37 Repositories
Python coco Libraries
[CVPR 2022] Official Pytorch code for OW-DETR: Open-world Detection Transformer
OW-DETR: Open-world Detection Transformer (CVPR 2022) [Paper] Akshita Gupta*, Sanath Narayan*, K J Joseph, Salman Khan, Fahad Shahbaz Khan, Mubarak Sh
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch
Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin
COCO Style Dataset Generator GUI
A simple GUI-based COCO-style JSON Polygon masks' annotation tool to facilitate quick and efficient crowd-sourced generation of annotation masks and bounding boxes. Optionally, one could choose to use a pretrained Mask RCNN model to come up with initial segmentations.
Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation
FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove
This repo is about implementing different approaches of pose estimation and also is a sub-task of the smart hospital bed project :smile:
Pose-Estimation This repo is a sub-task of the smart hospital bed project which is about implementing the task of pose estimation 😄 Many thanks to th
UDP++ (ECCVW 2020 Oral), (Winner of COCO 2020 Keypoint Challenge).
UDP-Pose This is the pytorch implementation for UDP++, which won the Fisrt place in COCO Keypoint Challenge at ECCV 2020 Workshop. Top-Down Results on
A python package to perform same transformation to coco-annotation as performed on the image.
coco-transform-util A python package to perform same transformation to coco-annotation as performed on the image. Installation Way 1 $ git clone https
Streamlit tool to explore coco datasets
What is this This tool given a COCO annotations file and COCO predictions file will let you explore your dataset, visualize results and calculate impo
SeMask: Semantically Masked Transformers for Semantic Segmentation.
SeMask: Semantically Masked Transformers Jitesh Jain, Anukriti Singh, Nikita Orlov, Zilong Huang, Jiachen Li, Steven Walton, Humphrey Shi This repo co
Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation.
PersonLab This is a Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation. The model predicts heatmaps and vari
2D Human Pose estimation using transformers. Implementation in Pytorch
PE-former: Pose Estimation Transformer Vision transformer architectures perform very well for image classification tasks. Efforts to solve more challe
Python library for computer vision labeling tasks. The core functionality is to translate bounding box annotations between different formats-for example, from coco to yolo.
PyLabel pip install pylabel PyLabel is a Python package to help you prepare image datasets for computer vision models including PyTorch and YOLOv5. I
[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
COCO-LM This repository contains the scripts for fine-tuning COCO-LM pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: COCO-LM: Correcting an
The official homepage of the (outdated) COCO-Stuff 10K dataset.
COCO-Stuff 10K dataset v1.1 (outdated) Holger Caesar, Jasper Uijlings, Vittorio Ferrari Overview Welcome to official homepage of the COCO-Stuff [1] da
[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
VirTex: Learning Visual Representations from Textual Annotations Karan Desai and Justin Johnson University of Michigan CVPR 2021 arxiv.org/abs/2006.06
The official homepage of the COCO-Stuff dataset.
The COCO-Stuff dataset Holger Caesar, Jasper Uijlings, Vittorio Ferrari Welcome to official homepage of the COCO-Stuff [1] dataset. COCO-Stuff augment
Hooks for VCOCO
Verbs in COCO (V-COCO) Dataset This repository hosts the Verbs in COCO (V-COCO) dataset and associated code to evaluate models for the Visual Semantic
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q
Txt2Xml tool will help you convert from txt COCO format to VOC xml format in Object Detection Problem.
TXT 2 XML All codes assume running from root directory. Please update the sys path at the beginning of the codes before running. Over View Txt2Xml too
Json2Xml tool will help you convert from json COCO format to VOC xml format in Object Detection Problem.
JSON 2 XML All codes assume running from root directory. Please update the sys path at the beginning of the codes before running. Over View Json2Xml t
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Simple Baselines for Human Pose Estimation and Tracking
Simple Baselines for Human Pose Estimation and Tracking News Our new work High-Resolution Representations for Labeling Pixels and Regions is available
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC
DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
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 orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai
[ICCV '21] In this repository you find the code to our paper Keypoint Communities
Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,
A set of tools for converting a darknet dataset to COCO format working with YOLOX
darknet格式数据→COCO darknet训练数据目录结构(详情参见dataset/darknet): darknet ├── class.names ├── gen_config.data ├── gen_train.txt ├── gen_valid.txt └── images
Visual Question Answering in Pytorch
Visual Question Answering in pytorch /!\ New version of pytorch for VQA available here: https://github.com/Cadene/block.bootstrap.pytorch This repo wa
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset, and represents Ultralytics open-source research int
Code for "Learning Canonical Representations for Scene Graph to Image Generation", Herzig & Bar et al., ECCV2020
Learning Canonical Representations for Scene Graph to Image Generation (ECCV 2020) Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, A
一个目标检测的通用框架(不需要cuda编译),支持Yolo全系列(v2~v5)、EfficientDet、RetinaNet、Cascade-RCNN等SOTA网络。
一个目标检测的通用框架(不需要cuda编译),支持Yolo全系列(v2~v5)、EfficientDet、RetinaNet、Cascade-RCNN等SOTA网络。
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)
ASGNet The code is for the paper "Adaptive Prototype Learning and Allocation for Few-Shot Segmentation" (accepted to CVPR 2021) [arxiv] Overview data/
OpenMMLab Pose Estimation Toolbox and Benchmark.
Introduction English | 简体中文 MMPose is an open-source toolbox for pose estimation based on PyTorch. It is a part of the OpenMMLab project. The master b
CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent performances in several models such as Faster R-CNN, YOLOv4, RetinaNet and . There is a maximum AP improvement of 1.9% and an average AP of 0.8% improvement on MS COCO dataset, compared to traditional evaluation-feedback modules. Here we just use as an example to illustrate the code.
CDIoU-CDIoUloss CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent p
Two-stage CenterNet
Probabilistic two-stage detection Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network. Probabilistic two-st
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a
Object detection on multiple datasets with an automatically learned unified label space.
Simple multi-dataset detection An object detector trained on multiple large-scale datasets with a unified label space; Winning solution of E
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
Deep High-Resolution Representation Learning for Human Pose Estimation (CVPR 2019) News [2020/07/05] A very nice blog from Towards Data Science introd