Hakjin Lee's repositories
mmdetection
OpenMMLab Detection Toolbox and Benchmark
Interactive-SAM-with-Gradio
Interactive SAM Demo with Gradio
PaddleDetection
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
ColossalAI
Making large AI models cheaper, faster and more accessible
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
e2cnn
E(2)-Equivariant CNNs Library for Pytorch
gradio
Create UIs for your machine learning model in Python in 3 minutes
lightning
Build and train PyTorch models and connect them to the ML lifecycle using Lightning App templates, without handling DIY infrastructure, cost management, scaling, and other headaches.
mim
MIM Installs OpenMMLab Packages
mmclassification
OpenMMLab Image Classification Toolbox and Benchmark
mmcv
OpenMMLab Computer Vision Foundation
mmediting
OpenMMLab Image and Video Editing Toolbox
mmengine
OpenMMLab Foundational Library for Training Deep Learning Models
mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
mmselfsup
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
mmtracking
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
oslo
OSLO: Open Source for Large-scale Optimization
prismatic-vlms
A flexible and efficient codebase for training visually-conditioned language models (VLMs)
python
Official Python client library for kubernetes
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
SegDrawer
Simple static web-based mask drawer, supporting semantic segmentation with Segment Anything Model (SAM).
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.