From 464169cec589c1bb9edaffe993827bcb01890a8e Mon Sep 17 00:00:00 2001 From: JMARyA Date: Thu, 19 Sep 2024 09:13:50 +0200 Subject: [PATCH] add ocrs --- technology/applications/Applications.md | 1 + technology/applications/cli/ocrs.md | 29 +++++++++++++++++++++++++ 2 files changed, 30 insertions(+) create mode 100644 technology/applications/cli/ocrs.md diff --git a/technology/applications/Applications.md b/technology/applications/Applications.md index c0da983..6d84b67 100644 --- a/technology/applications/Applications.md +++ b/technology/applications/Applications.md @@ -229,6 +229,7 @@ rev: 2024-07-14 - [tomb](./cli/tomb.md) - [dysk](./cli/dysk.md) - [pass](./cli/pass.md) +- [ocrs](./cli/ocrs.md) ## System - [Core Utils](./cli/system/Core%20Utils.md) diff --git a/technology/applications/cli/ocrs.md b/technology/applications/cli/ocrs.md new file mode 100644 index 0000000..c502ec1 --- /dev/null +++ b/technology/applications/cli/ocrs.md @@ -0,0 +1,29 @@ +--- +obj: application +repo: https://github.com/robertknight/ocrs +rev: 2024-09-19 +--- + +# ocrs +ocrs is a Rust library and CLI tool for extracting text from images, also known as OCR (Optical Character Recognition). + +The goal is to create a modern OCR engine that: +- Works well on a wide variety of images (scanned documents, photos containing text, screenshots etc.) with zero or much less preprocessing effort compared to earlier engines like Tesseract. This is achieved by using machine learning more extensively in the pipeline. +- Is easy to compile and run across a variety of platforms, including WebAssembly +- Is trained on open and liberally licensed datasets +- Has a codebase that is easy to understand and modify + +## Usage +ocrs can be used as a binary or embedded as a [rust](../../dev/programming/languages/Rust.md) crate. + +Usage: `ocrs [OPTIONS] ` + +### Options + +| Option | Description | +| ----------------------- | -------------------------------------------------- | +| `--detect-model ` | Use a custom text detection model | +| `--rec-model ` | Use a custom text recognition model | +| `-j, --json` | Output text and structure in JSON format | +| `-o, --output ` | Output file path (defaults to stdout) | +| `-p, --png` | Output annotated copy of input image in PNG format |