The TrOCR (Transformer-based Optical Character Recognition) model is one of the best performing OCR models. In our previous article we analyzed their performance on single lines of printed and handwritten text. However, like any other deep learning model, they have their limitations. TrOCR doesn’t perform well with curved text out of the box. This article […]
Tag: ocr
Qt uses VCPKG, CMake, OpenCV and Tesseract to implement Chinese and English OCR
Article directory 1. Development platform 2. Download files 2.1 Download and install the OpenCV library 2.2 Download and install the Tesseract-OCR library 2.3 Download the trained language package 3. CMakeLists.txt content 4. Main.cpp 4.1 Mixed Chinese and English OCR 5. Set up CMake + vcpkg in Qt Creator 5.1 Modify in the initialization configuration file […]
Pitfalls and solutions encountered when using GPU to train paddleocr model on new ubuntu
Directory 1. My ubuntu version! [Insert image description here](https://img-blog.csdnimg.cn/297945917309494ab03b50764e6fb775.png) 2. First pull the paddleocr source code 3. Download the model 4. Preparation before training 1. Create a file in the source code folder to put your own things 2. Prepare data 2.1 Data annotation 2.2 Data division 3. Rewrite the yml configuration file 4.Install anaconda […]
Front-end (25) – Detailed steps and sample code for front-end implementation of OCR image and text recognition
Blogger: The kitten is here The core of the article: Detailed steps and sample code for front-end implementation of OCR image and text recognition Article directory Introduction to OCR technology Step 1: Determine which OCR API to use Step 2: Create the front-end interface Step 3: Add image upload function Step 4: Send identification request […]
Optical character recognition OCR using support vector machine SVM
letters<-read.csv(“letterdata.csv”) # Load data file str(letters) ‘data.frame’: 20000 obs. of 17 variables: $ letter: Factor w/ 26 levels “A”,”B”,”C”,”D”,..: 20 9 4 14 7 19 2 1 10 13 … $ xbox : int 2 5 4 7 2 4 4 1 2 11 … $ ybox : int 8 12 11 11 1 11 […]
PPocr-openvino implementation (C++)
Foreword Tasks during the trial period The entry interview was about deep learning, but I never touched deep learning again after I came in. . . was arranged into traditional images and some traditional algorithms. . It is still a sweat enterprise, requiring unpaid overtime (no probationary period subsidies), and being contacted at any time […]
OpenCV implements OCR (optical character recognition)
Introduction: With the continuous development of computer vision technology, OCR (optical character recognition) technology has become more and more mature. OCR technology can identify text information in images and convert it into editable text format, providing convenience for various application scenarios. This article will introduce how to use the OpenCV library to implement camera OCR. […]
9 steps to build PaddleOCR image text recognition WebAPI under Windows
Table of Contents This article relies on existing resources to build a WebAPI for image text recognition on the Windows platform, so that other projects can Base64 encode the image and pass it to the API through the Post method, so that the text information in the image can be obtained. Step 1: Install the […]
PDF file text copy permission is encrypted, but all text in the PDF is required. Solution: Python + FineReaderOCR
This time I really found a powerful OCR to help me solve the problem 1. The usual situation If you need to extract text from PDF, the first software that comes to mind is Format Factory. Just use its “PDF→Text” function. The advantage is that the software runs quickly and the processing time is short. […]
Python Mnist handwritten multi-digit recognition based on paddleocr2.7.0
Directory of series articles Chapter 1 Python Mnist handwritten multi-digit recognition based on paddleocr2.7.0 Article directory Table of Contents of Series Articles Preface 1. Install PaddleOCR 2. Configuration environment 3. Create a handwritten digit data set 1. Splicing data sets Splicing the data set from 0-99: 2.Data display 4. Training model 1. Download the pre-trained […]