TextRecognitionDataGenerator 
A synthetic data generator for text recognition
What is it for?
Generating text image samples to train an OCR software. Now supporting non-latin text! For a more thorough tutorial see the official documentation.
What do I need to make it work?
Install the pypi package
pip install trdg
Afterwards, you can use trdg from the CLI. I recommend using a virtualenv instead of installing with sudo.
If you want to add another language, you can clone the repository instead. Simply run pip install -r requirements.txt
Docker image
If you would rather not have to install anything to use TextRecognitionDataGenerator, you can pull the docker image.
docker pull belval/trdg:latest
docker run -v /output/path/:/app/out/ -t belval/trdg:latest trdg [args]
The path (/output/path/) must be absolute.
New
- Add
--stroke_widthargument to set the width of the text stroke (Thank you @SunHaozhe) - Add
--stroke_fillargument to set the color of the text contour if stroke > 0 (Thank you @SunHaozhe) - Add
--word_splitargument to split on word instead of per-character. This is useful for ligature-based languages - Add
--dictargument to specify a custom dictionary (Thank you @luh0907) - Add
--font_dirargument to specify the fonts to use - Add
--output_maskto output character-level mask for each image - Add
--character_spacingto control space between characters (in pixels) - Add python module
- Add
--fontto use only one font for all the generated images (Thank you @JulienCoutault!) - Add
--fitand--marginsfor finer layout control - Change the text orientation using the
-orparameter - Specify text color range using
-tc '#000000,#FFFFFF', please note that the quotes are necessary - Add support for Simplified and Traditional Chinese
How does it work?
Words will be randomly chosen from a dictionary of a specific language. Then an image of those words will be generated by using font, background, and modifications (skewing, blurring, etc.) as specified.
Basic (Python module)
The usage as a Python module is very similar to the CLI, but it is more flexible if you want to include it directly in your training pipeline, and will consume less space and memory. There are 4 generators that can be used.
from trdg.generators import (
GeneratorFromDict,
GeneratorFromRandom,
GeneratorFromStrings,
GeneratorFromWikipedia,
)
# The generators use the same arguments as the CLI, only as parameters
generator = GeneratorFromStrings(
['Test1', 'Test2', 'Test3'],
blur=2,
random_blur=True
)
for img, lbl in generator:
# Do something with the pillow images here.
You can see the full class definition here:
Basic (CLI)
trdg -c 1000 -w 5 -f 64
You get 1,000 randomly generated images with random text on them like:
By default, they will be generated to out/ in the current working directory.
Text skewing
What if you want random skewing? Add -k and -rk (trdg -c 1000 -w 5 -f 64 -k 5 -rk)
Text distortion
You can also add distorsion to the generated text with -d and -do
Text blurring
But scanned document usually aren't that clear are they? Add -bl and -rbl to get gaussian blur on the generated image with user-defined radius (here 0, 1, 2, 4):
Background
Maybe you want another background? Add -b to define one of the three available backgrounds: gaussian noise (0), plain white (1), quasicrystal (2) or image (3).
When using image background (3). A image from the images/ folder will be randomly selected and the text will be written on it.
Handwritten
Or maybe you are working on an OCR for handwritten text? Add -hw! (Experimental)
It uses a Tensorflow model trained using this excellent project by Grzego.
The project does not require TensorFlow to run if you aren't using this feature
Dictionary
The text is chosen at random in a dictionary file (that can be found in the dicts folder) and drawn on a white background made with Gaussian noise. The resulting image is saved as [text]_[index].jpg
There are a lot of parameters that you can tune to get the results you want, therefore I recommend checking out trdg -h for more information.
Create images with Chinese text
It is simple! Just do trdg -l cn -c 1000 -w 5!
Generated texts come both in simplified and traditional Chinese scripts.
Traditional:
Simplified:
Add new fonts
The script picks a font at random from the fonts directory.
| Directory | Languages |
|---|---|
| fonts/latin | English, French, Spanish, German |
| fonts/cn | Chinese |
| fonts/ko | Korean |
Simply add/remove fonts until you get the desired output.
If you want to add a new non-latin language, the amount of work is minimal.
- Create a new folder with your language two-letters code
- Add a .ttf font in it
- Edit
run.pyto add an if statement inload_fonts() - Add a text file in
dictswith the same two-letters code - Run the tool as you normally would but add
-lwith your two-letters code
It only supports .ttf for now.
Benchmarks
Number of images generated per second.
- Intel Core i7-4710HQ @ 2.50Ghz + SSD (-c 1000 -w 1)
-t 1: 363 img/s-t 2: 694 img/s-t 4: 1300 img/s-t 8: 1500 img/s
- AMD Ryzen 7 1700 @ 4.0Ghz + SSD (-c 1000 -w 1)
-t 1: 558 img/s-t 2: 1045 img/s-t 4: 2107 img/s-t 8: 3297 img/s
Contributing
- Create an issue describing the feature you'll be working on
- Code said feature
- Create a pull request
Feature request & issues
If anything is missing, unclear, or simply not working, open an issue on the repository.
What is left to do?
- Better background generation
- Better handwritten text generation
- More customization parameters (mostly regarding background)
why they got different width(ps:i use my own texts)
Looking forward to hear from you .
@Belval
2 Jan 31, 2022
0 Oct 30, 2021
4 Mar 04, 2022
496 Jan 05, 2023
49 Sep 22, 2022
544 Dec 19, 2022
11 Dec 12, 2022
273 Jan 06, 2023
6 Apr 18, 2022
758 Dec 22, 2022
772 Dec 30, 2022
52 Nov 11, 2022
28 Nov 03, 2022
7.6k Jan 06, 2023
391 Dec 30, 2022
7 Dec 06, 2022
1 Jan 28, 2022
128 Dec 04, 2022
2 Sep 28, 2022
111 Nov 13, 2022