A Python script that creates subtitles of a given length from text paragraphs that can be easily imported into any Video Editing software such as FinalCut Pro for further adjustments.

Overview

Text to Subtitles - Python

main2

This python file creates subtitles of a given length from text paragraphs that can be easily imported into any Video Editing software such as FinalCut Pro for further adjustments.

1. Table of Contents

2. Description

2.1 Problem

In a fast-paced TV, Film, and Video production environment Video Editors are often faced with the task to create subtitles quickly and efficiently. They will often have a script that they manually into Video Editing software, one subtitle at a time, then adjust the timing.

In the case of Documentary films or long interviews, the number of subtitles can be overwhelming. In addition, there can be multiple subtitles in different languages.

2.2 Solution

Instead of manually typing the text in Video Editing Software or copy-pasting it from a text file one subtitle at a time this python script automatically converts text paragraphs, located in a text file into a standard .srt subtitle file. It can be then imported into any Video Editing Software.

The script creates subtitles of the same length, such as 3 seconds. Therefore, manual adjustments are still needed after importing the subtitles. Nevertheless, this workflow has proven to be much faster than the full manual process described above.

Input:

Call me Ishmael.

Some years ago,
never mind how long precisely,

having little or no money in my purse,
and nothing particular

Output:

1
00:00:00,000 --> 0:00:03,000
Call me Ishmael.

2
00:00:03,000 --> 0:00:06,000
Some years ago,
never mind how long precisely,

3
00:00:06,000 --> 0:00:09,000
having little or no money in my purse,
and nothing particular

2.3 Motivation behind the project

I first created this workflow when I was Directing and Video Editing TV mini-series. Since deadlines were extremely tight I was looking at every opportunity to speed up the delivery times while maintaining high quality. I later used it for commercial Videography projects. This solution fits my workflow very well and has proven to be very useful.

2.4 Development history

It was originally built simply by using a stack of regular expressions executed in the TextSoap.app along with some operations in Excel and manula copy-pasting. Later most of the steps were combined in a single Python script that is presented here.

3. Technologies Used

  • Python 3.9.4, compatible with Python 2.7 and above
  • datetime integrated module to work with date and time
  • re integrated regular expression operations module
  • os a portable way of using operating system dependent functionality

4. Installation

Download text_to_video_subtitles.py file from this GitHub repository.

5. Usage

5.1 Prepare .txt file

Take existing script or type it from scratch. Then manually split it into paragraphs in the following format:

Call me Ishmael.

Some years ago,
never mind how long precisely,

having little or no money in my purse,
and nothing particular
  • A single line represents a single line in a subtitle.
  • Empty line defines where one subtitle ends and a new one begins.
  • Normally one subtitle has one or two lines, but it can have more.

5.2 Rename and move .txt file

Paste the text into a text editor, then save it as subtitles.txt, and move the file into the same folder with text_to_subtitles.py.

5.3 Launch Python script

Open Terminal.app. Type python, add space, then drag and drop text_to_video_markers.py and press Return.

run python script with terminal

Alternatively, you can install the latest version of Python. Then right-click on text_to_video_markers.py file and choose Open with -> Python Launcher.app.

open python file with python launcher

Either method will run the script and create subtitles.srt file in the same folder.

5.4 Open subtitles.srt with FinalCut Pro

In FinalCut Pro choose File -> Import -> Captions..., then navigate to newly created subtitles.srt and select Import. This will import subtitles into an existing project. They will be visible in Timeline, Index (Captions), and Viewer. You can now easily adjust individual subtitles in Timeline and edit the text in Timeline and Inspector.

That's it! We have just automatically converted text with paragraphs into a universal .srt subtitle file for further adjustments and manipulations in Video editing software such as FinalCut Pro..

finalcut pro markers imported from text

6. Project Status

The project is: complete I am no longer working on it since I am not working for TV any longer. But if you have some ideas or want me to modify something contact me and we should be able to collaborate.

7. Known Limitations

  • An input text file must be named subtitles.txt
  • Text in subtitles.txt** file must be split into paragraphs.
  • Both text_to_subtitles.py and subtitles.txt must be located in the same folder.
  • The default subtitle length is 3 seconds and can only be changed inside text_to_subtitles.py code by changing the number in dursec = 3 statement.

8. Room for Improvement

  • Testing and logging the issues.
  • Making python script an executable file.
  • Developing GUI to be able to specify .txt and .fcpxml input files with any name and location.
  • Building a web app.

9. License

This project is open-source and available under the GNU General Public License v3.0

10. Contact

Created by @DmytroNorth - feel free to contact me at [email protected]!

Owner
Dmytro North
Dmytro North
CondenseNet: Light weighted CNN for mobile devices

CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua

Shichen Liu 690 Nov 30, 2022
This is an official implementation for "Video Swin Transformers".

Video Swin Transformer By Ze Liu*, Jia Ning*, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin and Han Hu. This repo is the official implementation of "V

Swin Transformer 981 Jan 03, 2023
Rethinking Transformer-based Set Prediction for Object Detection

Rethinking Transformer-based Set Prediction for Object Detection Here are the code for the ICCV paper. The code is adapted from Detectron2 and AdelaiD

Zhiqing Sun 62 Dec 03, 2022
The Video-based Accident Detection System built in Python

Accident-detection-system About the Project This Repository contains the Video-based Accident Detection System built in Python. Contributors Yukta Gop

SURYAVANSHI SNEHAL BALKRISHNA 50 Dec 07, 2022
A PyTorch-based Semi-Supervised Learning (SSL) Codebase for Pixel-wise (Pixel) Vision Tasks

PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the

Zhanghan Ke 255 Dec 11, 2022
Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.

VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks. VMAgent is constructed based on one month r

56 Dec 12, 2022
Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection, CVPR 2021. Installation A Linux pla

Tianning Yuan 269 Dec 21, 2022
PyTorch implementation of SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I

Jason Ma 14 Aug 30, 2022
Code for the paper "Graph Attention Tracking". (CVPR2021)

SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r

122 Dec 24, 2022
Codes and Data Processing Files for our paper.

Code Scripts and Processing Files for EEG Sleep Staging Paper 1. Folder Tree ./src_preprocess (data preprocessing files for SHHS and Sleep EDF) sleepE

Chaoqi Yang 18 Dec 12, 2022
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Hongje Seong 72 Dec 14, 2022
Code-free deep segmentation for computational pathology

NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation

André Pedersen 26 Nov 23, 2022
Huawei Hackathon 2021 - Sweden (Stockholm)

huawei-hackathon-2021 Contributors DrakeAxelrod Challenge Requirements: python=3.8.10 Standard libraries (no importing) Important factors: Data depend

Drake Axelrod 32 Nov 08, 2022
Yolo object detection - Yolo object detection with python

How to run download required files make build_image make download Docker versio

3 Jan 26, 2022
RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020)

RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020) Hong Wang, Qi Xie, Qian Zhao, and Deyu Meng [PDF] [Supplementary M

Hong Wang 6 Sep 27, 2022
A parametric soroban written with CADQuery.

A parametric soroban written in CADQuery The purpose of this project is to demonstrate how "code CAD" can be intuitive to learn. See soroban.py for a

Lee 4 Aug 13, 2022
Convolutional Neural Network for Text Classification in Tensorflow

This code belongs to the "Implementing a CNN for Text Classification in Tensorflow" blog post. It is slightly simplified implementation of Kim's Convo

Denny Britz 5.5k Jan 02, 2023
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap

Cameron Davidson-Pilon 25.1k Jan 02, 2023
Only valid pull requests will be allowed. Use python only and readme changes will not be accepted.

❌ This repo is excluded from hacktoberfest This repo is for python beginners and contains lot of beginner python projects for practice. You can also s

Prajjwal Pathak 50 Dec 28, 2022