A synthetic data generator for text recognition
Generating text image samples to train an OCR software. Now supporting non-latin text!
I use Archlinux so I cannot tell if it works on Windows yet.
Python 3.X
OpenCV 3.2 (It probably works with 2.4)
Pillow
Numpy
Requests
BeautifulSoup
tqdm
You can simply use pip install -r requirements.txt
too.
-tc '#000000,#FFFFFF'
, please note that the quotes are necessary
-al
with fixed width (0: Left, 1: Center, 2: Right)-wd
python run.py -w 5 -f 64
You get 1000 randomly generated images with random text on them like:
What if you want random skewing? Add -k
and -rk
(python run.py -w 5 -f 64 -k 5 -rk
)
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):
Maybe you want another background? Add -b
to define one of the three available backgrounds: gaussian noise (0), plain white (1), quasicrystal (2) or picture (3).
When using picture background (3). A picture from the pictures/ folder will be randomly selected and the text will be written on it.
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
You can also add distorsion to the generated text with -d
and -do
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 recommand checking out python run.py -h
for more informations.
It is simple! Just do python run.py -l cn -c 1000 -w 5
!
Unfortunately I do not speak Chinese so you may have to edit texts/cn.txt
to include some meaningful words instead of random glyphs.
Here are examples of what I could make with it:
Traditional:
Simplified:
Yes, the script picks a font at random from the fonts directory.
fonts/latin | English, French, Spanish, German |
fonts/cn | Chinese |
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.
run.py
to add an if statement in load_fonts()
dicts
with the same two-letters code-l
with your two-letters codeIt only supports .ttf for now.
-t 1
: 363 img/s-t 2
: 694 img/s-t 4
: 1300 img/s-t 8
: 1500 img/s-t 1
: 558 img/s-t 2
: 1045 img/s-t 4
: 2107 img/s-t 8
: 3297 img/sIf anything is missing, unclear, or simply not working, open an issue on the repository.
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