GSoC Weekly status update #8

I have changed the framework interface from its previous form, although the previous front end is still present in the repo. Now the new interface,, need all the file names to be provided as command line arguments. The user gets the convenience  of using the tab completion this way. The user will have to give as command line arguments 6 files (font  file, test cases file, reference file, rendering output and files to store output) and an optional directory name(if the engine is harfbuzz).
 If the rendering engine is harfbuzz, user can run the script  along with the test cases file and font file as parameters, to create the rendered output file. If that is not the case, the user will have to create this file as well in the prescribed form.

Now, the algorithm that actually test the rendering was a bit buggy and was giving certain wrong outputs for words with multiple rendering engines and I have cleared this error. This feature gives correct output now for the files I tried it with.
The next thing I am working on is the web interface and I am using Flask framework. Will make this code public as soon as I get the script running from the page.

GSoC Weekly report #4

This week my main task was to migrate my code to Python. As of now I have implemented my algorithm in Python. Here is the link to the repo :

I have expanded my test cases’ list a bit. Now it has 243 Malayalam words. I have manually created files with glyph names of these test cases in four fonts: Rachana, Meera, Suruma and Lohith-Malayalam in files names rachana-glyph.txt,  meera-glyph.txt etc. (It is still a bit buggy, so haven’t pushed the latest commit of this yet).

What the code basically does is, it will ask the tester which font she/he wants to test in. Say it is Meera. The code will look for the reference file which we manually create and the file with harfbuzz rendering of the test cases, names as hb_meera_rendering.txt. This file can be created by running script with proper font files in the current directory. The main script will scan both these files and compare the glyph name corresponding to each word and stores the wrongly rendered words to a new list. Finally hb-view will be executed on the words inside this list and a file named output.png will be generated in the same directory that contains all the wrongly rendered words.

The baseline glyph names’ files aren’t ready yet with complete glyph names of all the 243 words. Will be able to complete it within 1-2 days.

GSoC Weekly update #2

Coding period for GSoC has started the past week and I have been working on a very simple implementation of the proposal in C and two tiny bash scripts. My code is available here:

The first thing to be done to test using these scripts is create a file that contains a set of words to be tested to see if their rendering is correct. Here I have taken a sample test data file created by SMC a while ago (ml-harfbuzz-testdata,txt). Now pass this file through the script along with the necessary font file. That is:

./ ml-harfbuzz-testdata.txt /path/to/fontfile

This will create a file named rendered_glyphs.txt that contains the output of hb-shape function of harfbuzz, i.e. the glyph name followed by some additional numbers (which will be ignored for now).

Now create a file that contains the actual glyph names of the words in the the test data wordfile. I got the data from font forge. This has to be created manually and, as of now, obeying the following structure:






Also make sure that glyph names of each word is in the same order as that of the corresponding words in the test data file. I have named it orig_glyphs.txt Once this is done, we can pass the above two files through the executable of the script rendering_testing.c, say rendering_testing. That is:

./rendering_testing orig_glyphs.txt rendered_glyphs.txt

This script will compare the glyphs in order and if it find any pairs that doesn’t match, it will write to a file, result.txt, the line number in which the word appears in the test data file. Otherwise it will tell you the renderings are perfect.

Once this is done, to see the words with wrong renderings we will have to run the third script It takes as input the result.txt file, the test data file and also the font file. That is:

./ result.txt ml-harfbuzz-testdata.txt /path/to/fontfile

This script will create png images of the wrongly rendered words in the current directory.

That is all about my scripts. But the C code is very much inefficient. It even spits segmentation faults with some files. Once I make sure that I am on the right path after discussing with my mentor, I will be working on improving my algorithm and making this code better. That would be my next week’s work.