simoncozens / atokern Goto Github PK

And cache it. Massive speed up.

Thanks for your work Simon, such an exciting project!

Upon cloning the repo, installing the requirements and fontTools via pip3 and running .kerncritic, I get the following error:

AttributeError: module 'tensorflow' has no attribute 'logging'

Any pointers please?

I'm trying to run the training script on a group of fonts.

I've dumped the kerning, it's pickled all the fonts, etc. I'm running the script "out of the box" so to speak, with no adjustments to the settings.

When it comes to the "Training" portion I'm getting an error.

Traceback (most recent call last):
  File "atokern.keras.py", line 334, in <module>
    ],shuffle = True, validation_data=(val_tensors, val_kern))
  File "/usr/local/lib/python3.6/site-packages/keras/engine/training.py", line 1602, in fit
    batch_size=batch_size)
  File "/usr/local/lib/python3.6/site-packages/keras/engine/training.py", line 1414, in _standardize_user_data
    exception_prefix='input')
  File "/usr/local/lib/python3.6/site-packages/keras/engine/training.py", line 141, in _standardize_input_data
    str(array.shape))
ValueError: Error when checking input: expected rightofl to have 3 dimensions, but got array with shape (0, 1)

Printing val_tensors reveals that all my arrays are empty. Any idea of what I am doing wrong?

{'rightofl': array([], shape=(0, 1), dtype=float64),
'leftofr': array([], shape=(0, 1), dtype=float64), 
'rightofo': array([], shape=(0, 1), dtype=float64), 
'rightofH': array([], shape=(0, 1), dtype=float64), 
'mwidth': array([], dtype=float64)}

Looks like this reference no longer exists: http://www.simon-cozens.org/downloads/kernmodel.hdf5

With quite a lot of the font files I’ve tried this on, including the one I want to actually get suggested kerning values for, I get an error:

Font <filename> produced a string that was too wide/high

Looking at the source, it appears I possibly need to increase box_width and box_height, but having tried that it also seems that requires retraining the neural network from scratch since it assumes particular values for these variables.

Is there another possible approach to fixing this?

Hi Simon,

Amazing project – I tried something like this many years ago but the tooling around neural nets was so poor that I didn't get anywhere. In my opinion, you're going about this exactly the right way, so I'm really excited I found this. I want to bring up something that was already mentioned in the Typedrawers thread: the idea of doing letter-fitting in one go, i.e. spacing and kerning at the same time.

You can use a linear programming model to turn the resulting glyph distance pairs into a set of sidebearings plus a kerning table that's minimized by the sum of absolute or squared kerns (i.e. what I did in skosch/fittingroom). You also get around ethical complaints, because your training data is now based on total glyph distances, not raw sidebearing and kerning values, which amounts to learning from printed matter instead of pirated font file data.

If you're worried (as you mentioned in your TD post) about unusual pairs like /t/Q messing up your training data ... maybe you can go through a few big corpora and identify pair frequencies and then drop uncommon pairs from the training data (or put them into low-learning-rate batches), as those are the ones designers would probably ignore.

I'd love to learn what your plans are for this project. Looking forward to your comments.

I had to do this:

diff --git a/kerncritic b/kerncritic
index 9892895..6f9e8f7 100755
--- a/kerncritic
+++ b/kerncritic
@@ -25,7 +25,7 @@ def download_url(url, output_path):
                              miniters=1, desc=url.split('/')[-1]) as t:
         urllib.request.urlretrieve(url, filename=output_path, reporthook=t.update_to)
 
-tf.logging.set_verbosity(tf.logging.ERROR)
+tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
 
 if not os.path.exists("badkerndetector.hdf5"):
   print("Downloading bad kern detection model")

And then downloading http://dealer.simon-cozens.org/~simon/badkerndetector.hdf5 fails.