ttconv (Timed Text Conversion)

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Introduction

ttconv is a library and command line application written in pure Python for converting between timed text formats used in the presentations of captions, subtitles, karaoke, etc.

TTML / IMSC ---                         --- IMSC / TTML
                \                     /
SCC / CEA 608 ----- Canonical Model -------- WebVTT
                /                     \
EBU STL -------                         --- SRT
              /
SRT ---------

ttconv works by mapping the input document, whatever its format, into an internal canonical model, which is then mapped to the format of the output document is derived. The canonical model closely follows the TTML 2 data model, as constrained by the IMSC 1.1 Text Profile specification.

Online demo

https://ttconv.sandflow.com/

Format support

ttconv currently supports the following input and output formats. Additional input and output formats are planned, and suggestions/contributions are welcome.

Input Formats

• CEA 608/.scc
• IMSC 1.1 Text Profile/.ttml
• EBU STL
• SubRip/.srt

Output Formats

• SubRip/.srt
• IMSC 1.1 Text Profile/.ttml
• WebVTT

Quick start

To install the latest version of ttconv, including pre-releases:

pip install --pre ttconv

tt convert -i <input .scc file> -o <output .ttml file>

Documentation

Command line

tt convert [-h] -i INPUT -o OUTPUT [--itype ITYPE] [--otype OTYPE] [--config CONFIG] [--config_file CONFIG_FILE]

• --itype: TTML | SCC | STL | SRT (extrapolated from the filename, if omitted)
• --otype: TTML | SRT | VTT (extrapolated from the filename, if omitted)
• --config and --config_file: JSON dictionaries with the following members:
  • "general": JSON object: General configuration options (see below)
  • "imsc_writer": JSON object: IMSC Writer configuration options (see below)
  • "stl_reader": JSON object: STL Reader configuration options (see below)
  • "vtt_writer": JSON object: WebVTT Writer configuration options (see below)

Example:

tt convert -i <.scc file> -o <.ttml file> --itype SCC --otype TTML --config '{"general": {"progress_bar":false, "log_level":"WARN"}}'

General configuration

progress_bar

"progress_bar": true | false

A progress bar is displayed if progress_bar is true and log_level is "INFO".

Default: true

log_level

"log_level": "INFO" | "WARN" | "ERROR"

Logging verbosity

Default: "INFO"

document_lang

"document_lang": <RFC 5646 language tag>

Overrides the top-level language of the input document.

Example: "document_lang": "es-419"

Default: None

IMSC Writer configuration

time_format

"time_format": "frames" | "clock_time" | "clock_time_with_frames"

Specifies whether the TTML time expressions are in frames (f), HH:MM:SS.mmm or HH:MM:SS:FF

Default: "frames" if "fps" is specified, "clock_time" otherwise

fps

"fps": "<num>/<denom>"

Specifies the ttp:frameRate and ttp:frameRateMultiplier of the output document.

Required when time_format is frames or clock_time_with_frames. No effect otherwise.

Example:

--config '{"general": {"progress_bar":false, "log_level":"WARN"}, "imsc_writer": {"time_format":"clock_time_with_frames", "fps": "25/1"}}'

STL Reader configuration

disable_fill_line_gap

"disable_fill_line_gap" : true | false

true means that the STL reader does not fill gaps between lines

Default: false

disable_line_padding

"disable_line_padding" : true | false

true means that the STL reader does not add padding at the begining/end of lines

Default: false

program_start_tc

"program_start_tc" : "TCP" | "HH:MM:SS:FF"

Specifies a starting offset, either the TCP field of the GSI block or a user-specified timecode

Default: "00:00:00:00"

font_stack

"font_stack" : [<font-families>](https://www.w3.org/TR/ttml2/#style-value-font-families)

Overrides the font stack

Default: "Verdana, Arial, Tiresias, sansSerif"

ax_row_count

"max_row_count" : "MNR" | integer

Specifies a maximum number of rows for open subtitles, either the MNR field of the GSI block or a user-specified value

Default: 23

VTT Writer configuration

line_position

"line_position" : true | false

true means that the VTT writer outputs line and line alignment cue settings

Default: false

Library

The overall architecture of the library is as follows:

• Reader modules validate and convert input files into instances of the canonical model (see ttconv.imsc.reader.to_model() for example);
• Filter modules transform instances of the canonical data model, e.g. all text styling and positioning might be removed from an instance of the canonical model to match the limited capabilities of downstream devices; and
• Writer modules convert instances of the canonical data model into output files.

Processing shared across multiple reader and writer modules is factored out in common modules whenever possible. For example, several output formats require an instance of the canonical data model to be transformed into a sequence of discrete temporal snapshots – a process called ISD generation.

The library uses the Python logging module to report non-fatal events.

Unit tests illustrate the use of the library, e.g. ReaderWriterTest.test_imsc_1_test_suite at src/test/python/test_imsc_writer.py.

Detailed documentation including reference documents is under doc.

Dependencies

Runtime

• python >= 3.7

Development

The project uses pipenv to manage dependencies.

• pylint
• coverage

Development

Setup

Local

• run pipenv install --dev
• set the PYTHONPATH environment variable to src/main/python, e.g. export PYTHONPATH=src/main/python
• pipenv run can then be used

Docker

docker build --rm -f Dockerfile -t ttconv:latest .
docker run -it --rm ttconv:latest bash

Example

From the root directory of the project:

mkdir build
pipenv install --dev
export PYTHONPATH=src/main/python
python src/main/python/ttconv/tt.py convert -i src/test/resources/scc/mix-rows-roll-up.scc -o build/mix-rows-roll-up.ttml

Code coverage

Unit test code coverage is provided by the script at scripts/coverage.sh

Continuous integration

Overview

Automated testing is provided by the script at scripts/ci.sh

Local

Run ./scripts/ci.sh

GitHub actions

See .github/workflows/main.yml

Docker

Run docker run -it --rm ttconv:latest /bin/sh scripts/ci.sh