Mindket

CnOCR Demo

Newversion 1 · updated

Overview

A Gradio demo of CnOCR, a Python OCR toolkit that reads English, numbers, Chinese and vertical text from pictures. It suits people who want to try it before installing it.

CnOCR Demo is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Python and pip
  • The huggingface_hub package, to fetch the files
  • Gradio 5.35.0, and the packages in requirements.txt
  • The system packages in packages.txt, which Hugging Face installs with apt-get
Runs in
  • A web browser, straight from the Space page on Hugging Face
  • Windows, macOS or Linux with Python, as a local copy
  • Python 3 programs, where the CnOCR toolkit itself is used
Start with
pip install -U huggingface_hub
hf download breezedeus/CnOCR-Demo --repo-type space --local-dir CnOCR-Demo
cd CnOCR-Demo

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

CnOCR Demo is a Gradio app on Hugging Face Spaces for CnOCR, an optical character recognition toolkit for Python 3. CnOCR reads English letters and numbers, Simplified Chinese, some Traditional Chinese models and vertical text. It ships with more than 20 trained models for different scenes and offers simple training commands for your own models.

Who it suits

It suits people who need to read Chinese or English text from pictures, and developers who want to try CnOCR before installing the toolkit.

IndustryWho uses itHow they use itExample
AdministrationOffice staffTurn a photographed document into textOpen the Space and give it a picture of a page
SoftwarePython developersTry the recognition quality before adding the toolkitRun a test picture through the demo
PublishingEditorsPull text out of images with vertical writingGive it a picture of a vertical text block

Anyone who needs handwriting recognition can skip it, since the source does not mention handwriting.

Where to use it

  • A web browser, straight from the Space page on Hugging Face
  • Windows, macOS or Linux with Python, as a local copy
  • Python 3 programs, where the CnOCR toolkit itself is used
Use caseWhoWhat they get back
Read text from a pictureAnyone with a scanThe recognised text, shown in the browser
Test the toolkitDevelopersA quick view of how CnOCR handles their images
Train a custom modelResearchersSimple training commands that the toolkit provides

How to set it up

Using it online needs nothing. A local copy needs these first.

  • Python and pip
  • The huggingface_hub package, to fetch the files
  • Gradio 5.35.0, and the packages in requirements.txt
  • The system packages in packages.txt, which Hugging Face installs with apt-get
  1. Install the Hugging Face Hub package.
  2. Download the Space into a folder called CnOCR-Demo.
  3. Move into that folder.
  4. Install Gradio 5.35.0, then the packages from requirements.txt.
  5. Start the app.
pip install -U huggingface_hub
hf download breezedeus/CnOCR-Demo --repo-type space --local-dir CnOCR-Demo
cd CnOCR-Demo
pip install gradio==5.35.0
pip install -r requirements.txt
python app.py

How to use it

Open the Space page on Hugging Face and give it a picture that holds text. For a local copy, run python app.py in the folder and open the page it starts.

Example

You give the app a photo of a page with Chinese text. It runs CnOCR on the picture and shows the characters it recognises.

For newcomers and experts

If you are new, try a clear photo of a short line of text. OCR means a program reads the letters in a picture and gives them back as text.

If you know the field, CnOCR offers a range of pretrained models for different scenes and lets you train your own with its commands. The repository also holds a Streamlit version of the demo besides the Gradio one.

  1. You give the app a picture with text
  2. CnOCR runs a recognition model on it
  3. The recognised text shows on the page

Good to know

  • It reads common characters in English, numbers and Chinese, plus vertical text, and some models cover Traditional Chinese
  • The Space runs on the basic CPU hardware at Hugging Face, so large pictures may take a while
  • License: apache-2
  • Cost to run: none named
  • Data it reaches: the pictures you give it

README and files

README

CnOCR Demo

A Gradio demo of CnOCR, a Python OCR toolkit that reads English, numbers, Chinese and vertical text from pictures. It suits people who want to try it before installing it.

Made by breezedeus 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: CnOCR Demo is a Gradio app on Hugging Face Spaces for CnOCR, an optical character recognition toolkit for Python 3. CnOCR reads English letters and numbers, Simplified Chinese, some Traditional Chinese models and vertical text. It ships with more than 20 trained models for different scenes and offers simple training commands for your own models.

Who it suits: It suits people who need to read Chinese or English text from pictures, and developers who want to try CnOCR before installing the toolkit.

Industry | Who uses it | How they use it | Example
Administration | Office staff | Turn a photographed document into text | Open the Space and give it a picture of a page
Software | Python developers | Try the recognition quality before adding the toolkit | Run a test picture through the demo
Publishing | Editors | Pull text out of images with vertical writing | Give it a picture of a vertical text block

Anyone who needs handwriting recognition can skip it, since the source does not mention handwriting.

Where to use it:

  • A web browser, straight from the Space page on Hugging Face
  • Windows, macOS or Linux with Python, as a local copy
  • Python 3 programs, where the CnOCR toolkit itself is used
Use case | Who | What they get back
Read text from a picture | Anyone with a scan | The recognised text, shown in the browser
Test the toolkit | Developers | A quick view of how CnOCR handles their images
Train a custom model | Researchers | Simple training commands that the toolkit provides

How to set it up: Using it online needs nothing. A local copy needs these first.

  • Python and pip
  • The huggingface_hub package, to fetch the files
  • Gradio 5.35.0, and the packages in requirements.txt
  • The system packages in packages.txt, which Hugging Face installs with apt-get
  1. Install the Hugging Face Hub package.
  2. Download the Space into a folder called CnOCR-Demo.
  3. Move into that folder.
  4. Install Gradio 5.35.0, then the packages from requirements.txt.
  5. Start the app.
pip install -U huggingface_hub
hf download breezedeus/CnOCR-Demo --repo-type space --local-dir CnOCR-Demo
cd CnOCR-Demo
pip install gradio==5.35.0
pip install -r requirements.txt
python app.py

How to use it: Open the Space page on Hugging Face and give it a picture that holds text. For a local copy, run python app.py in the folder and open the page it starts.

Example: You give the app a photo of a page with Chinese text. It runs CnOCR on the picture and shows the characters it recognises.

For newcomers and experts: If you are new, try a clear photo of a short line of text. OCR means a program reads the letters in a picture and gives them back as text.

If you know the field, CnOCR offers a range of pretrained models for different scenes and lets you train your own with its commands. The repository also holds a Streamlit version of the demo besides the Gradio one.

You give the app a picture with text
CnOCR runs a recognition model on it
The recognised text shows on the page

Good to know:

  • It reads common characters in English, numbers and Chinese, plus vertical text, and some models cover Traditional Chinese
  • The Space runs on the basic CPU hardware at Hugging Face, so large pictures may take a while
  • License: apache-2
  • Cost to run: none named
  • Data it reaches: the pictures you give it

On Hugging Face, 13 November 2026

  • Likes: 47
  • Built with: gradio
  • License: apache-2.0

Links

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.

Files
README.md  4 KB

1 file, 4 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
CnOCR Demo This page47gradioapache-2.0
FLUX.1 [dev]Shares gradio9,583gradiomit
InstantIDShares gradio3,659gradioapache-2.0
Chat With Janus-Pro-7BShares gradio2,036gradiomit
PhotoMakerShares gradio1,960gradioapache-2.0
Z Image TurboShares gradio1,940gradioapache-2.0
Numbers as Mindket last read them, on 2026-11-12.

Reviews

No ratings yet

Write a review

No reviews yet.

More from Mindket

See all from Mindket

Nanosaur2-670M

well9472 · Kit

Makes illustrations from text prompts with a small 670M-parameter diffusion model, run through ComfyUI. Built as a low-budget research model for people who wan…

New

Reads handwritten Arabic text from images and returns it as text. A fine-tuned PaddleOCR-VL model for people digitizing Arabic handwriting.

New

Makes video clips from a text prompt or an image plus text, at up to 720P and 24 frames per second, in the Diffusers format for a single consumer GPU.

New

Similar in Developer

See all in Developer

Wan2.2-S2V-14B

Wan-AI · Kit

Generates cinematic video of a character driven by an audio track, and can also lip-sync existing video. For video creators, animators and researchers with a l…

New

Wan2.2-Animate-14B

Wan-AI · Kit

Animates a character or swaps one into a video by copying a performer's movement and expressions, as one model from the Wan2.2 video family. Use only faces and…

New

d3-turbo

vllm-sr · Kit

Answers choice, yes-or-no, score, box and tracking questions about text, images or video in one call, with a probability for each answer. For people building r…

New