#image-segmentation (19 Repositories)
Ranked open-source repositories tagged with #image-segmentation, scored by pull request acceptance likelihood and maintainer engagement velocity.
23.8%
10.5h
19 repositories tagged #image-segmentation
petercorke/machinevision-toolbox-python
Machine vision toolbox for Python
feyninc/nobg
a library for background removal models
NVIDIA-ISAAC-ROS/isaac_ros_image_segmentation
NVIDIA-accelerated, deep learned semantic image segmentation
open-edge-platform/geti
Build computer vision models in a fraction of the time and with less data.
jolibrain/deepdetect
Deep Learning Server and CLI for Torch and TensorRT
MuscleMap/MuscleMap
MuscleMap: An Open-Source, Community-Supported Consortium for Whole-Body Quantitative MRI of Muscle
nipreps/smriprep
Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools)
ANTsX/ANTs
Advanced Normalization Tools (ANTs)
hukenovs/easyportrait
EasyPortrait - Face Parsing and Portrait Segmentation Dataset
PaddlePaddle/PaddleRS
Awesome Remote Sensing Toolkit based on PaddlePaddle.
ZwwWayne/K-Net
[NeurIPS2021] Code Release of K-Net: Towards Unified Image Segmentation
xuebinqin/U-2-Net
The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
SkalskiP/top-cvpr-2023-papers
This repository is a curated collection of the most exciting and influential CVPR 2023 papers. 🔥 [Paper + Code]
PaddlePaddle/PaddleSeg
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
open-mmlab/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
qubvel/segmentation_models
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
ailia-ai/ailia-models
The collection of pre-trained, state-of-the-art AI models for ailia SDK
roboflow/notebooks
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.