Annotate datasets with a semi-trained or fully trained YOLOv5 model

Overview

YOLOv5 Auto Annotator

Annotate datasets with a semi-trained or fully trained YOLOv5 model

Prerequisites

Ubuntu >=20.04
Python >=3.7

System dependencies

sudo apt install python3-dev python3-pip

Python dependencies

cycler==0.11.0
fonttools==4.29.0
kiwisolver==1.3.2
lxml==4.6.4
numpy==1.21.4
opencv-contrib-python==4.5.5.62
opencv-python==4.5.5.62
packaging==21.3
Pillow==9.0.0
pyparsing==3.0.7
python-dateutil==2.8.2
six==1.16.0
tqdm==4.62.3

Install with the following command -

pip3 install -r requirements.txt

Run the application

Execute annotate.py in the following format -

usage: annotate.py [-h] [--viewmode] [--imgdir IMGDIR] [--annodir ANNODIR] [--confThreshold CONFTHRESHOLD] [--nmsThreshold NMSTHRESHOLD] [--width WIDTH] [--height HEIGHT] [--onnx_path ONNX_PATH] [--labels_path LABELS_PATH]

optional arguments:
  -h, --help            show this help message and exit
  --viewmode            Toggle View Mode
  --imgdir IMGDIR       Directory of images
  --annodir ANNODIR     Directory of annotations
  --confThreshold CONFTHRESHOLD
                        Class confidence
  --nmsThreshold NMSTHRESHOLD
                        NMS threshold
  --width WIDTH         Width of network input
  --height HEIGHT       Height of network input
  --onnx_path ONNX_PATH
                        Path to onnx file
  --labels_path LABELS_PATH
                        Path to labels file

Example -

python3 annotate.py --imgdir /home/kn1ght/Documents/images --annodir annotations --onnx_path models/YOLOv5s/yolov5s.onnx --labels_path models/YOLOv5s/coco.names --viewmode
Owner
Akash James
AI Architect at iWizards | NVIDIA Jetson AI Ambassador | Intel Edge AI Certified | NVIDIA 5x Certified | NASA Space Apps 2x Winner | Speaker | Hackathons
Akash James
Optimizing Deeper Transformers on Small Datasets

DT-Fixup Optimizing Deeper Transformers on Small Datasets Paper published in ACL 2021: arXiv Detailed instructions to replicate our results in the pap

16 Nov 14, 2022
Graph Representation Learning via Graphical Mutual Information Maximization

GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20

93 Dec 29, 2022
For visualizing the dair-v2x-i dataset

3D Detection & Tracking Viewer The project is based on hailanyi/3D-Detection-Tracking-Viewer and is modified, you can find the original version of the

34 Dec 29, 2022
A Gura parser implementation for Python

Gura Python parser This repository contains the implementation of a Gura (compliant with version 1.0.0) format parser in Python. Installation pip inst

Gura Config Lang 19 Jan 25, 2022
Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images (ICCV 2021)

Table of Content Introduction Getting Started Datasets Installation Experiments Training & Testing Pretrained models Texture fine-tuning Demo Toward R

VinAI Research 42 Dec 05, 2022
Python Classes: Medical Insurance Project using Object Oriented Programming Concepts

Medical-Insurance-Project-OOP Python Classes: Medical Insurance Project using Object Oriented Programming Concepts Classes are an incredibly useful pr

Hugo B. 0 Feb 04, 2022
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.

NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine

419 Jan 03, 2023
A pytorch reprelication of the model-based reinforcement learning algorithm MBPO

Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo

Xingyu Lin 93 Jan 05, 2023
Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. Prerequisites Python 2.7

SK T-Brain 754 Dec 29, 2022
PyTorch implementation of Pay Attention to MLPs

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Jake Tae 34 Dec 13, 2022
An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and Machine Learning.

ALgorithmic_Trading_with_ML An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and

1 Mar 14, 2022
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"

[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas

PatatiPatata 28 Oct 18, 2022
This is a repo of basic Machine Learning!

Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource

Ekram Asif 53 Dec 31, 2022
PyTorch common framework to accelerate network implementation, training and validation

pytorch-framework PyTorch common framework to accelerate network implementation, training and validation. This framework is inspired by works from MML

Dongliang Cao 3 Dec 19, 2022
Codes for paper "Towards Diverse Paragraph Captioning for Untrimmed Videos". CVPR 2021

Towards Diverse Paragraph Captioning for Untrimmed Videos This repository contains PyTorch implementation of our paper Towards Diverse Paragraph Capti

Yuqing Song 61 Oct 11, 2022
A PyTorch Image-Classification With AlexNet And ResNet50.

PyTorch 图像分类 依赖库的下载与安装 在终端中执行 pip install -r -requirements.txt 完成项目依赖库的安装 使用方式 数据集的准备 STL10 数据集 下载:STL-10 Dataset 存储位置:将下载后的数据集中 train_X.bin,train_y.b

FYH 4 Feb 22, 2022
This repo contains implementation of different architectures for emotion recognition in conversations.

Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty

Deep Cognition and Language Research (DeCLaRe) Lab 1k Dec 30, 2022
Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia

3 Apr 12, 2022
Introduction to AI assignment 1 HCM University of Technology, term 211

Sokoban Bot Introduction to AI assignment 1 HCM University of Technology, term 211 Abstract This is basically a solver for Sokoban game using Breadth-

Quang Minh 4 Dec 12, 2022
A particular navigation route using satellite feed and can help in toll operations & traffic managemen

How about adding some info that can quanitfy the stress on a particular navigation route using satellite feed and can help in toll operations & traffic management The current analysis is on the satel

Ashish Pandey 1 Feb 14, 2022