facebookresearch/Detectron
The Awesome Machine Learning list marks this entry as deprecated.
FAIR's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework.
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more.
FAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.
Free and open source face recognition with deep neural networks.
А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.
A PyTorch-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.
Machine learning from Apple. Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.
AutoML for Image, Text, Tabular, Time-Series, and MultiModal Data.
Fastest unstructured dataset management for TensorFlow/PyTorch. Stream & version-control data. Store even petabyte-scale data in a single numpy-like array on the cloud accessible on any machine. Visit activeloop.ai for more info.
Python
