{"id":18339946,"url":"https://github.com/mxagar/ocr_guide","last_synced_at":"2025-08-30T06:44:02.446Z","repository":{"id":161019289,"uuid":"635724364","full_name":"mxagar/ocr_guide","owner":"mxagar","description":"This repository contains a guide and example code on Optical Character Recognition (OCR).","archived":false,"fork":false,"pushed_at":"2023-06-17T11:13:51.000Z","size":47217,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-09T20:47:43.852Z","etag":null,"topics":["easyocr","image-processing","ocr","optical-character-recognition","tesseract-ocr"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mxagar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-05-03T10:18:39.000Z","updated_at":"2024-06-13T03:00:17.000Z","dependencies_parsed_at":null,"dependency_job_id":"8b320931-9a53-4395-b3ba-9345bc26d4e3","html_url":"https://github.com/mxagar/ocr_guide","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mxagar/ocr_guide","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mxagar%2Focr_guide","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mxagar%2Focr_guide/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mxagar%2Focr_guide/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mxagar%2Focr_guide/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mxagar","download_url":"https://codeload.github.com/mxagar/ocr_guide/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mxagar%2Focr_guide/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272815815,"owners_count":24997661,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-30T02:00:09.474Z","response_time":77,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["easyocr","image-processing","ocr","optical-character-recognition","tesseract-ocr"],"created_at":"2024-11-05T20:19:56.906Z","updated_at":"2025-08-30T06:44:02.410Z","avatar_url":"https://github.com/mxagar.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Guide on Optical Character Recognition (OCR)\n\nThis repository contains a guide and example code on Optical Character Recognition (OCR).\n\nI compiled this material after trying several tutorials and courses; I list the most relevant ones here:\n\n- [Udemy: Optical Character Recognition (OCR) in Python](https://www.udemy.com/course/ocr-optical-character-recognition-in-python/)\n- [PyImageSearch: Tutorials on OCR](https://pyimagesearch.com/)\n\nThe repository is organized in theme-related folders and each of them contains (1) a guide in Markdown which explains everything (including setup \u0026 Co.) and (2) example code.\n\n- [`01_Tesseract`](./01_Tesseract): main folder with all the necessary basics for OCR with Tesseract.\n  - Tesseract: installation, usage\n  - Image processing for OCR\n  - EAST (detection) + OpenCV (image processing) + Tesseract (recognition) for OCR in natural scenarios\n  - OCR in videos: modularization of all learned functions into a video application\n- [`02_EasyOCR`](./02_EasyOCR): package which detects very easily text in natural scenes.\n- [`03_Keras_CNN`](./03_Keras_CNN): training of a Keras-CNN model to detect handwritten digits.\n- [`04_Projects`](./04_Projects):\n  - Project 1: specific terms are searched and highlighted in book images.\n  - Project 2: processing (alignment, thresholding, etc.) of a receipt to apply OCR.\n  - Project 3: license plate detection.\n\nThe folder `01` is probably the most important, since the other introduce additional packages and extra examples.\n\nIf you are interested in other related guides:\n\n- A compilation of Object Detection and Segmentation Examples: [detection_segmentation_pytorch](https://github.com/mxagar/detection_segmentation_pytorch)\n- My notes on PyImageSearch tutorials: [pyimagesearch_tutorials](https://github.com/mxagar/pyimagesearch_tutorials)\n- My notes on the Udacity Deep Learning Nanodegree: [deep_learning_udacity](https://github.com/mxagar/deep_learning_udacity)\n- My notes on the Udacity Computer Vision Nanodepree: [computer_vision_udacity](https://github.com/mxagar/computer_vision_udacity)\n\n\nMikel Sagardia, 2023.  \nNo guarantees.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmxagar%2Focr_guide","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmxagar%2Focr_guide","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmxagar%2Focr_guide/lists"}