使用深度学习框架提取视频硬字幕;docker容器免安装深度学习库,使用本地api接口使得界面和后端识别分离;

Overview

extract-video-subtittle

使用深度学习框架提取视频硬字幕;

本地识别无需联网;

CPU识别速度可观;

容器提供API接口;

运行环境

本项目运行环境非常好搭建,我做好了docker容器免安装各种深度学习包;

提供windows界面操作;

容器为CPU版本;

视频演示

https://www.bilibili.com/video/BV18Q4y1f774/

程序说明

1、先启动后端容器实例

docker run -d -p 6666:6666 m986883511/extract_subtitles

image-20210801214757813

2、启动程序

简单介绍页面

1:点击左边按钮连接第一步启动的容器;

2:视频提取字幕的总进度

3:当前视频帧显示的位置,就是视频进度条

4:识别出来的文字会在这里显示一下

image-20210801215010179

image-20210801215258761

3、点击选择视频确认字幕位置

点击选择视频按钮,这时你可以拖动进度条到有字幕的位置;然后点击选择字幕区域;在视频中画一个矩形;

image-20210801215258761

4、点击测试连接API

image-20210801220206554

后端没问题的话,会显示已连通;此时所有步骤准备就绪

5、开始识别

点击请先完成前几步按钮,内部分为这几个步骤

  1. 本地通过ffmpeg提取视频声音保存到temp目录(0%-10%)
  2. api通信将声音文件发送到容器内,容器内spleeter库提取声音中人声,结果保存在容器内temp目录,很耗时间,吃CPU和内存(10%-30)
  3. api通信,将人声根据停顿分片,返回分片结果,耗较短的时间(30%-40%)
  4. 根据说话分片时间开始识别字幕(40-%100%)

当100%的时候查看temp目录就生成了和视频同名的srt字幕文件

运行后台

后端接口容器地址Docker Hub

此过程可能时间较长,您需要预先安装好好docker,并配置好docker加速器,你可能需要先docker login

docker run -d -p 6666:6666 m986883511/extract_subtitles

本项目缺少文件

因网速墙的问题,大文件推送不上去,可以参考.gitignore中写的

其他

视频提取

# 视频片段提取
ffmpeg -ss 00:15:45 -t 00:02:15 -i test/three_body_3_7.mp4 -vcodec copy -acodec copy test/3body.mp4
# 打包界面程序
C:/Python/Python38-32/Scripts/pyinstaller.exe main.spec

参考资料

本项目中深度学习源代码为/docker/backend

原作者为:https://github.com/YaoFANGUK/video-subtitle-extractor

You might also like...
Comments
  • 提取人声一直没结果

    提取人声一直没结果

    image 视频是40多分钟的连续剧。CPU版本。之前用YaoFANGUK/video-subtitle-extractor提取字幕很成功也准确,但时间比较长。看到作者用音频分析减少了识别的帧数,所以试了一下。但在提取人声时,已经等待了近50分钟没有结果。而且CPU的占用只有1%左右,这明显不正常。用YaoFANGUK/video-subtitle-extractor整个的耗时可能都没有这么久。另外autosub也是提取音频来语音识别字幕,识别人声也很快,同样的视频几分钟就完了。麻烦作者看看是出了什么问题呢。

    opened by royzengyi 2
  • 项目咨询

    项目咨询

    Hello,我尝试了一下这个软件,感觉还是不错的,不过在实际使用中还是会有不少问题。

    我是一个独立开发者,这边愿意付费或者合作来完善一下,让这个项目更具实用性,不知道你有没有兴趣呢?

    没有找到联系方式,只好通过issue来试一下,你可以在看到之后删除,谢谢。

    我的邮箱是yedaxia#foxmail.com

    opened by YeDaxia 1
Releases(0.2.0)
Owner
歌者
失去人性,失去很多;失去兽性,失去一切;活着才能燃烧自己。
歌者
TUPÃ was developed to analyze electric field properties in molecular simulations

TUPÃ: Electric field analyses for molecular simulations What is TUPÃ? TUPÃ (pronounced as tu-pan) is a python algorithm that employs MDAnalysis engine

Marcelo D. Polêto 10 Jul 17, 2022
Source Code For Template-Based Named Entity Recognition Using BART

Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h

174 Dec 19, 2022
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Ryuichi Yamamoto 1.8k Jan 08, 2023
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

keven 198 Dec 20, 2022
Source Code for DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances (https://arxiv.org/pdf/2012.01775.pdf)

DialogBERT This is a PyTorch implementation of the DialogBERT model described in DialogBERT: Neural Response Generation via Hierarchical BERT with Dis

Xiaodong Gu 67 Jan 06, 2023
An open-source, low-cost, image-based weed detection device for fallow scenarios.

Welcome to the OpenWeedLocator (OWL) project, an opensource hardware and software green-on-brown weed detector that uses entirely off-the-shelf compon

Guy Coleman 145 Jan 05, 2023
Accelerated deep learning R&D

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

Catalyst-Team 3.1k Jan 06, 2023
Easy to use Audio Tagging in PyTorch

Audio Classification, Tagging & Sound Event Detection in PyTorch Progress: Fine-tune on audio classification Fine-tune on audio tagging Fine-tune on s

sithu3 15 Dec 22, 2022
🤖 A Python library for learning and evaluating knowledge graph embeddings

PyKEEN PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-m

PyKEEN 1.1k Jan 09, 2023
Norm-based Analysis of Transformer

Norm-based Analysis of Transformer Implementations for 2 papers introducing to analyze Transformers using vector norms: Kobayashi+'20 Attention is Not

Goro Kobayashi 52 Dec 05, 2022
Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Transformer Quantization This repository contains the implementation and experiments for the paper presented in Yelysei Bondarenko1, Markus Nagel1, Ti

83 Dec 30, 2022
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.

Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu

Florian 40 Dec 09, 2022
Code for “ACE-HGNN: Adaptive Curvature ExplorationHyperbolic Graph Neural Network”

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network This repository is the implementation of ACE-HGNN in PyTorch. Environment pyt

9 Nov 28, 2022
This is the repo of the manuscript "Dual-branch Attention-In-Attention Transformer for speech enhancement"

DB-AIAT: A Dual-branch attention-in-attention transformer for single-channel SE

Guochen Yu 68 Dec 16, 2022
[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

GenForce: May Generative Force Be with You 93 Dec 25, 2022
Manipulation OpenAI Gym environments to simulate robots at the STARS lab

Manipulator Learning This repository contains a set of manipulation environments that are compatible with OpenAI Gym and simulated in pybullet. In par

STARS Laboratory 5 Dec 08, 2022
[ICCV 2021] Released code for Causal Attention for Unbiased Visual Recognition

CaaM This repo contains the codes of training our CaaM on NICO/ImageNet9 dataset. Due to my recent limited bandwidth, this codebase is still messy, wh

Wang Tan 66 Dec 31, 2022
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li

DV Lab 137 Dec 14, 2022
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang 1.2k Dec 29, 2022