features, and community support to enhance your projects in image segmentation tasks.

https://github.com/open-mmlab/mmsegmentation