بسم الله الرحمن الرحيم

Make sure you have Docker installed on your system. If you are using Docker for Windows, make sure you enable Linux containers.

For the first time, or whenever you need to make sure you have the latest image, you need to pull the docker image that is used to run the below scripts.

docker pull elmohafez/ayah-detection:latest

In the below scripts, open a bash shell container based on the image you pulled/built in the previous step, then run all the scripts under this shell.

docker run -it --rm elmohafez/ayah-detection:latest

This will open a bash shell where you can run all the scripts. For example:

./svg2png.sh ...
./detect_lines.py ...

Type exit when done to stop the shell container and return to your host shell.

Locate the SVG folder that contains 604 images in SVG format. In the below examples, we assume this is located at ~/Downloads/MHFZ_SOSY. You must mount this as a volume when launching your Docker container.

docker run -it --rm \
  -v $PWD/output/makky/MHFZ_BAZY:/svg \
  --env-file $PWD/.env \
  -e RECITATION_ID=19 -e COUNT_METHOD=makky \
  elmohafez/ayah-detection:latest

If you are using Docker for Windows, the mounted path would be something like: C:\Folder\MHFZ_SOSY.

The .env file referenced in the --env-file above should contain secret variables in the following format:

ENCRYPTION_KEY=
ENCRYPTION_IV=
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=

More details about such variables will come later.

Also RECITATION_ID and COUNT_METHOD variables should reflect those of the mounted recitation. A full list of recitations can be found in recitations.csv.

./svg2png.sh 800 10 /svg /svg/output/images

Where:

• 800 is the desired image width, known as reference width
• 10 is the padding to add to images
• /svg is the input folder (mounted by docker)
• /svg/output/images is the output folder to store resulting images

IMPORTANT: Please note that this script modifies SVG files by removing some paths from them. If you want to preserve them for further editing, it is advised that you copy them first and work on the new copy.

./fix_color_mode.py --input_path /svg/output/images/800

Where --input_path is the generated folder from the previous step.

./detect_lines.py \
  --input_path /svg/output/images/800 \
  --output_path /svg/output

Where:

• --input_path is the path to input folder containing PNG images
• --output_path is the path to output folder to generate verification images in

IMPORTANT: Manually verify all the generated images under --output_path/lines to make sure lines are properly separated with no or minor overlap between text. If necessary, edit the corresponding SVGs to minimize any overlap.

./detect_ayat.py \
  --input_path /svg/output/images/800 \
  --output_path /svg/output \
  --separator1_path ./separator1.png \
  --separator3_path ./separator3.png \
  --count_method $COUNT_METHOD \
  --matching_threshold 0.42 \
  --pages 4,6,8,10..30,500 \
  --start_sura_aya_tsv /svg/RecitationData$RECITATION_ID.tsv

Where:

• --input_path is the path to input folder containing PNG images
• --output_path is the path to output folder to generate verification images in
• --separator1_path is the path to separator image template for pages 1 and 2
• --separator3_path is the path to separator image template for pages 3 up to the end
• --count_method is the counting method to use (choices are {basry,shamy,madany2,madany1,kofy,makky})
• --matching_threshold is an optional matching threshold to match aya separators, default = 0.42
• --pages is an optional comma seprated page numbers or ranges (default is 1..604)
• --start_sura is an optional start sura numbers for each page in the input pages (default is 1)
• --start_aya is an optional start aya numbers for each page in the input pages (default is 1)
• --start_sura_aya_tsv if specified, reads start_sura and start_aya numbers from recitation tsv

In the case of partially updating recitations, you need to specify --pages and either --start_sura_aya_tsv or the pair of --start_sura and --start_aya. If you choose the latter, make sure the first sura and aya in every page are specified correctly in --start_sura and --start_aya in the same order. If you choose the former, make sure you have manually copied a previously generated RecitationData<id>.tsv in the specified path.

To get the list of pages to fill in the --pages parameter, just type this command:

ls -1 /svg/*.svg | while read l; do basename $l .svg; done | xargs | tr ' ' ','

IMPORTANT: Manually verify all the generated images under --output_path/ayat to make sure all aya separators are identified correctly. Based on the detection, aya regions are highlighted in random colors with a small text overlaid on each region. It is in the format aya:region[sura]. Sura headers have the special aya number -1 while basmalah verses have the number 0.

The script may fail in the middle if any separator is missed causing aya counts to go beyond array boundaries. In such case, manually check which page the first misdetection happened at, and restart the script from there, but with a slightly modified --matching_threshold. For example, a very small missed separator requires a lower threshold. So you can try 0.39. Do not restart the script from page 1 so that you don't get different errors in the early pages.

After manually verifying lines and aya regions, it is time to generate region files for each screen resolution in a format that is compatible with Android, iOS and Windows.

./sqlite_encoder.py \
  --input_path /svg/output/segments \
  --output_path /svg/output/encoded \
  --reference_width 800 \
  --recitation_id $RECITATION_ID \
  --update_previous_recitation

Where:

• --input_path is the path to input folder containing segmented data SQL files to import
• --output_path is the path to output folder to generate platform specific files into
• --reference_width is the reference width of which segmented data SQL files were generated (the same one that you used in step 1)
• --recitation_id is the recitation ID of the segmented data (check recitations.csv for the complete list)
• --update_previous_recitation should be added if this is an update (see below)

Now it is time to generate the archives that will be uploaded to the cloud. Each archive is a zip file containing encrypted images plus the regions file. A separate archive is generated for each screen resolution.

./prepare_archives.sh \
  10 \
  /svg \
  /svg/output/encoded \
  /svg/output/images \
  /svg/output/archives \
  $RECITATION_ID 1

Where:

• 10 is the padding to add to images (same as you used in step 1)
• /svg is the input folder (mounted by docker)
• /svg/output/encoded is the input folder containing generated region files from the previous step
• /svg/output/images is the output folder to store resulting images
• /svg/output/archives is the output folder to store resulting archives
• $RECITATION_ID is the recitation ID
• 1 should be only added if this is an update (see below)

IMPORTANT: For this script to run, you must supply 2 environment variables for encryption to work. These must match the keys used inside the app to decode the images. They are namely:

• ENCRYPTION_KEY: Encryption Key
• ENCRYPTION_IV: Initialization Vector

These are passed in the --env-file parameter above.

The final step is to upload the generated archives to the cloud:

./upload_archives.py \
  --input_path /svg/output/archives \
  --aws_region_name ams3 \
  --aws_s3_endpoint_url https://ams3.digitaloceanspaces.com \
  --aws_s3_public_base_url https://elmohafez-app-data.ams3.digitaloceanspaces.com \
  --aws_s3_bucket elmohafez-app-data \
  --aws_s3_object_prefix recitations/

Where:

• --input_path is the path to input folder containing archives to upload to S3
• --aws_region_name is the AWS region name
• --aws_s3_endpoint_url is the AWS S3 endpoint URL, if different from the default (e.g. DigitalOcean)
• --aws_s3_public_base_url is the public URL prefix to verify uploaded archives
• --aws_s3_bucket is the AWS S3 Bucket
• --aws_s3_object_prefix is the AWS S3 object prefix (parent folder)

IMPORTANT: For this script to run, you must supply 2 environment variables for authentication. They are namely:

• AWS_ACCESS_KEY_ID
• AWS_SECRET_ACCESS_KEY

These are passed in the --env-file parameter above.

• Edit ElMohafez/sources/recitations.csv to enable the recitation and to set its mediaType to 1 (images). If this is an update, and there is a new archive that should be downloaded, increase the value in column dataLatestVersion by 1.
• Add /svg/output/encoded/RecitationData<ID>.tsv to the project under ElMohafez/sources/. If this is an update, replace that file with the new one, if changed.
• Add a new dictionary to ElMohafez/sources/Seed.plist to refer to the newly added file under the dictionary RecitationsData. If this is an update with a new tsv file, edit the dictionary by renaming the last string from RecitationData<ID>Seeded to RecitationsData<ID>-<UID>Seeded where <UID> is an increment by one for every update (e.g. 1, 2, ...)
• Increase the app bundle version to trigger a CoreData migration.

• Add an SQL script to update rewaya table so that you accomplish the following
  • Enable the new recitation if it was was not (enabled=1)
  • Change mediaType of the new recantation to image mode (mediaType=1)
  • Increment recitation version if an update is available (data_latest_version = <NEW_VERSION>). For example: UPDATE Rewaya SET enabled = 1, mediaType = 1 WHERE rewayaId = 3. Updates: UPDATE Rewaya SET data_latest_version = 1 WHERE rewayaId = 3.
• Save the above script in a file with name mohafez/src/main/assets/upgrade_script{VERSION}.txt where {VERSION} is the database version in new app release.
• Increment the constant DATABASE_VERSION in the class mohafez/src/main/java/net/hammady/android/mohafez/databse/DataBaseAccess.java to be the same as {VERSION}`. All new changes should be in one script file suffixed with the version number. So, if you have any other changes to database in the same release then it should be written in the same file and database version and no need to put a separate file and increment database version twice.
• Follow the regular release steps by editing apps version names and numbers in build script and run gradle custom build to generate the required APKs.

• Add Recitation Steps:

  • Add SQL script to Mohafez\Mohafez.Shared\Assets\UpgradeScripts with name upgrade<Increment_Number> .
  • Add SQL statements like (insert into rewaya (enabled, origin_id, rewayaId, name, name_en, mediaType) values(1, 3, 37, 'حفص عن عاصم (تجويد)', 'Hafss an Assem (Tajweed)', 1);).
  • Make sure that you set (enabled,mediaType) fields as (enabled=1 ,mediaType=1).
  • Open project using visual studio 2015 then open 'Mohafez\Mohafez.Windows\Package.appxmanifest' from Packaging tab increment database version:Major:Minor:Build:Revision.
  • Also open 'Mohafez\Mohafez.WindowsPhone\Package.appxmanifest' from Packaging tab increment database version:
    Major:Minor:Build:Revision .

• Updating Recitation Steps:

  • Add SQL script to 'Mohafez\Mohafez.Shared\Assets\UpgradeScripts' with name upgrade<Increment_Number> .
  • Add SQL statements like (UPDATE rewaya SET enabled='1', mediaType='1',data_latest_version = 1 WHERE rewayaId in (13,15,16,21,22,20,24,23,18,29);).
  • Make sure that you set (enabled,mediaType,data_latest_version) fields as (enabled=1 ,mediaType=1,data_latest_version = <Increment_Number>).
  • Open project using visual studio 2015 then open 'Mohafez\Mohafez.Windows\Package.appxmanifest' from Packaging tab increment database version:Major:Minor:Build:Revision .
  • Also open 'Mohafez\Mohafez.WindowsPhone\Package.appxmanifest' from Packaging tab increment database version:
    Major:Minor:Build:Revision .

TODO do image diff and sql diff to identify changes alone.

Any updates to a recitation must contain all the previous updates happened to the original archive. So if there are 3 updates to apply, the update archive must contain all the changed pages in all the 3 updates.

You simply mount the new SVG folder with the changed pages only and do all the steps as above with a few exceptions:

1. Add --update_previous_recitation to the ./sqlite_encoder command. This will look for a previously generated tsv file in the input path. You need to copy it there before running the command. Make sure you copy the latest version of this file, either from the original recitation, or from the latest update to the recitation.

2. Add 1 at the end of ./prepare_archives.sh which denotes that a patch archive is needed. The difference is that the final archive file name is suffixed with _patch and the data file inside is named data_patch.txt rather than data.txt.

You also need to copy any changed files from the First Run to the original run (the whole SVGs) and repeat all the steps to upload a modified archive.

Sometimes it is faster to do similar recitations in parallel, then revise them at the same time. You can use the below script for this purpose. It can be also used to compare updated recitations with their original images.

docker run -it --rm \
  -v $PWD/output/MHFZ_WRDN/output/ayat:/path1 \
  -v $PWD/output/MHFZ_GMAZ/output/ayat:/path2 \
  -v $PWD/output/DIFF_WRDN_GMAZ:/path3 \
  elmohafez/ayah-detection:latest \
    ./compare-2-outputs.py \
      --input_path1 /path1 \
      --input_path2 /path2 \
      --output_path /path3

This compares images in input folders $PWD/output/MHFZ_WRDN/output/ayat and $PWD/output/MHFZ_GMAZ/output/ayat. When the script finishes, review the images generated in $PWD/output/DIFF_WRDN_GMAZ.

MIT

This is based on Quran Utilities from quran organizatoin.