R2CNN_Faster_RCNN_Tensorflow Abstract This is a tensorflow re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detecti

Object detection and instance segmentation toolkit based on PaddlePaddle.

An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q

IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It or

Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc

This is an oriented object detector based on tensorflow object detection API. Most of the code is not changed except for those related to the need of

Pedestron Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection. We provide a list of detec

BMaskR-CNN This code is developed on Detectron2 Boundary-preserving Mask R-CNN ECCV 2020 Tianheng Cheng, Xinggang Wang, Lichao Huang, Wenyu Liu Video

A Faster Pytorch Implementation of Faster R-CNN Write at the beginning [05/29/2020] This repo was initaited about two years ago, developed as the firs

Faster RCNN with PyTorch Note: I re-implemented faster rcnn in this project when I started learning PyTorch. Then I use PyTorch in all of my projects.

Face Detection Docker Solution Using Faster R-CNN Dockerface is a deep learning face detector. It deploys a trained Faster R-CNN network on Caffe thro

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at

MoroccoAI Data Challenge (Edition #001) This Reposotory is result of our work in the comepetiton organized by MoroccoAI in the context of the first Mo

TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.