Recherche avancée
Autres articles (76)
-
Websites made with MediaSPIP
2 mai 2011, parThis page lists some websites based on MediaSPIP.
-
Creating farms of unique websites
13 avril 2011, parMediaSPIP platforms can be installed as a farm, with a single "core" hosted on a dedicated server and used by multiple websites.
This allows (among other things) : implementation costs to be shared between several different projects / individuals rapid deployment of multiple unique sites creation of groups of like-minded sites, making it possible to browse media in a more controlled and selective environment than the major "open" (...) -
Other interesting software
13 avril 2011, parWe don’t claim to be the only ones doing what we do ... and especially not to assert claims to be the best either ... What we do, we just try to do it well and getting better ...
The following list represents softwares that tend to be more or less as MediaSPIP or that MediaSPIP tries more or less to do the same, whatever ...
We don’t know them, we didn’t try them, but you can take a peek.
Videopress
Website : http://videopress.com/
License : GNU/GPL v2
Source code : (...)
Sur d’autres sites (7776)
-
Is it possible to "stretch" audio in the frequency domain ?
9 juillet 2024, par Christian SchmitzWe would like to make quite similar frequencies better decernible for further AI-analysis. Because of that, we would like to stretch the audio in the frequency domain. This means that instead of having two frequency bands of 30Hz and 40Hz, is it possible to "stretch" them to have maybe 28Hz and 45Hz ?


Thanks a lot and if that wasn't clear enough, please don't hesitate to ask ! :)


We tried cleaning the data with ffmpeg, but it appears that for our task we need a clearer representation of the frequencies in the data


-
Error initializing FFmpegKit : "TypeError : Cannot read property 'getLogLevel' of null" in React Native
9 janvier, par Md Monirozzaman khanI'm developing a React Native application where I need to process videos using the ffmpeg-kit-react-native library. However, I'm encountering an issue during the initialization of FFmpegKitConfig. The error message is :


ERROR Error initializing FFmpegKit: [TypeError: Cannot read property 'getLogLevel' of null]


Here is my App.js code




import React, { useState, useEffect } from 'react';
import { StyleSheet, Text, View, TouchableOpacity, Alert, Dimensions, ScrollView, LayoutAnimation, UIManager, Platform } from 'react-native';
import * as ImagePicker from 'expo-image-picker';
import * as FileSystem from 'expo-file-system';
import { Video } from 'expo-av';
import { MaterialIcons } from '@expo/vector-icons';
import { FFmpegKit, FFmpegKitConfig, ReturnCode } from 'ffmpeg-kit-react-native';

const windowWidth = Dimensions.get('window').width;

if (Platform.OS === 'android') {
 UIManager.setLayoutAnimationEnabledExperimental && UIManager.setLayoutAnimationEnabledExperimental(true);
}

export default function App() {
 const [videoFiles, setVideoFiles] = useState([]);
 const [isGridView, setIsGridView] = useState(false);
 const [isConverting, setIsConverting] = useState(false);

 useEffect(() => {
 FFmpegKitConfig.init()
 .then(() => {
 console.log('FFmpegKit initialized');
 })
 .catch((error) => {
 console.error('Error initializing FFmpegKit:', error);
 });
 }, []);

 const pickVideo = async () => {
 const { status } = await ImagePicker.requestMediaLibraryPermissionsAsync();
 if (status !== 'granted') {
 alert('Sorry, we need media library permissions to make this work!');
 return;
 }

 let result = await ImagePicker.launchImageLibraryAsync({
 mediaTypes: ImagePicker.MediaTypeOptions.Videos,
 allowsMultipleSelection: true,
 });

 if (!result.canceled && result.assets.length > 0) {
 const newFiles = result.assets.filter(
 (newFile) => !videoFiles.some((existingFile) => existingFile.uri === newFile.uri)
 );

 if (newFiles.length < result.assets.length) {
 Alert.alert('Duplicate Files', 'Some files were already added.');
 }

 LayoutAnimation.configureNext(LayoutAnimation.Presets.easeInEaseOut);
 setVideoFiles([...videoFiles, ...newFiles]);
 }
 };

 const convertVideos = async () => {
 setIsConverting(true);
 const outputDir = `${FileSystem.documentDirectory}Output`;

 const dirInfo = await FileSystem.getInfoAsync(outputDir);
 if (!dirInfo.exists) {
 await FileSystem.makeDirectoryAsync(outputDir, { intermediates: true });
 }

 for (const video of videoFiles) {
 const { uri } = video;
 const filename = uri.split('/').pop();
 const outputFilePath = `${outputDir}/${filename.split('.').slice(0, -1).join('.')}_modified.mp4`;

 const ffmpegCommand = `-y -i "${uri}" -af "atempo=1.02, bass=g=4:f=80:w=3, treble=g=4:f=3200:w=3, firequalizer=gain_entry='entry(0,0);entry(62,2);entry(125,1.5);entry(250,1);entry(500,1);entry(1000,1);entry(2000,1.5);entry(4000,2.5);entry(8000,3);entry(16000,4)', compand=attacks=0.05:decays=0.25:points=-80/-80-50/-15-30/-10-10/-2:soft-knee=4:gain=2, deesser, highpass=f=35, lowpass=f=17000, loudnorm=I=-16:LRA=11:TP=-1.5, volume=3.9dB" -c:v copy -c:a aac -b:a 224k -ar 48000 -threads 0 "${outputFilePath}"`;

 try {
 const session = await FFmpegKit.execute(ffmpegCommand);
 const returnCode = await session.getReturnCode();

 if (ReturnCode.isSuccess(returnCode)) {
 console.log(`Video converted: ${outputFilePath}`);
 } else if (ReturnCode.isCancel(returnCode)) {
 console.log('Conversion cancelled');
 } else {
 console.error(`FFmpeg process failed: ${session.getFailStackTrace()}`);
 }
 } catch (error) {
 console.error(`Error converting video: ${error.message}`);
 }
 }

 setIsConverting(false);
 Alert.alert('Conversion Complete', 'All videos have been converted.');
 };

 const deleteVideo = (uri) => {
 LayoutAnimation.configureNext(LayoutAnimation.Presets.easeInEaseOut);
 setVideoFiles(videoFiles.filter((video) => video.uri !== uri));
 };

 const clearAllVideos = () => {
 LayoutAnimation.configureNext(LayoutAnimation.Presets.easeInEaseOut);
 setVideoFiles([]);
 };

 const toggleLayout = () => {
 LayoutAnimation.configureNext(LayoutAnimation.Presets.easeInEaseOut);
 setIsGridView(!isGridView);
 };

 return (
 <view style="{styles.container}">
 <text style="{styles.header}">Video Converter App</text>
 <touchableopacity style="{styles.addButton}">
 <text style="{styles.addButtonText}">Select or Browse Videos</text>
 </touchableopacity>
 <view style="{styles.headerContainer}">
 <text style="{styles.videoCount}">Total Videos: {videoFiles.length}</text>
 {videoFiles.length > 0 && (
 <>
 <touchableopacity style="{styles.clearButtonContainer}">
 <materialicons size="{24}" color="red" style="{styles.clearIcon}"></materialicons>
 <text style="{styles.clearAllText}">Clear All</text>
 </touchableopacity>
 <touchableopacity style="{styles.toggleLayoutButton}">
 <materialicons size="{24}" color="#fff"></materialicons>
 </touchableopacity>
 >
 )}
 </view>
 {isGridView ? (
 <scrollview contentcontainerstyle="{styles.gridContainer}">
 {videoFiles.map((item, index) => (
 <view key="{index}" style="{styles.videoItemGrid}">
 
 <touchableopacity>> deleteVideo(item.uri)} style={styles.deleteButtonGrid}>
 <materialicons size="{24}" color="red"></materialicons>
 </touchableopacity>
 </view>
 ))}
 </scrollview>
 ) : (
 <view style="{styles.list}">
 {videoFiles.map((item, index) => (
 <view key="{index}" style="{styles.videoItem}">
 
 <text style="{styles.fileName}">{decodeURI(item.fileName || item.uri.split('/').pop() || 'Unknown File')}</text>
 <touchableopacity>> deleteVideo(item.uri)} style={styles.deleteButton}>
 <materialicons size="{24}" color="red"></materialicons>
 </touchableopacity>
 </view>
 ))}
 </view>
 )}
 {videoFiles.length > 0 && (
 <touchableopacity style="{styles.convertButton}" disabled="{isConverting}">
 <text style="{styles.convertButtonText}">{isConverting ? 'Converting...' : 'Convert'}</text>
 </touchableopacity>
 )}
 </view>
 );
}

const styles = StyleSheet.create({
 container: {
 flex: 1,
 backgroundColor: '#fff',
 alignItems: 'center',
 padding: 10,
 },
 header: {
 fontSize: 24,
 fontWeight: 'bold',
 marginBottom: 5,
 },
 addButton: {
 backgroundColor: '#007BFF',
 padding: 15,
 borderRadius: 10,
 alignItems: 'center',
 marginBottom: 5,
 width: '100%',
 elevation: 2,
 shadowColor: '#000',
 shadowOffset: { width: 0, height: 5 },
 shadowOpacity: 0.8,
 shadowRadius: 2,
 },
 addButtonText: {
 color: '#fff',
 fontSize: 18,
 fontWeight: 'bold',
 },
 headerContainer: {
 flexDirection: 'row',
 alignItems: 'center',
 justifyContent: 'space-between',
 width: '100%',
 marginBottom: 10,
 },
 videoCount: {
 fontSize: 18,
 },
 clearButtonContainer: {
 flexDirection: 'row',
 alignItems: 'center',
 marginRight: 10,
 },
 clearIcon: {
 marginRight: 5,
 },
 clearAllText: {
 fontSize: 16,
 color: 'red',
 textDecorationLine: 'underline',
 },
 toggleLayoutButton: {
 backgroundColor: '#007BFF',
 padding: 1,
 borderRadius: 8,
 alignItems: 'center',
 justifyContent: 'center',
 },
 list: {
 flex: 1,
 width: '100%',
 },
 videoItem: {
 padding: 5,
 borderBottomColor: '#ccc',
 borderBottomWidth: 0.7,
 flexDirection: 'row',
 alignItems: 'center',
 },
 videoItemGrid: {
 flexDirection: 'column',
 alignItems: 'center',
 margin: 4,
 borderWidth: 1,
 borderColor: '#ccc',
 borderRadius: 8,
 padding: 2,
 position: 'relative',
 },
 thumbnail: {
 width: 70,
 height: 70,
 marginRight: 10,
 },
 thumbnailGrid: {
 width: 80,
 height: 80,
 marginBottom: 0,
 },
 fileName: {
 fontSize: 16,
 marginLeft: 10,
 flex: 1,
 },
 deleteButton: {
 marginLeft: 60,
 width: 20,
 height: 20,
 },
 deleteButtonGrid: {
 position: 'absolute',
 bottom: 5,
 right: 5,
 },
 convertButton: {
 backgroundColor: '#007BFF',
 padding: 15,
 borderRadius: 10,
 alignItems: 'center',
 marginTop: 20,
 width: '100%',
 },
 convertButtonText: {
 color: '#fff',
 fontSize: 18,
 fontWeight: 'bold',
 },
 gridContainer: {
 flexDirection: 'row',
 flexWrap: 'wrap',
 justifyContent: 'flex-start',
 paddingVertical: 5,
 paddingHorizontal: 5,
 width: '100%',
 },
});






App.json




{
 "expo": {
 "name": "VidoeConvert",
 "slug": "VidoeConvert",
 "version": "1.0.0",
 "orientation": "portrait",
 "icon": "./assets/icon.png",
 "userInterfaceStyle": "light",
 "splash": {
 "image": "./assets/splash.png",
 "resizeMode": "contain",
 "backgroundColor": "#ffffff"
 },
 "ios": {
 "supportsTablet": true
 },
 "android": {
 "adaptiveIcon": {
 "foregroundImage": "./assets/adaptive-icon.png",
 "backgroundColor": "#ffffff"
 },
 "package": "com.anonymous.VidoeConvert"
 },
 "web": {
 "favicon": "./assets/favicon.png"
 },
 "plugins": [
 "@config-plugins/ffmpeg-kit-react-native",
 "expo-build-properties"
 ]
 }
}






Package.json




{
 "name": "vidoeconvert",
 "version": "1.0.0",
 "main": "expo/AppEntry.js",
 "scripts": {
 "start": "expo start",
 "android": "expo run:android",
 "ios": "expo run:ios",
 "web": "expo start --web"
 },
 "dependencies": {
 "@config-plugins/ffmpeg-kit-react-native": "^8.0.0",
 "@expo/metro-runtime": "~3.2.1",
 "expo": "~51.0.17",
 "expo-asset": "~10.0.10",
 "expo-av": "^14.0.6",
 "expo-document-picker": "~12.0.2",
 "expo-file-system": "~17.0.1",
 "expo-image-picker": "~15.0.7",
 "expo-media-library": "~16.0.4",
 "expo-status-bar": "~1.12.1",
 "ffmpeg-kit-react-native": "^6.0.2",
 "react": "18.2.0",
 "react-dom": "18.2.0",
 "react-native": "^0.74.3",
 "react-native-document-picker": "^9.3.0",
 "react-native-ffmpeg": "^0.5.2",
 "react-native-vector-icons": "^10.1.0",
 "react-native-web": "~0.19.10",
 "expo-build-properties": "~0.12.3"
 },
 "devDependencies": {
 "@babel/core": "^7.20.0"
 },
 "private": true
}






Has anyone encountered a similar issue or can point me in the right direction to resolve this error ? Any help would be greatly appreciated !


How to remove the error ?


any configruation required for this project ?


-
Introducing the BigQuery & Data Warehouse Export feature
30 janvier, par Matomo Core TeamMatomo is built on a simple truth : your data belongs to you, and you should have complete control over it. That’s why we’re excited to launch our new BigQuery & Data Warehouse Export feature for Matomo Cloud, giving you even more ways to work with your analytics data.
Until now, getting raw data from Matomo Cloud required APIs and custom scripts, or waiting for engineering help.
Our new BigQuery & Data Warehouse Export feature removes those barriers. You can now access your raw, unaggregated data and schedule regular exports straight to your data warehouse.
The feature works with all major data warehouses including (but not limited to) :
- Google BigQuery
- Amazon Redshift
- Snowflake
- Azure Synapse Analytics
- Apache Hive
- Teradata
You can schedule exports, combine your Matomo data with other data sources in your data warehouse, and easily query data with SQL-like queries.
Direct raw data access for greater data portability
Waiting for engineering support can delay your work. Managing API connections and writing scripts can be time-consuming. This keeps you from focusing on what you do best—analysing data.
With the BigQuery & Data Warehouse Export feature, you get direct access to your raw Matomo data without the technical setup. So, you can spend more time analysing data and finding insights that matter.
Bringing your data together
Answering business questions often requires data from multiple sources. A single customer interaction might span your CRM, web analytics, sales systems, and more. Piecing this data together manually is time-consuming—what starts as a seemingly simple question from stakeholders can turn into hours of work collecting and comparing data across different tools.
This feature lets you combine your Matomo data with data from other business systems in your data warehouse. Instead of switching between tools or manually comparing spreadsheets, you can analyse all your data in one place to better understand how customers interact with your business.
Easy, custom analysis with SQL-like queries
Standard, pre-built reports often don’t address the specific, detailed questions that analysts need to answer.
When you use the BigQuery & Data Warehouse Export feature, you can use SQL-like queries in your data warehouse to do detailed, customised analysis. This flexibility allows you to explore your data in depth and uncover specific insights that aren’t possible with pre-built reports.
Here is an example of how you might use SQL-like query to compare the behaviours of paying vs. non-paying users :
<xmp>SELECT
custom_dimension_value AS user_type, -- Assuming 'user_type' is stored in a custom dimension
COUNT(*) AS total_visits,
AVG(visit_total_time) AS avg_duration,
SUM(conversion.revenue) AS total_spent
FROM
`your_project.your_dataset.matomo_log_visit` AS visit
LEFT JOIN
`your_project.your_dataset.matomo_log_conversion` AS conversion
ON
visit.idvisit = conversion.idvisit
GROUP BY
custom_dimension_value; </xmp>
This query helps you compare metrics such as the number of visits, average session duration, and total amount spent between paying and non-paying users. It provides a full view of behavioural differences between these groups.
Advanced data manipulation and visualisation
When you need to create detailed reports or dive deep into data analysis, working within the constraints of a fixed user interface (UI) can limit your ability to draw insights.
Exporting your Matomo data to a data warehouse like BigQuery provides greater flexibility for in-depth manipulation and advanced visualisations, enabling you to uncover deeper insights and tailor your reports more effectively.
Getting started
To set up data warehouse exports in your Matomo :
- Go to System Admin (cog icon in the top right corner)
- Select ‘Export’ from the left-hand menu
- Choose ‘BigQuery & Data Warehouse’
You’ll find detailed instructions in our data warehouse exports guide.
Please note, enabling this feature will cost an additional 10% of your current subscription. You can view the exact cost by following the steps above.
New to Matomo ? Start your 21-day free trial now (no credit card required), or request a demo.
Try Matomo for Free
21 day free trial. No credit card required.
Syndiquer tout le site
