mirror of
https://github.com/stronk-dev/Guitar-Sheet-Parser.git
synced 2025-07-05 08:25:09 +02:00
e32d66c10b
Added input for rawtxt (speedy input, but with assumptions, so it has to be generated by this program Fix check for selected input extensions
93 lines
3.9 KiB
Python
93 lines
3.9 KiB
Python
#!/usr/bin/env python3
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##
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# @file main.py
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#
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# @brief This program converts supported tablature source files to a printable format
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#
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# @section description Description
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# Creates Song objects of all tablatures it can find in a given directory or its subdirectories
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# Supported inputs currently: Any .txt file, as long as each section has a corresponding [<sectionName>] delimiter
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# Supported outputs currently: PNG format
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# Song objects are then parsed into separate metadata information and sections
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# Sections contain lines of lyric and corresponding tablature data
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# The program then tries to fit these sections within the chosen output dimensions (currently A4)
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# as best as it can, shrinking or growing sections to fit the remaining space
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#
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# @section notes Notes
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# - Splitting raw text into lyric and tablature info is very basic at the moment.
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# We need a better way to classify & split the various channels (raw tab, lyrics, chords, more?) that can be expected in tablature
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#
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# @section todo TODO
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# - Various prints should be printed at specific log levels, to easily switch between debug, info or warnings only
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import lib.chordFinder
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import lib.dataStructures
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import lib.initSongs
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import lib.transpose
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import lib.config
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import output2img
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import output2txt
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def main():
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# Init config file
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lib.config.initConfig()
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# Init Song objects for all songs with compatible inputs
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songs = lib.initSongs.getSongObjects()
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# Get what programs we are going to run
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configObj = lib.config.config['options']
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exportToImg = configObj['exporttoimg']
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exportToTxt = configObj['exporttotxt']
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exportToRaw = configObj['exporttoraw']
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# Convert all songs into sections
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for song in songs:
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print("Start parsing of file '{}'...".format(song.inputFile))
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# Initialise internal data structures
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print("song file extension {}".format(song.fileExtension))
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if song.fileExtension == 'txt':
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song.initSections()
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elif song.fileExtension == 'rawtxt':
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song.initPreprocessed()
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else:
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print("File extension '{}' not supported. Skipping...".format(song.fileExtension))
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continue
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# If input is .raw output. If output to raw is set, overwrite itself
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# ready quickly using rules
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if not song.isParsed:
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print("Song was not initialized correctly. Skipping...")
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continue
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if exportToTxt:
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# Create subdirectory where we will output our images
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targetDirectory = song.outputLocation + "-txt"
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print("Successfully parsed file. Writing output to '{}'\n".format(targetDirectory))
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# Write out metadata and sections, as many as can fit on one page
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output2txt.outputToTxt(targetDirectory, False, song)
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if exportToRaw:
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# Create subdirectory where we will output our images
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targetDirectory = song.outputLocation + "-txt"
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print("Successfully parsed file. Writing output to '{}'\n".format(targetDirectory))
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# Write out metadata and sections, as many as can fit on one page
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output2txt.outputToTxt(targetDirectory, True, song)
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if exportToImg:
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# Fit all sections on each page, resizes down if it does not fit on width
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song.fitSectionsByWidth()
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# Prerender: calculate Pages, and move sections into Pages
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song.sectionsToPages()
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# Optimalisation: try to fill whitespace
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while song.canFillWhitespace():
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print("Resizing down to fit whitespace more efficiently")
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song.resizeAllSections(-1)
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song.sectionsToPages()
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# Optimalisation: increase font size as long as the amount of pages does not increase or we cause an overflow on width
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song.increaseWhileSameAmountOfPages()
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# Parse as PNG a4
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# Create subdirectory where we will output our images
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targetDirectory = song.outputLocation + "-a4-png"
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print("Successfully parsed file. Writing output to '{}'\n".format(targetDirectory))
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# Write out metadata and sections, as many as can fit on one page
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output2img.outputToImage(targetDirectory, song)
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if __name__ == "__main__":
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main()
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