Seven Segment Optical Character Recognition
DIGITS_LOOKUP = {
(1, 1, 1, 1, 1, 1, 0): 0,
(1, 1, 0, 0, 0, 0, 0): 1,
(1, 0, 1, 1, 0, 1, 1): 2,
(1, 1, 1, 0, 0, 1, 1): 3,
(1, 1, 0, 0, 1, 0, 1): 4,
(0, 1, 1, 0, 1, 1, 1): 5,
(0, 1, 1, 1, 1, 1, 1): 6,
(1, 1, 0, 0, 0, 1, 0): 7,
(1, 1, 1, 1, 1, 1, 1): 8,
(1, 1, 1, 0, 1, 1, 1): 9,
(0, 0, 0, 0, 0, 1, 1): '-'
}
Digital recognition of seven-segment digital tube is relatively simple compared to handwritten numeral.
Detect the existence of the corresponding bit, then encode the image, you can accurately identify the number.
- opencv
- numpy
- matplotlib
git clone https://github.com/bill0412/SSOCR.git
pip install -r requirements.txt
python ssocr.py images/test1.png -s -r
$ python ssocr.py images\test1.BMP
['-', 3, 0, '.', 3, 7]
$ python ssocr.py images\test2.BMP -s
[1, 7, 7, '.', 7]
$ python ssocr.py images\test3.BMP -s
[0, 7, 8, '.', 3]
$ python ssocr.py images\test4.BMP -s
[0, 7, 2, '.', 6]
$ python ssocr.py images/test4.png -r # for images with reverted black and white
[1, '.', 9, 9]
