sheatless 1.4.0

A python library for extracting parts from sheetmusic pdfs

sheatless - A python library for extracting parts from sheetmusic pdfs

Sheatless, a tool for The Beatless to become sheetless. Written and managed by the web-committee in the student orchestra The Beatless. Soon to be integrated in taktlaus.no.

API

PdfPredictor

class PdfPredictor():
	def __init__(
        self,
        pdf : BytesIO | bytes,
        instruments=None,
        instruments_file=None,
        instruments_file_format="yaml",
        use_lstm=False,
        tessdata_dir=None,
        log_stream=sys.stdout,
        use_multiprocessing=False,
        ):
		...
	
	def parts(self):
		for ...:
			yield  {
				"name": "<part name>",
				"instruments": ["<instrument name", ...],
				"fromPage": "<from page>",
				"toPage": "<to page>",
			}

Arguments for __init__:

• pdf - PDF file object
• instruments (optional) - Dictionary of instruments. Will override any provided instruments file.
• instruments_file (optional) - Full path to instruments file or instruments file object. Accepted extensions: .yaml, .yml, .json
• instruments_file_format (optional) - Format of instruments_file if it is a file object. Accepted formats: yaml, json
  • If neither instruments_file nor instruments is provided a default instruments file will be used.
• use_lstm (optional) - Use LSTM instead of legacy engine mode.
• tessdata_dir (optional) - Full path to tessdata directory. If not provided, whatever the environment variable TESSDATA_DIR will be used.
• log_stream (optional) - File stream log output will be sent to. Can be set to None to disable logging.
• use_multiprocessing (optional) - If set to True, detection will be performed in a separate process.

processUploadedPdf

def processUploadedPdf(pdfPath, imagesDirPath, instruments_file=None, instruments=None, use_lstm=False, tessdata_dir=None):
    ...
	return parts, instrumentsDefaultParts

which will be available with

from sheatless import processUploadedPdf

Arguments description here:

Argument	Optional	Description
pdfPath		Full path to PDF file.
imagesDirPath		Full path to output images.
instruments_file	(optional)	Full path to instruments file. Accepted formats: YAML (.yaml, .yml), JSON (.json).
instruments	(optional)	Dictionary of instruments. Will override any provided instruments file.
		If neither instruments_file nor instruments is provided a default instruments file will be used.
use_lstm	(optional)	Use LSTM instead of legacy engine mode.
tessdata_dir	(optional)	Full path to tessdata directory. If not provided, whatever the environment variable TESSDATA_DIR will be used.

Returns description here:

Return	Description
parts	A list of dictionaries { "name": "name", "instruments": ["instrument 1", "instrument 2"...] "fromPage": i, "toPage": j } describing each part
instrumentsDefaultParts	A dictionary { ..., "instrument_i": j, ... }, where j is the index in the parts list for the default part for instrument_i.

predict_parts_in_pdf

def predict_parts_in_pdf(
	pdf : BytesIO | bytes,
	instruments=None,
	instruments_file=None,
	instruments_file_format="yaml",
	use_lstm=False,
	tessdata_dir=None,
	):
    ...
    return parts, instrumentsDefaultParts

Arguments:

• pdf - PDF file object
• instruments (optional) - Dictionary of instruments. Will override any provided instruments file.
• instruments_file (optional) - Full path to instruments file or instruments file object. Accepted extensions: .yaml, .yml, .json
• instruments_file_format (optional) - Format of instruments_file if it is a file object. Accepted formats: yaml, json
  • If neither instruments_file nor instruments is provided a default instruments file will be used.
• use_lstm (optional) - Use LSTM instead of legacy engine mode.
• tessdata_dir (optional) - Full path to tessdata directory. If not provided, whatever the environment variable TESSDATA_DIR will be used.

Returns:

• parts - A list of dictionaries { "name": "name", "instruments": ["instrument 1", "instrument 2"...] "fromPage": i, "toPage": j } describing each part
• instrumentsDefaultParts - A dictionary { ..., "instrument_i": j, ... }, where j is the index in the parts list for the default part for instrument_i.

predict_parts_in_img

def predict_parts_in_img(img : io.BytesIO | bytes | PIL.Image.Image, instruments, use_lstm=False, tessdata_dir=None) -> typing.Tuple[list, list]:
    ...
    return partNames, instrumentses

Arguments:

• img - image object
• instruments - dictionary of instruments
• use_lstm (optional) - Use LSTM instead of legacy engine mode.
• tessdata_dir (optional) - Full path to tessdata directory. If not provided, whatever the environment variable TESSDATA_DIR will be used.

Returns:

• partNames - a list of part names
• instrumentses - a list of lists of instruments for each part

Example docker setup

Sheatless requires tesseract and poppler installed on the system to work. An example docker setup as well as integration of the library can be found in sheatless-splitter.