A synthetic data generator for text recognition
Generating text image samples to train an OCR software
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
You can simply use pip install -r requirements.txt too.
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
New
- You can add distorsion to the generated text
- You can "fake" handwriting using
-hw - You can add gaussian blur to the resulting image
- Sentences from Wikipedia can be used instead of random words with
python run.py -wk 1(requires an Internet connection) - Sentences can be picked from a file passed as a parameter with
python run.py -i ./texts/random_1.txt
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.
Yes, the script picks a font at random from the fonts directory. Simply add / remove fonts until you get the desired output.
It only supports .ttf for now.
- Create an issue describing the feature you'll be working on
- Code said feature
- Create a pull request
If anything is missing, unclear, or simply not working, open an issue on the repository.
- Better background generation
- Better handwritten text generation
- More customization parameters (mostly regarding background)
- Implement
--include_symbols - Implement
--include_numbers