Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)

Overview

Detecting Text in Natural Image with Connectionist Text Proposal Network

The codes are used for implementing CTPN for scene text detection, described in:

Z. Tian, W. Huang, T. He, P. He and Y. Qiao: Detecting Text in Natural Image with
Connectionist Text Proposal Network, ECCV, 2016.

Online demo is available at: textdet.com

These demo codes (with our trained model) are for text-line detection (without side-refinement part).

Required hardware

You need a GPU. If you use CUDNN, about 1.5GB free memory is required. If you don't use CUDNN, you will need about 5GB free memory, and the testing time will slightly increase. Therefore, we strongly recommend to use CUDNN.

It's also possible to run the program on CPU only, but it's extremely slow due to the non-optimal CPU implementation.

Required softwares

Python2.7, cython and all what Caffe depends on.

How to run this code

  1. Clone this repository with git clone https://github.com/tianzhi0549/CTPN.git. It will checkout the codes of CTPN and Caffe we ship.

  2. Install the caffe we ship with codes bellow.

    • Install caffe's dependencies. You can follow this tutorial. Note: we need Python support. The CUDA version we need is 7.0.

    • Enter the directory caffe.

    • Run cp Makefile.config.example Makefile.config.

    • Open Makefile.config and set WITH_PYTHON_LAYER := 1. If you want to use CUDNN, please also set CUDNN := 1. Uncomment the CPU_ONLY :=1 if you want to compile it without GPU.

      Note: To use CUDNN, you need to download CUDNN from NVIDIA's official website, and install it in advance. The CUDNN version we use is 3.0.

    • Run make -j && make pycaffe.

  3. After Caffe is set up, you need to download a trained model (about 78M) from Google Drive or our website, and then populate it into directory models. The model's name should be ctpn_trained_model.caffemodel.

  4. Now, be sure you are in the root directory of the codes. Run make to compile some cython files.

  5. Run python tools/demo.py for a demo. Or python tools/demo.py --no-gpu to run it under CPU mode.

How to use other Caffe

If you may want to use other Caffe instead of the one we ship for some reasons, you need to migrate the following layers into the Caffe.

  • Reverse
  • Transpose
  • Lstm

License

The codes are released under the MIT License.

Owner
Tian Zhi
PhD Candidate.
Tian Zhi
Natural language detection

Detect the language of text. What’s so cool about franc? franc can support more languages(†) than any other library franc is packaged with support for

Titus 3.8k Jan 02, 2023
Responsive Doc. scanner using U^2-Net, Textcleaner and Tesseract

Responsive Doc. scanner using U^2-Net, Textcleaner and Tesseract Toolset U^2-Net is used for background removal Textcleaner is used for image cleaning

3 Jul 13, 2022
Image Detector and Convertor App created using python's Pillow, OpenCV, cvlib, numpy and streamlit packages.

Image Detector and Convertor App created using python's Pillow, OpenCV, cvlib, numpy and streamlit packages.

Siva Prakash 11 Jan 02, 2022
Optical character recognition for Japanese text, with the main focus being Japanese manga

Manga OCR Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with Tran

Maciej Budyś 327 Jan 01, 2023
STEFANN: Scene Text Editor using Font Adaptive Neural Network

STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

Prasun Roy 208 Dec 11, 2022
Computer vision applications project (Flask and OpenCV)

Computer Vision Applications Project This project is at it's initial phase. This is all about the implementation of different computer vision techniqu

Suryam Thapa 1 Jan 26, 2022
OCR, Scene-Text-Understanding, Text Recognition

Scene-Text-Understanding Survey [2015-PAMI] Text Detection and Recognition in Imagery: A Survey paper [2014-Front.Comput.Sci] Scene Text Detection and

Alan Tang 354 Dec 12, 2022
The code for CVPR2022 paper "Likert Scoring with Grade Decoupling for Long-term Action Assessment".

Likert Scoring with Grade Decoupling for Long-term Action Assessment This is the code for CVPR2022 paper "Likert Scoring with Grade Decoupling for Lon

10 Oct 21, 2022
MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition

MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition Python 2.7 Python 3.6 MORAN is a network with rectification mechanism for

Canjie Luo 595 Dec 27, 2022
Using computer vision method to recognize and calcutate the features of the architecture.

building-feature-recognition In this repository, we accomplished building feature recognition using traditional/dl-assisted computer vision method. Th

4 Aug 11, 2022
question‘s area recognition using image processing and regular expression

======================================== Paper-Question-recognition ======================================== question‘s area recognition using image p

Yuta Mizuki 7 Dec 27, 2021
Read Japanese manga inside browser with selectable text.

mokuro Read Japanese manga with selectable text inside a browser. See demo: https://kha-white.github.io/manga-demo mokuro_demo.mp4 Demo contains excer

Maciej Budyś 170 Dec 27, 2022
Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector

CRAFT: Character-Region Awareness For Text detection Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector | Paper |

188 Dec 28, 2022
aardio的opencv库

opencv_aardio dll库下载地址:https://github.com/xuncv/opencv-plugin/releases import cv2 img = cv2.imread("./images/Lena.jpg",1) img = cv2.medianBlur(img,5)

71 Dec 31, 2022
Code for the paper: Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution

Fusformer Code for the paper: "Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution" Plateform Python 3.8.5 + Pytor

Jin-Fan Hu (胡锦帆) 11 Dec 12, 2022
Introduction to image processing, most used and popular functions of OpenCV

👀 OpenCV 101 Introduction to image processing, most used and popular functions of OpenCV go here.

Vusal Ismayilov 3 Jul 02, 2022
SceneCollisionNet This repo contains the code for "Object Rearrangement Using Learned Implicit Collision Functions", an ICRA 2021 paper. For more info

SceneCollisionNet This repo contains the code for "Object Rearrangement Using Learned Implicit Collision Functions", an ICRA 2021 paper. For more info

NVIDIA Research Projects 31 Nov 22, 2022
Multi-choice answer sheet correction system using computer vision with opencv & python.

Multi choice answer correction 🔴 5 answer sheet samples with a specific solution for detecting answers and sheet correction. 🔴 By running the soluti

Reza Firouzi 7 Mar 07, 2022
OCR, Object Detection, Number Plate, Real Time

README.md PrePareded anaconda env requirements.txt clova AI → deep text recognition → trained weights (ex, .pth) wpod-net weights (ex, .h5 , .json) ht

Kaven Lee 7 Dec 06, 2022
InverseRenderNet: Learning single image inverse rendering, CVPR 2019.

InverseRenderNet: Learning single image inverse rendering !! Check out our new work InverseRenderNet++ paper and code, which improves the inverse rend

Ye Yu 141 Dec 20, 2022