A unofficial pytorch implementation of PAN(PSENet2): Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

Overview

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

Requirements

  • pytorch 1.1+
  • torchvision 0.3+
  • pyclipper
  • opencv3
  • gcc 4.9+

Download

PAN_resnet18_FPEM_FFM and PAN_resnet18_FPEM_FFM on icdar2015:

the updated model(resnet18:78.8,shufflenetv2: 72.4,lr:le-3) is not the best model

google drive

Data Preparation

train: prepare a text in the following format, use '\t' as a separator

/path/to/img.jpg path/to/label.txt
...

val: use a folder

img/ store img
gt/ store gt file

Train

  1. config the train_data_path,val_data_pathin config.json
  2. use following script to run
python3 train.py

Test

eval.py is used to test model on test dataset

  1. config model_path, img_path, gt_path, save_path in eval.py
  2. use following script to test
python3 eval.py

Predict

predict.py is used to inference on single image

  1. config model_path, img_path, in predict.py
  2. use following script to predict
python3 predict.py

The project is still under development.

Performance

ICDAR 2015

only train on ICDAR2015 dataset

Method image size (short size) learning rate Precision (%) Recall (%) F-measure (%) FPS
paper(resnet18) 736 x x x 80.4 26.1
my (ShuffleNetV2+FPEM_FFM+pse扩张) 736 1e-3 81.72 66.73 73.47 24.71 (P100)
my (resnet18+FPEM_FFM+pse扩张) 736 1e-3 84.93 74.09 79.14 21.31 (P100)
my (resnet50+FPEM_FFM+pse扩张) 736 1e-3 84.23 76.12 79.96 14.22 (P100)
my (ShuffleNetV2+FPEM_FFM+pse扩张) 736 1e-4 75.14 57.34 65.04 24.71 (P100)
my (resnet18+FPEM_FFM+pse扩张) 736 1e-4 83.89 69.23 75.86 21.31 (P100)
my (resnet50+FPEM_FFM+pse扩张) 736 1e-4 85.29 75.1 79.87 14.22 (P100)
my (resnet18+FPN+pse扩张) 736 1e-3 76.50 74.70 75.59 14.47 (P100)
my (resnet50+FPN+pse扩张) 736 1e-3 71.82 75.73 73.72 10.67 (P100)
my (resnet18+FPN+pse扩张) 736 1e-4 74.19 72.34 73.25 14.47 (P100)
my (resnet50+FPN+pse扩张) 736 1e-4 78.96 76.27 77.59 10.67 (P100)

examples

todo

  • MobileNet backbone

  • ShuffleNet backbone

reference

  1. https://arxiv.org/pdf/1908.05900.pdf
  2. https://github.com/WenmuZhou/PSENet.pytorch

If this repository helps you,please star it. Thanks.

Owner
zhoujun
深度学习工程师,最近准备做端侧
zhoujun
Official implementation of "StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation" (SIGGRAPH 2021)

StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation This repository contains the official PyTorch implementation of the following

Wonjong Jang 270 Dec 30, 2022
a reimplementation of Holistically-Nested Edge Detection in PyTorch

pytorch-hed This is a personal reimplementation of Holistically-Nested Edge Detection [1] using PyTorch. Should you be making use of this work, please

Simon Niklaus 375 Dec 06, 2022
No-reference Image Quality Assessment(NIQA) Algorithms (BRISQUE, NIQE, PIQE, RankIQA, MetaIQA)

No-Reference Image Quality Assessment Algorithms No-reference Image Quality Assessment(NIQA) is a task of evaluating an image without a reference imag

Dae-Young Song 26 Jan 04, 2023
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation

63 Nov 18, 2022
The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"

MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi

NeurAI 12 Nov 02, 2022
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

OFA Sys 1.4k Jan 08, 2023
Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions

Aquarius Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions NOTE: We are currently going through the open-source process requir

Zhiyuan YAO 0 Jun 02, 2022
Personalized Federated Learning using Pytorch (pFedMe)

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

Charlie Dinh 226 Dec 30, 2022
PPO Lagrangian in JAX

PPO Lagrangian in JAX This repository implements PPO in JAX. Implementation is tested on the safety-gym benchmark. Usage Install dependencies using th

Karush Suri 2 Sep 14, 2022
The Instructed Glacier Model (IGM)

The Instructed Glacier Model (IGM) Overview The Instructed Glacier Model (IGM) simulates the ice dynamics, surface mass balance, and its coupling thro

27 Dec 16, 2022
Face Library is an open source package for accurate and real-time face detection and recognition

Face Library Face Library is an open source package for accurate and real-time face detection and recognition. The package is built over OpenCV and us

52 Nov 09, 2022
The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

Published by SpaceML • About SpaceML • Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with

SpaceML 92 Nov 30, 2022
The 2nd place solution of 2021 google landmark retrieval on kaggle.

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

229 Dec 13, 2022
Prometheus exporter for Cisco Unified Computing System (UCS) Manager

prometheus-ucs-exporter Overview Use metrics from the UCS API to export relevant metrics to Prometheus This repository is a fork of Drew Stinnett's or

Marshall Wace 6 Nov 07, 2022
A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.

ManhattanSLAM Authors: Raza Yunus, Yanyan Li and Federico Tombari ManhattanSLAM is a real-time SLAM library for RGB-D cameras that computes the camera

117 Dec 28, 2022
The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

1 Jan 27, 2022
Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd.

Head Detector Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd. The head_detection mod

Ramana Sundararaman 76 Dec 06, 2022
Iranian Cars Detection using Yolov5s, PyTorch

Iranian Cars Detection using Yolov5 Train 1- git clone https://github.com/ultralytics/yolov5 cd yolov5 pip install -r requirements.txt 2- Dataset ../

Nahid Ebrahimian 22 Dec 05, 2022
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et

Sean M. Hendryx 1 Jan 27, 2022
Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap

2 Oct 20, 2022