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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
OpenMMLab Detection Toolbox and Benchmark
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source …
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Image augmentation for machine learning experiments.
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
End-to-End Object Detection with Transformers
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Statsmodels: statistical modeling and econometrics in Python
Geometric Computer Vision Library for Spatial AI
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
A PyTorch implementation of the Transformer model in "Attention is All You Need".
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
A PyTorch implementation of EfficientNet
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
A faster pytorch implementation of faster r-cnn
A unified framework for machine learning with time series