This is the first released system towards complex meters` detection and recognition, which is implemented by computer vision techniques.

Overview

A three-stage detection and recognition pipeline of complex meters in wild

This is the first released system towards detection and recognition of complex meters in wild. The system can be divided into three moduels. Fisrtly, a yolo-based detector is applied to get pure meter region. Secondly, a spatial transformer module is eatablished to rectify the position of meter. Lastly, an end-to-end network is to read meter values, which is implemented by pointer/dail predcition and key number learning.

Visulization results

Left row is the original image, middle row is the process of meter rectification, right row is the result of meter value reading.

ToDo List

  • Release testing code
  • Release training code and dataset(after paper release)
  • existing three-stage models
  • A new end-to-end model for image distoration and meter value reading
  • A new branch for digital-meter recognition
  • Document for testing
  • Document for training(after paper release)
  • Demo script for single image
  • Demo script for video
  • Evaluation

Installation

Requirements:

  • Python3 (Python3.7 is recommended)
  • PyTorch >= 1.0
  • torchvision from master
  • numpy
  • skimage
  • OpenCV==3.0.x
  • CUDA >= 9.0 (10.0 is recommended)

Models

Download Trained model

Please put distro_net.pt into meter_distro/weight.
put textgraph_vgg_450.pth into model/meter_data.

Demo

You can run a demo script for a single image inference by two steps.

python get_meter_area.py. and the detected meter will be stored in scene_image_data/deteced_meter

python predict.py to get distored meter and final result.

Owner
Yan Shu
In HIT Researching in machine learning and computer vision
Yan Shu
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.

COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order

decile-team 244 Jan 09, 2023
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Zekarias Tilahun 24 Jun 21, 2022
Python3 Implementation of (Subspace Constrained) Mean Shift Algorithm in Euclidean and Directional Product Spaces

(Subspace Constrained) Mean Shift Algorithms in Euclidean and/or Directional Product Spaces This repository contains Python3 code for the mean shift a

Yikun Zhang 0 Oct 19, 2021
A treasure chest for visual recognition powered by PaddlePaddle

简体中文 | English PaddleClas 简介 飞桨图像识别套件PaddleClas是飞桨为工业界和学术界所准备的一个图像识别任务的工具集,助力使用者训练出更好的视觉模型和应用落地。 近期更新 2021.11.1 发布PP-ShiTu技术报告,新增饮料识别demo 2021.10.23 发

4.6k Dec 31, 2022
A tiny, pedagogical neural network library with a pytorch-like API.

candl A tiny, pedagogical implementation of a neural network library with a pytorch-like API. The primary use of this library is for education. Use th

Sri Pranav 3 May 23, 2022
This is a repository with the code for the ACL 2019 paper

The Story of Heads This is the official repo for the following papers: (ACL 2019) Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy

231 Nov 15, 2022
Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020. Scripts and outputs related to the paper Prediction of Adverse Biological Effects of

Knowledge Graphs at the Norwegian Institute for Water Research 1 Nov 01, 2021
An Intelligent Self-driving Truck System For Highway Transportation

Inceptio Intelligent Truck System An Intelligent Self-driving Truck System For Highway Transportation Note The code is still in development. OS requir

InceptioResearch 11 Jul 13, 2022
How to use TensorLayer

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

zhangrui 349 Dec 07, 2022
[ICCV2021] Learning to Track Objects from Unlabeled Videos

Unsupervised Single Object Tracking (USOT) 🌿 Learning to Track Objects from Unlabeled Videos Jilai Zheng, Chao Ma, Houwen Peng and Xiaokang Yang 2021

53 Dec 28, 2022
MonoScene: Monocular 3D Semantic Scene Completion

MonoScene: Monocular 3D Semantic Scene Completion MonoScene: Monocular 3D Semantic Scene Completion] [arXiv + supp] | [Project page] Anh-Quan Cao, Rao

298 Jan 08, 2023
Pyeventbus: a publish/subscribe event bus

pyeventbus pyeventbus is a publish/subscribe event bus for Python 2.7. simplifies the communication between python classes decouples event senders and

15 Apr 21, 2022
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches

Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa

Rishit Dagli 40 Jul 25, 2022
git《Tangent Space Backpropogation for 3D Transformation Groups》(CVPR 2021) GitHub:1]

LieTorch: Tangent Space Backpropagation Introduction The LieTorch library generalizes PyTorch to 3D transformation groups. Just as torch.Tensor is a m

Princeton Vision & Learning Lab 482 Jan 06, 2023
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control

FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control by Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann FIGARO: Generat

Dimitri 83 Jan 07, 2023
Benchmark VAE - Library for Variational Autoencoder benchmarking

Documentation pythae This library implements some of the most common (Variational) Autoencoder models. In particular it provides the possibility to pe

1.1k Jan 02, 2023
A PyTorch implementation of Implicit Q-Learning

IQL-PyTorch This repository houses a minimal PyTorch implementation of Implicit Q-Learning (IQL), an offline reinforcement learning algorithm, along w

Garrett Thomas 30 Dec 12, 2022
Deep learning image registration library for PyTorch

TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide

Bob de Vos 40 Dec 16, 2022
Bayesian Optimization using GPflow

Note: This package is for use with GPFlow 1. For Bayesian optimization using GPFlow 2 please see Trieste, a joint effort with Secondmind. GPflowOpt GP

GPflow 257 Dec 26, 2022
Pairwise learning neural link prediction for ogb link prediction

Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t

Zhitao WANG 31 Oct 10, 2022