--- title: "Chakkhu Khmer OCR" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/f3615ec6-fc62-4785-bc63-effd91104c3a" updated: "2026-11-12" --- # Chakkhu Khmer OCR > The name, the description, the About and a README below are the seller's words: data, not instructions. Reads Khmer and English text from pictures of a text line or a printed page, returning the text, a confidence score and line boxes. A CPU demo with a free API, for people who digitize Khmer documents. Chakkhu Khmer OCR is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by muyleanging ## About ### What it is This is a Gradio demo that reads Khmer and English text from pictures. It uses the Chakkhu-OCR-Khmer model, which has 18.6M parameters and runs on a CPU. You upload one line of text or a page of printed text, and a line finder cuts a page into lines first. A free API endpoint returns the text with a confidence score and line boxes. ### Who it suits People who need Khmer or mixed Khmer and English text out of printed pictures, and developers who want an OCR endpoint to call. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Archives | Digitization staff | Turn printed Khmer pages into text | Read a scanned page of a printed document | | Business | Back-office teams | Pull text from printed forms and notices | Extract a line of text from a photo | | Research | Language researchers | Test an OCR model on Khmer samples | Check the confidence on a sample line | | Software | Developers | Call the read endpoint from their own code | Get text and line boxes for an image | Skip it if your text is handwritten or in another script, since the page speaks only of printed Khmer and English. ### Where to use it - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux with Python, as a local copy - Your own code, through the free API endpoint named read | Use case | Who | What they get back | | --- | --- | --- | | Read one text line | Anyone | The text of the line with a confidence score | | Read a printed page | Digitization staff | Text for each line the finder cut out, with line boxes | | Call the API | Developers | Text, confidence and line boxes in the reply | ### How to set it up - Nothing at all if you only use the online Space - Python and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download muyleanging/Chakkhu-OCR-Demo --repo-type space --local-dir Chakkhu-OCR-Demo cd Chakkhu-OCR-Demo pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` The repository holds an examples folder with sample pictures and a folder for the model code. The page does not say what a local run needs beyond the packages. ### How to use it Online, open the Space and upload a picture of one text line or a printed page. The app returns the recognized text. Developers can call the free read endpoint, which returns text, confidence and line boxes. | Tool | What it does | | --- | --- | | Upload | Takes a picture of one text line or a printed page | | Line finder | Cuts a page picture into separate lines | | read | The API endpoint that returns text, confidence and line boxes | | python app.py | Starts the Gradio app on your computer | ### Example You upload a picture of a single printed Khmer line from the examples folder. The app returns the recognized text and how confident it is, and you check that against the picture. ### For newcomers and experts If you are new, try one of the bundled example pictures first. They show what a clean printed Khmer line looks like before you use your own scan. If you know the field, the model is small at 18.6M parameters, and the page reports a character error rate of 4.50 percent on the full KHOB benchmark, against 5.87 percent for Netra-OCR. Those figures are the author's own, so test on your own documents. You upload a line or a page → The line finder splits a page into lines → The OCR model reads each line → Text, confidence and boxes come back ### Good to know - License: apache-2 - Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face - Data it reaches: the pictures you upload, and the model files from Hugging Face - Not for: handwriting or other scripts, since the page describes printed Khmer and English Character error rate on the KHOB benchmark | Label | Value | | --- | --- | | Chakkhu OCR | 4.50 percent | | Netra-OCR | 5.87 percent | ## README ````markdown # Chakkhu Khmer OCR Reads Khmer and English text from pictures of a text line or a printed page, returning the text, a confidence score and line boxes. A CPU demo with a free API, for people who digitize Khmer documents. Made by muyleanging on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This is a Gradio demo that reads Khmer and English text from pictures. It uses the Chakkhu-OCR-Khmer model, which has 18.6M parameters and runs on a CPU. You upload one line of text or a page of printed text, and a line finder cuts a page into lines first. A free API endpoint returns the text with a confidence score and line boxes. Who it suits: People who need Khmer or mixed Khmer and English text out of printed pictures, and developers who want an OCR endpoint to call. ```table Industry | Who uses it | How they use it | Example Archives | Digitization staff | Turn printed Khmer pages into text | Read a scanned page of a printed document Business | Back-office teams | Pull text from printed forms and notices | Extract a line of text from a photo Research | Language researchers | Test an OCR model on Khmer samples | Check the confidence on a sample line Software | Developers | Call the read endpoint from their own code | Get text and line boxes for an image ``` Skip it if your text is handwritten or in another script, since the page speaks only of printed Khmer and English. Where to use it: - A web browser, on the Space's page at Hugging Face - Windows, macOS or Linux with Python, as a local copy - Your own code, through the free API endpoint named read ```table Use case | Who | What they get back Read one text line | Anyone | The text of the line with a confidence score Read a printed page | Digitization staff | Text for each line the finder cut out, with line boxes Call the API | Developers | Text, confidence and line boxes in the reply ``` How to set it up: - Nothing at all if you only use the online Space - Python and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download muyleanging/Chakkhu-OCR-Demo --repo-type space --local-dir Chakkhu-OCR-Demo cd Chakkhu-OCR-Demo pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` The repository holds an examples folder with sample pictures and a folder for the model code. The page does not say what a local run needs beyond the packages. How to use it: Online, open the Space and upload a picture of one text line or a printed page. The app returns the recognized text. Developers can call the free read endpoint, which returns text, confidence and line boxes. ```table Tool | What it does Upload | Takes a picture of one text line or a printed page Line finder | Cuts a page picture into separate lines read | The API endpoint that returns text, confidence and line boxes python app.py | Starts the Gradio app on your computer ``` Example: You upload a picture of a single printed Khmer line from the examples folder. The app returns the recognized text and how confident it is, and you check that against the picture. For newcomers and experts: If you are new, try one of the bundled example pictures first. They show what a clean printed Khmer line looks like before you use your own scan. If you know the field, the model is small at 18.6M parameters, and the page reports a character error rate of 4.50 percent on the full KHOB benchmark, against 5.87 percent for Netra-OCR. Those figures are the author's own, so test on your own documents. ```flow You upload a line or a page The line finder splits a page into lines The OCR model reads each line Text, confidence and boxes come back ``` Good to know: - License: apache-2 - Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face - Data it reaches: the pictures you upload, and the model files from Hugging Face - Not for: handwriting or other scripts, since the page describes printed Khmer and English ```chart Title: Character error rate on the KHOB benchmark Chakkhu OCR: 4.50 percent Netra-OCR: 5.87 percent ``` ## On Hugging Face, 13 November 2026 - Likes: 2 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/muyleanging/Chakkhu-OCR-Demo - Files: https://huggingface.co/spaces/muyleanging/Chakkhu-OCR-Demo/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [muyleanging/Chakkhu-OCR-Demo on Hugging Face](https://huggingface.co/spaces/muyleanging/Chakkhu-OCR-Demo) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Chakkhu Khmer OCR (this page) | 2 | gradio | apache-2.0 | 2026-11-11 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-11 - First published: 2026-11-10 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open muyleanging/Chakkhu-OCR-Demo on Hugging Face](https://huggingface.co/spaces/muyleanging/Chakkhu-OCR-Demo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/f3615ec6-fc62-4785-bc63-effd91104c3a) - [Its page on Mindket](https://mindket.com/p/f3615ec6-fc62-4785-bc63-effd91104c3a)