A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
-
Updated
Sep 5, 2019 - Python
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021
Detectorch - detectron for PyTorch
RectLabel is an offline image annotation tool for object detection and segmentation.
Code for ICCV2019 paper "InstaBoost: Boosting Instance Segmentation Via Probability Map Guided Copy-Pasting"
[ECCV 2020] Boundary-preserving Mask R-CNN
A PyTorch Detectron codebase for domain adaptation of object detectors.
7th place solution for the 2018 Data Science Bowl with a score of 0.591
Chainer Implementation of Mask R-CNN. (Training code to reproduce the original result is available.)
Domain Adaptive Faster R-CNN in Detectron
Implements Adversarial Examples for Semantic Segmentation and Object Detection, using PyTorch and Detectron2
Real-time Detectron using webcam.
Epic Kitchens Object Detector and Feature Extractor using Faster-RCNN with Detectron2
Software to visualize detectron training stats
Detectron with VoVNet(CVPRW'19) backbone networks
Detectron with VoVNet : select the vovnet branch
Detectron is Facebook AI Research’s (FAIR) 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. Detectron model is meant to advance object detection by offering speedy training and addressing the issues companies face when ma…
The Jakarnotator is an annotation tool to create your own database for instance segmentation problem.
Object detection
AI Breast cancer detection using InBreast, CBIS-DDSM, MIAS mammography image datasets
Add a description, image, and links to the detectron topic page so that developers can more easily learn about it.
To associate your repository with the detectron topic, visit your repo's landing page and select "manage topics."