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https://github.com/yas-sim/handwritten-japanese-ocr
Handwritten Japanese OCR demo using touch panel to draw the input text using Intel OpenVINO toolkit
https://github.com/yas-sim/handwritten-japanese-ocr
deep-learning dl-models handwritten-text-recognition inference-engine intel japanese ocr ocr-demo openvino python text-detection text-recognition text-regions touch-panel
Last synced: 3 days ago
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Handwritten Japanese OCR demo using touch panel to draw the input text using Intel OpenVINO toolkit
- Host: GitHub
- URL: https://github.com/yas-sim/handwritten-japanese-ocr
- Owner: yas-sim
- License: apache-2.0
- Created: 2020-05-01T08:27:12.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-04-05T02:16:34.000Z (over 2 years ago)
- Last Synced: 2024-04-23T00:09:51.717Z (7 months ago)
- Topics: deep-learning, dl-models, handwritten-text-recognition, inference-engine, intel, japanese, ocr, ocr-demo, openvino, python, text-detection, text-recognition, text-regions, touch-panel
- Language: Python
- Homepage:
- Size: 821 KB
- Stars: 33
- Watchers: 1
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Handwritten Japanese Deep Learning Based OCR with Touch Panel Demo
This is a handwritten Japanese OCR demo program based on a sample program from [**Intel(r) Distribution of OpenVINO(tm) Toolkit 2020.2**](https://software.intel.com/en-us/openvino-toolkit) (`handwritten-japanese-recognition.py`)
The demo program has simple UI and you can write Japanese on the screen with the touch panel by your finger tip and try Japanese OCR performance.
The demo uses a pre-trained text-detection DL model (`text-detection-0003`) from Intel(r) [Open Model Zoo](https://github.com/opencv/open_model_zoo) to detect the text regions from the canvas and run a DL based OCR model for those text regions.
手書き日本語OCRデモです。[**Intel(r) Distribution of OpenVINO(tm) toolkit 2020.2**](https://software.intel.com/en-us/openvino-toolkit)に付属の`handwritten-japanese-recognition.py`デモを大幅に書き換えています。
簡単なUIを用意していますのでタッチパネル付きPCがあれば指で字を書いて認識させるデモを行うことが可能です。
Intel(r) [Open Model Zoo](https://github.com/opencv/open_model_zoo)の文字検出DLモデル(`text-detection-0003`)で自動領域識別も行ない、DL-OCRモデルで文字認識を行います。
[NEW 03-Apr-2022] Added C++ postprocess version. **Text detection postprocess performance improved by ~x20.** (handwritten-japanese-ocr-touch-panel-demo-cpp.py).
[NEW 03-Apr-2022] Migrated OpenVINO API to API 2.0 for both native Python version and C++ postprocess version. (OpenVINO 2022.1 support)
### Required DL Models to Run This Demo
The demo expects the following models in the Intermediate Representation (IR) format:
* handwritten-japanese-recognition-0001
* text-detection-0003
You can download those models from OpenVINO [Open Model Zoo](https://github.com/opencv/open_model_zoo).
In the `models.lst` is the list of appropriate models for this demo that can be obtained via `Model downloader`.
Please see more information about `Model downloader` [here](../../../tools/downloader/README.md).
## How to Run
(Assuming you have successfully installed and setup OpenVINO 2020.2. If you haven't, go to the OpenVINO web page and follow the [*Get Started*](https://software.intel.com/en-us/openvino-toolkit/documentation/get-started) guide to do it.)
### 1. Install dependencies
The demo depends on:
- opencv-python
- numpy
To install all the required Python modules you can use:
``` sh
(Linux) python3 -m pip install -r requirements.txt
(Win10) python -m pip install -r requirements.txt
```
### 2. Download DL models from OMZ
Use `Model Downloader` to download the required models.
``` sh
(Linux/Win10) omz_downloader --list models.lst
```
### 3. Build C++ postprocess Python module (Optional)
Prerequisites: To build the C++ postprocess Python module, you need to install OpenVINO dev package and OpenCV dev package. OpenVINO and OpenCV must be found by cmake.
Please refer to the [OpenVINO install guide](https://docs.openvino.ai/latest/openvino_docs_install_guides_overview.html) for details.
```sh
(Linux)
source setup_ocv_vars.sh
./build.sh
(Win10)
setup_ocv_vars.bat
build.bat
```
### 4. Run the demo app
This program doesn't take any command line arguments. All file names and paths are hard coded in the source code.
``` sh
(Linux) python3 handwritten-japanese-OCR-touch-panel-demo.py
(Win10) python handwritten-japanese-OCR-touch-panel-demo.py
```
Please make sure the following files are placed at the proper location.
```
./
+ handwritten_japanese-OCR-touch-panel-demo.py
+ data
| + kondate_nakayosi_char_list.txt
+ intel
| + handwritten-japanese-recognition-0001
| | + FP16
| | | + handwritten-japanese-recognition-0001.xml
| | | + handwritten-japanese-recognition-0001.bin
| + text-detection-0003
| | + FP16
| | | + text-detection-0003.xml
| | | + text-detection-0003.bin
```
## Demo Output
The application uses the terminal to show resulting recognition text strings.
## Tested Environment
- Windows 11 x64
- Intel(r) Distribution of OpenVINO(tm) toolkit 2022.1
- Python 3.7 x64
## See Also
* [Using Open Model Zoo demos](../../README.md)
* [Model Optimizer](https://docs.openvinotoolkit.org/latest/_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html)
* [Model Downloader](../../../tools/downloader/README.md)