10 ms·

Classifying Japanese characters from the Edo period

49 points by soofy 9y ago

wodenokoto 9y ago
Anyone know the work he refers to as the inspiration for this article?
titanix2 9y ago
If I understand correctly, the guy downloaded a data set, train it and get happy because it performs over 95% on the training set from the data set. This is not interesting at all because the hard part is to actually segment and classify characters in a real text, and in real life they don’t conveniently come as 28x28 images. As someone with a few hours of training in reading that kind of texts the difficulties are: - taking appart characters (hentaigana) that looks very close - segmenting characters because size and length vary a lot - differentiating between kana and kanji because the former are deritaves of the latter and they sometime look quite alike So the experimenter should have started his post telling he didn’t know any Japanese instead of closing it as such (even if one can notice when he just use modern kana as classes).
- chch 9y ago
  Since the original article doesn't give a lot of context as to what these characters looks like in context, here is an image of a Japanese book [1] and some playing cards [2] to give context to the segmentation difficulties. [1] https://wakancambridge.files.wordpress.com/2015/07/e8bbbde58fa3e381b5e3818fe3818ae3818be38197.jpg?w=640 https://wakancambridge.files.wordpress.com/2015/07/e8bbbde58... [2] http://img03.aucfan.com/item_data/image/20150720/yahoo/u/u80632805.3.jpg http://img03.aucfan.com/item_data/image/20150720/yahoo/u/u80...
  - microcolonel 9y ago
    Hard enough for a literate human to segment.
    - pavel_lishin 9y ago
      It does look like an alien language to me; I wonder what Latin or Cyrillic script would look like to someone for whom that was perfectly legible.
      - fenomas 9y ago
        Writing like this is more or less analogous to cursive handwriting in English. I mean, if you write out "minimum" in cursive, someone who learned English exclusively from printed text might think it was a scribble. But someone familiar with cursive decodes the whole word in a chunk, partly from understanding how latin letters get transformed into cursive, and partly from having seen "minimum" written in cursive before, and maybe also using nearby words for context. There's a roughly similar thing going on here.
        glandium 9y ago
        That is absolutely true, but, like cursive handwriting in English, there are cases where it's all gibberish, even to natives. See, for example, how doctors handwriting is barely readable. With effort, you can make up the words you are familiar with. But not the others. Now, imagine some text in medieval english in doctors handwriting. That would be basically undecipherable for most people. The same is true about many Edo period (and older) writings, which are written as "scribbles", and use old vocabulary/grammar that most people don't know. They are essentially unreadable to most Japanese, except the trained ones (e.g. historians).
        pavel_lishin 9y ago
        That's a good point. My last name, when written in Russian cursive, looks like a series of waves, and is effectively indistinguishable from a child's scribble.
    - deleted 9y ago
      [deleted]
- reustle 9y ago
  > This is not interesting at all because... Comments like this make me reluctant to post things I work on
  - mikekchar 9y ago
    The OP's comment is very good because the discussion in the article is quite misleading about what they accomplished. It's also apparently self-serving; apparently marketing material for Wolfram. As your sibling's post makes extremely clear, classifying handwritten text from the Edo period is a much, much, much more difficult problem. In fact the samples they have taken for training are so unstylized that they might just as well have done an article about recognising modern hiragana hand writing. That would be very cool too, but would have gathered no interest because it is a well solved problem. I have no problem with people doing fun projects and explaining how they did them. I have a bit of a problem with people apparently making exaggerated claims about their product's capabilities.
    - greeneggs 9y ago
      > I have no problem with people doing fun projects and explaining how they did them. I have a bit of a problem with people apparently making exaggerated claims about their product's capabilities. This isn't written by a Wolfram employee. It seems to be just someone's fun and educational project, posted on a Wolfram message board.
  - fenomas 9y ago
    I think the article is more mistitled than anything else. I mean, it's a fine article for someone interested in how to train a classifier on an annotated dataset in Mathematica. It's just not very interesting for someone interested in how to classify Japanese characters from the Edo period.
peterburkimsher 9y ago
I want to do the same for Chinese. I have a collection of 1500 fonts, and finally exported all the PNGs for 75,000 characters. Now I need to pad, crop, and scale to make 28x28 (or 32x32, or 64x64, or another resolution). Then I want to do the Machine Learning (Classify) step. The article doesn't go into any detail about how to install Classify, how to import the training and testing data, and how to then actually run it. I watched the videos from CS231n because of my boss, but again, I'm still not really sure what to do practically. If I have lots of folders of images, what should I do to build an OCR program?
- visarga 9y ago
  - load images, convert into array, call it X - put the labels (character codes one hot encoded) in an array called y - use a convolutional neural network to learn the mapping X->y (training) - send new images to the network to make predictions That's how you train all neural nets in supervised learning.
  - peterburkimsher 9y ago
    Just like the article, your comment is pseudo-code. Isn't there a tutorial for this?
    - yorwba 9y ago
      You could try http://fast.ai http://fast.ai They show all the steps necessary to train an image classifier (for cats vs. dogs, but it should be possible to adapt to other classes easily) and the explanations are excellent. But if you are trying to do OCR on complete texts, maybe even handwritten, you're getting close to research-level problems very quickly.
    - mchaver 9y ago
      OCR for handwritten number and Latin characters: http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_ml/py_knn/py_knn_opencv/py_knn_opencv.html http://opencv-python-tutroals.readthedocs.io/en/latest/py_tu... As my sibling poster mentioned, these are generally research level tasks. Most people working on this are either writing papers on very particular issues related to OCR or they are working in industry and the companies are not open sourcing their code because it is expensive to produce and/or they have custom data sets they don't want to give away. There might be some tutorials somewhere though. Source: previously worked on OCR systems for European and East Asian languages.
pornel 9y ago
The training set contains errors. The に row is especially messy: it's full of 小, ふ, and み.
- ramchip 9y ago
  Aren't these hentaigana? http://www.book-seishindo.jp/kana/onjun_2.html#ni http://www.book-seishindo.jp/kana/onjun_2.html#ni
  - pornel 9y ago
    Ahh, I see. These aren't supposed to be visual variants of に specifically, but are just any old forms/arbitrary other characters that were used in place of に (sort of like "V" being classified as "u" because of Roman texts).

49 points by soofy 9y ago

Anyone know the work he refers to as the inspiration for this article?

If I understand correctly, the guy downloaded a data set, train it and get happy because it performs over 95% on the training set from the data set. This is not interesting at all because the hard part is to actually segment and classify characters in a real text, and in real life they don’t conveniently come as 28x28 images. As someone with a few hours of training in reading that kind of texts the difficulties are: - taking appart characters (hentaigana) that looks very close - segmenting characters because size and length vary a lot - differentiating between kana and kanji because the former are deritaves of the latter and they sometime look quite alike So the experimenter should have started his post telling he didn’t know any Japanese instead of closing it as such (even if one can notice when he just use modern kana as classes).

chch 9y ago
Since the original article doesn't give a lot of context as to what these characters looks like in context, here is an image of a Japanese book [1] and some playing cards [2] to give context to the segmentation difficulties. [1] https://wakancambridge.files.wordpress.com/2015/07/e8bbbde58fa3e381b5e3818fe3818ae3818be38197.jpg?w=640 https://wakancambridge.files.wordpress.com/2015/07/e8bbbde58... [2] http://img03.aucfan.com/item_data/image/20150720/yahoo/u/u80632805.3.jpg http://img03.aucfan.com/item_data/image/20150720/yahoo/u/u80...
- microcolonel 9y ago
  Hard enough for a literate human to segment.
  - pavel_lishin 9y ago
    It does look like an alien language to me; I wonder what Latin or Cyrillic script would look like to someone for whom that was perfectly legible.
    - fenomas 9y ago
      Writing like this is more or less analogous to cursive handwriting in English. I mean, if you write out "minimum" in cursive, someone who learned English exclusively from printed text might think it was a scribble. But someone familiar with cursive decodes the whole word in a chunk, partly from understanding how latin letters get transformed into cursive, and partly from having seen "minimum" written in cursive before, and maybe also using nearby words for context. There's a roughly similar thing going on here.
      - glandium 9y ago
        That is absolutely true, but, like cursive handwriting in English, there are cases where it's all gibberish, even to natives. See, for example, how doctors handwriting is barely readable. With effort, you can make up the words you are familiar with. But not the others. Now, imagine some text in medieval english in doctors handwriting. That would be basically undecipherable for most people. The same is true about many Edo period (and older) writings, which are written as "scribbles", and use old vocabulary/grammar that most people don't know. They are essentially unreadable to most Japanese, except the trained ones (e.g. historians).
      - pavel_lishin 9y ago
        That's a good point. My last name, when written in Russian cursive, looks like a series of waves, and is effectively indistinguishable from a child's scribble.
  - deleted 9y ago
    [deleted]
reustle 9y ago
> This is not interesting at all because... Comments like this make me reluctant to post things I work on
- mikekchar 9y ago
  The OP's comment is very good because the discussion in the article is quite misleading about what they accomplished. It's also apparently self-serving; apparently marketing material for Wolfram. As your sibling's post makes extremely clear, classifying handwritten text from the Edo period is a much, much, much more difficult problem. In fact the samples they have taken for training are so unstylized that they might just as well have done an article about recognising modern hiragana hand writing. That would be very cool too, but would have gathered no interest because it is a well solved problem. I have no problem with people doing fun projects and explaining how they did them. I have a bit of a problem with people apparently making exaggerated claims about their product's capabilities.
  - greeneggs 9y ago
    > I have no problem with people doing fun projects and explaining how they did them. I have a bit of a problem with people apparently making exaggerated claims about their product's capabilities. This isn't written by a Wolfram employee. It seems to be just someone's fun and educational project, posted on a Wolfram message board.
- fenomas 9y ago
  I think the article is more mistitled than anything else. I mean, it's a fine article for someone interested in how to train a classifier on an annotated dataset in Mathematica. It's just not very interesting for someone interested in how to classify Japanese characters from the Edo period.

peterburkimsher 9y ago

I want to do the same for Chinese. I have a collection of 1500 fonts, and finally exported all the PNGs for 75,000 characters. Now I need to pad, crop, and scale to make 28x28 (or 32x32, or 64x64, or another resolution). Then I want to do the Machine Learning (Classify) step. The article doesn't go into any detail about how to install Classify, how to import the training and testing data, and how to then actually run it. I watched the videos from CS231n because of my boss, but again, I'm still not really sure what to do practically. If I have lots of folders of images, what should I do to build an OCR program?

visarga 9y ago
- load images, convert into array, call it X - put the labels (character codes one hot encoded) in an array called y - use a convolutional neural network to learn the mapping X->y (training) - send new images to the network to make predictions That's how you train all neural nets in supervised learning.
- peterburkimsher 9y ago
  Just like the article, your comment is pseudo-code. Isn't there a tutorial for this?
  - yorwba 9y ago
    You could try http://fast.ai http://fast.ai They show all the steps necessary to train an image classifier (for cats vs. dogs, but it should be possible to adapt to other classes easily) and the explanations are excellent. But if you are trying to do OCR on complete texts, maybe even handwritten, you're getting close to research-level problems very quickly.
  - mchaver 9y ago
    OCR for handwritten number and Latin characters: http://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_ml/py_knn/py_knn_opencv/py_knn_opencv.html http://opencv-python-tutroals.readthedocs.io/en/latest/py_tu... As my sibling poster mentioned, these are generally research level tasks. Most people working on this are either writing papers on very particular issues related to OCR or they are working in industry and the companies are not open sourcing their code because it is expensive to produce and/or they have custom data sets they don't want to give away. There might be some tutorials somewhere though. Source: previously worked on OCR systems for European and East Asian languages.

pornel 9y ago

The training set contains errors. The に row is especially messy: it's full of 小, ふ, and み.

ramchip 9y ago
Aren't these hentaigana? http://www.book-seishindo.jp/kana/onjun_2.html#ni http://www.book-seishindo.jp/kana/onjun_2.html#ni
- pornel 9y ago
  Ahh, I see. These aren't supposed to be visual variants of に specifically, but are just any old forms/arbitrary other characters that were used in place of に (sort of like "V" being classified as "u" because of Roman texts).