Working with new version of TF & Extracted Hand class to separate file.

[CT83]

I plan to move more stuff around in the coming days, and refactor it so that different styling (biases, line height, width, colors) can be managed easily. I am planning to turn this into something beginner ML Engineers like me can easily work on.

Great work on the Repo!🎉

[CT83]

I have also made few changes which allow the code to be compatible with current version of tensorflow. Please let me know what you think and if I should proceed with what I am doing and keep making PRs

[CT83]

I am just expanding on your work here, but this is what I am trying to perfect. I will send my changes in a PR if you are interested.

[mandystroech]

Can you add more writing styles/fonts too?

[CT83]

@mandystroech Head over to my Fork https://github.com/CT83/handwriting-synthesis .
See https://github.com/CT83/handwriting-synthesis/blob/testing/ct83_demo.py
Changing the styles/fonts is only a matter of changing the style, bias, line_height, stroke_widths you can get unlimited combinations using these. For anything else you would have to collect training data separately.

[CT83]

Hey @TheMasterOfMagic,

1. I am probably in the same boat as you, I honestly don't know how the styles were generated, I will probably have to look into it myself, but I think maybe maybe you could try to view them using OpenCV's cv2.imshow() the styles seem to be numpy arrays and so are OpenCV images, I am not sure how that would work, but it's worth a try.
   You might have already read the paper this repo is based on Generating Sequences With Recurrent Neural Networks by Alex Graves does it shed any light on how this process works?

2. You could try looking more into the rnn.py, tf_base_model.py and the checkpoints directory, that is where the original model seems to be stored.

I was working on this project more from refactoring the code point of view I wished I was of more help.
Also, I have just enabled issues on my Fork, you should see them now, but I would suggest keeping the issues here, as I more people will see those.

[CT83]

Wow! You made some progress! Awesome, keep at it.
I am glad to hear that the reading the paper helped.
You could try joining some online groups like Slack Channels those usually are full of smart people, who can help.
Google. Deep Learning Slack Groups

[ifradev-me]

hi, does anyone know where the datasets are? because the website always timed out when i try to go there.