
Recherche avancée
Médias (3)
-
Valkaama DVD Cover Outside
4 octobre 2011, par
Mis à jour : Octobre 2011
Langue : English
Type : Image
-
Valkaama DVD Label
4 octobre 2011, par
Mis à jour : Février 2013
Langue : English
Type : Image
-
Valkaama DVD Cover Inside
4 octobre 2011, par
Mis à jour : Octobre 2011
Langue : English
Type : Image
Autres articles (83)
-
MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
MediaSPIP version 0.1 Beta
16 avril 2011, parMediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...) -
Personnaliser en ajoutant son logo, sa bannière ou son image de fond
5 septembre 2013, parCertains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;
Sur d’autres sites (13851)
-
Error in Splitting Educational Videos into Segments Using Python (ffmpeg issue) [closed]
28 décembre 2024, par Yahia Mohamed HanbalI created a Python project to split long educational videos into smaller segments, each focused on a single question. The program uses OCR to detect text on video frames, identifies the word "Question," extracts the number following it, and splits the video whenever the number increases.


here is the video i am tring to split ((video))


Here’s an example of the program’s output :


Video loaded: 14071 frames at 60 FPS, duration: 234.52s 
Frame 480, Time 8.00s, Question: 6 
... 
Frame 12360, Time 206.00s, Question: 7 
Creating segment 1: 8.00s to 206.00s 
Error: module 'ffmpeg' has no attribute 'Error'



I’ve shared the full code in a GitHub repository for reference : Automated Video Scene Cutting.


What the Program Does


- 

- Input : A long educational video.
- Processing :

- 

- Detects text in each frame using OCR.
- Searches for the word "Question" followed by a number.
- Monitors when the number increases to identify segment boundaries.








- Output : Creates video segments corresponding to individual questions.








The Problem


The program detects the questions and timestamps correctly, but when it tries to create the segments, I encounter the following error :


Error: module 'ffmpeg' has no attribute 'Error'



What I’ve Tried


- 

- Verified the
ffmpeg-python
library is installed (pip show ffmpeg-python
confirms the installation). - Ensured the
ffmpeg
binary is accessible from the command line. - Reviewed the library documentation to ensure the correct usage of
ffmpeg
. - Tested with different video files to rule out input-specific issues.










Environment Details


- 

- OS : Windows 11
- Python Version : 3.9.13
- Key Libraries :
ffmpeg-python








If anyone has insights into resolving this issue or suggestions for alternative approaches to handle this use case, I’d greatly appreciate your help.


Thank you !


-
build : Fine-grained link-time dependency settings
22 janvier 2017, par Diego Biurrunbuild : Fine-grained link-time dependency settings
Previously, all link-time dependencies were added for all libraries,
resulting in bogus link-time dependencies since not all dependencies
are shared across libraries. Also, in some cases like libavutil, not
all dependencies were taken into account, resulting in some cases of
underlinking.To address all this mess a machinery is added for tracking which
dependency belongs to which library component and then leveraged
to determine correct dependencies for all individual libraries. -
lavfi : add a new filtergraph parsing API
16 janvier 2023, par Anton Khirnovlavfi : add a new filtergraph parsing API
Callers currently have two ways of adding filters to a graph - they can
eithercreate, initialize, and link them manually
use one of the avfilter_graph_parse*() functions, which take a
(typically end-user-written) string, split it into individual filter
definitions+options, then create filters, apply options, initialize
filters, and finally link them - all based on information from this
string.A major problem with the second approach is that it performs many
actions as a single atomic unit, leaving the caller no space to
intervene in between. Such intervention would be useful e.g. tomodify filter options ;
supply hardware device contexts ;
both of which typically must be done before the filter is initialized.Callers who need such intervention are then forced to invent their own
filtergraph parsing, which is clearly suboptimal.This commit aims to address this problem by adding a new modular
filtergraph parsing API. It adds a new avfilter_graph_segment_parse()
function to parse a string filtergraph description into an intermediate
tree-like representation (AVFilterGraphSegment and its children).This intermediate form may then be applied step by step using further
new avfilter_graph_segment*() functions, with user intervention possible
between each step.