angzhou / anchor Goto Github PK

Dear author,

I'm very impressed by the accuracy you achieved. Congratulations!
At my local side, I reproduced the model test and also verified it with my experiment data. One interesting thing I found that if the threshold value on my input images is around 100, the result can be pretty good.

Btw, when I tried to recognize the alphanumeric and symbols using the same model, it did not work. After I checked the data in ICDAR 2013 competition test database and also the data/lables.txt in this source, and I guessed the model actually do not support them.

So do you have plan on this? From the view of application, number and general symbols are frequently used. If possible, could you share the training part. Or have you published your paper work in somewhere?

Thanks again for your great work.

Prediction: top3: [('九', '35.49'), ('右', '21.37'), ('力', '20.25')]

Robust offline handwritten character recognition through exploring writer-independent features under the guidance of printed data