Stars
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
β‘ A Fast, Extensible Progress Bar for Python and CLI
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Code for the paper "Language Models are Unsupervised Multitask Learners"
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Image augmentation for machine learning experiments.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
Depth-Aware Video Frame Interpolation (CVPR 2019)
Setup and customize deep learning environment in seconds.
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
π Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
Keras implementation of RetinaNet object detection.
PyTorch implementation of Super SloMo by Jiang et al.
A library for training and deploying machine learning models on Amazon SageMaker
NVIDIA DeepStream SDK 8.0 / 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
Turn repositories into Jupyter-enabled Docker images
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
PyTorch extensions for fast R&D prototyping and Kaggle farming
gradslam is an open source differentiable dense SLAM library for PyTorch
π The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!
A light and fast one class detection framework for edge devices. We provide face detector, head detector, pedestrian detector, vehicle detector......