https://github.com/mxagar/ocr_guide
This repository contains a guide and example code on Optical Character Recognition (OCR).
https://github.com/mxagar/ocr_guide
easyocr image-processing ocr optical-character-recognition tesseract-ocr
Last synced: 10 months ago
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This repository contains a guide and example code on Optical Character Recognition (OCR).
- Host: GitHub
- URL: https://github.com/mxagar/ocr_guide
- Owner: mxagar
- Created: 2023-05-03T10:18:39.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-17T11:13:51.000Z (about 3 years ago)
- Last Synced: 2025-04-09T20:47:43.852Z (about 1 year ago)
- Topics: easyocr, image-processing, ocr, optical-character-recognition, tesseract-ocr
- Language: Jupyter Notebook
- Homepage:
- Size: 45 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Guide on Optical Character Recognition (OCR)
This repository contains a guide and example code on Optical Character Recognition (OCR).
I compiled this material after trying several tutorials and courses; I list the most relevant ones here:
- [Udemy: Optical Character Recognition (OCR) in Python](https://www.udemy.com/course/ocr-optical-character-recognition-in-python/)
- [PyImageSearch: Tutorials on OCR](https://pyimagesearch.com/)
The repository is organized in theme-related folders and each of them contains (1) a guide in Markdown which explains everything (including setup & Co.) and (2) example code.
- [`01_Tesseract`](./01_Tesseract): main folder with all the necessary basics for OCR with Tesseract.
- Tesseract: installation, usage
- Image processing for OCR
- EAST (detection) + OpenCV (image processing) + Tesseract (recognition) for OCR in natural scenarios
- OCR in videos: modularization of all learned functions into a video application
- [`02_EasyOCR`](./02_EasyOCR): package which detects very easily text in natural scenes.
- [`03_Keras_CNN`](./03_Keras_CNN): training of a Keras-CNN model to detect handwritten digits.
- [`04_Projects`](./04_Projects):
- Project 1: specific terms are searched and highlighted in book images.
- Project 2: processing (alignment, thresholding, etc.) of a receipt to apply OCR.
- Project 3: license plate detection.
The folder `01` is probably the most important, since the other introduce additional packages and extra examples.
If you are interested in other related guides:
- A compilation of Object Detection and Segmentation Examples: [detection_segmentation_pytorch](https://github.com/mxagar/detection_segmentation_pytorch)
- My notes on PyImageSearch tutorials: [pyimagesearch_tutorials](https://github.com/mxagar/pyimagesearch_tutorials)
- My notes on the Udacity Deep Learning Nanodegree: [deep_learning_udacity](https://github.com/mxagar/deep_learning_udacity)
- My notes on the Udacity Computer Vision Nanodepree: [computer_vision_udacity](https://github.com/mxagar/computer_vision_udacity)
Mikel Sagardia, 2023.
No guarantees.