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MediaSPIP Simple : futur thème graphique par défaut ?
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Autres articles (112)
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Mise à jour de la version 0.1 vers 0.2
24 juin 2013, parExplications des différents changements notables lors du passage de la version 0.1 de MediaSPIP à la version 0.3. Quelles sont les nouveautés
Au niveau des dépendances logicielles Utilisation des dernières versions de FFMpeg (>= v1.2.1) ; Installation des dépendances pour Smush ; Installation de MediaInfo et FFprobe pour la récupération des métadonnées ; On n’utilise plus ffmpeg2theora ; On n’installe plus flvtool2 au profit de flvtool++ ; On n’installe plus ffmpeg-php qui n’est plus maintenu au (...) -
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 ;
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Ecrire une actualité
21 juin 2013, parPrésentez les changements dans votre MédiaSPIP ou les actualités de vos projets sur votre MédiaSPIP grâce à la rubrique actualités.
Dans le thème par défaut spipeo de MédiaSPIP, les actualités sont affichées en bas de la page principale sous les éditoriaux.
Vous pouvez personnaliser le formulaire de création d’une actualité.
Formulaire de création d’une actualité Dans le cas d’un document de type actualité, les champs proposés par défaut sont : Date de publication ( personnaliser la date de publication ) (...)
Sur d’autres sites (8418)
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10 Customer Segments Examples and Their Benefits
9 mai 2024, par ErinNow that companies can segment buyers, the days of mass marketing are behind us. Customer segmentation offers various benefits for marketing, content creation, sales, analytics teams and more. Without customer segmentation, your personalised marketing efforts may fall flat.
According to the Twilio 2023 state of personalisation report, 69% of business leaders have increased their investment in personalisation. There’s a key reason for this — customer retention and loyalty directly benefit from personalisation. In fact, 62% of businesses have cited improved customer retention due to personalisation efforts. The numbers don’t lie.
Keep reading to learn how customer segments can help you fine-tune your personalised marketing campaigns. This article will give you a better understanding of customer segmentation and real-world customer segment examples. You’ll leave with the knowledge to empower your marketing strategies with effective customer segmentation.
What are customer segments ?
Customer segments are distinct groups of people or organisations with similar characteristics, needs and behaviours. Like different species of plants in a garden, each customer segment has specific needs and care requirements. Customer segments are useful for tailoring personalised marketing campaigns for specific groups.
Personalised marketing has been shown to have significant benefits — with 56% of consumers saying that a personalised experience would make them become repeat buyers.
Successful marketing teams typically focus on these types of customer segmentation :
- Geographic segmentation : groups buyers based on their physical location — country, city, region or climate — and language.
- Purchase history segmentation : categorises buyers based on their purchasing habits — how often they make purchases — and allows brands to distinguish between frequent, occasional and one-time buyers.
- Product-based segmentation : groups buyers according to the products they prefer or end up purchasing.
- Customer lifecycle segmentation : segments buyers based on where they are in the customer journey. Examples include new, repeat and lapsed buyers. This segmentation category is also useful for understanding the behaviour of loyal buyers and those at risk of churning.
- Technographic segmentation : focuses on buyers’ technology preferences, including device type, browser type, and operating system.
- Channel preference segmentation : helps us understand why buyers prefer to purchase via specific channels — whether online channels, physical stores or a combination of both.
- Value-based segmentation : categorises buyers based on their average purchase value and sensitivity to pricing, for example. This type of segmentation can provide insights into the behaviours of price-conscious buyers and those willing to pay premium prices.
Customer segmentation vs. market segmentation
Customer segmentation and market segmentation are related concepts, but they refer to different aspects of the segmentation process in marketing.
Market segmentation is the broader process of dividing the overall market into homogeneous groups. Market segmentation helps marketers identify different groups based on their characteristics or needs. These market segments make it easier for businesses to connect with new buyers by offering relevant products or new features.
On the other hand, customer segmentation is used to help you dig deep into the behaviour and preferences of your current customer base. Marketers use customer segmentation insights to create buyer personas. Buyer personas are essential for ensuring your personalised marketing efforts are relevant to the target audience.
10 customer segments examples
Now that you better understand different customer segmentation categories, we’ll provide real-world examples of how customer segmentation can be applied. You’ll be able to draw a direct connection between the segmentation category or categories each example falls under.
One thing to note is that you’ll want to consider privacy and compliance when you are considering collecting and analysing types of data such as gender, age, income level, profession or personal interests. Instead, you can focus on these privacy-friendly, ethical customer segmentation types :
1. Geographic location (category : geographic segmentation)
The North Face is an outdoor apparel and equipment company that relies on geographic segmentation to tailor its products toward buyers in specific regions and climates.
For instance, they’ll send targeted advertisements for insulated jackets and snow gear to buyers in colder climates. For folks in seasonal climates, The North Face may send personalised ads for snow gear in winter and ads for hiking or swimming gear in summer.
The North Face could also use geographic segmentation to determine buyers’ needs based on location. They can use this information to send targeted ads to specific customer segments during peak ski months to maximise profits.
2. Preferred language (category : geographic segmentation)
Your marketing approach will likely differ based on where your customers are and the language they speak. So, with that in mind, language may be another crucial variable you can introduce when identifying your target customers.
Language-based segmentation becomes even more important when one of your main business objectives is to expand into new markets and target international customers — especially now that global reach is made possible through digital channels.
Coca-Cola’s “Share a Coke” is a multi-national campaign with personalised cans and bottles featuring popular names from countries around the globe. It’s just one example of targeting customers based on language.
3. Repeat users and loyal customers (category : customer lifecycle segmentation)
Sephora, a large beauty supply company, is well-known for its Beauty Insider loyalty program.
It segments customers based on their purchase history and preferences and rewards their loyalty with gifts, discounts, exclusive offers and free samples. And since customers receive personalised product recommendations and other perks, it incentivises them to remain members of the Beauty Insider program — adding a boost to customer loyalty.
By creating a memorable customer experience for this segment of their customer base, staying on top of beauty trends and listening to feedback, Sephora is able to keep buyers coming back.
4. New customers (category : customer lifecycle segmentation)
Subscription services use customer lifecycle segmentation to offer special promotions and trials for new customers.
HBO Max is a great example of a real company that excels at this strategy :
They offer 40% savings on an annual ad-free plan, which targets new customers who may be apprehensive about the added monthly cost of a recurring subscription.
This marketing strategy prioritises fostering long-term customer relationships with new buyers to avoid high churn rates.
5. Cart abandonment (category : purchase history segmentation)
With a rate of 85% among US-based mobile users, cart abandonment is a huge issue for ecommerce businesses. One way to deal with this is to segment inactive customers and cart abandoners — those who showed interest by adding products to their cart but haven’t converted yet — and send targeted emails to remind them about their abandoned carts.
E-commerce companies like Ipsy, for example, track users who have added items to their cart but haven’t followed through on the purchase. The company’s messaging often contains incentives — like free shipping or a limited-time discount — to encourage passive users to return to their carts.
Research has found that cart abandonment emails with a coupon code have a high 44.37% average open rate.
6. Website activity (category : technographic segmentation)
It’s also possible to segment customers based on website activity. Now, keep in mind that this is a relatively broad approach ; it covers every interaction that may occur while the customer is browsing your website. As such, it leaves room for many different types of segmentation.
For instance, you can segment your audience based on the pages they visited, the elements they interacted with — like CTAs and forms — how long they stayed on each page and whether they added products to their cart.
Matomo’s Event Tracking can provide additional context to each website visit and tell you more about the specific interactions that occur, making it particularly useful for segmenting customers based on how they spend their time on your website.
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Get the web insights you need, while respecting user privacy.
Amazon segments its customers based on browsing behaviour — recently viewed products and categories, among other things — which, in turn, allows them to improve the customer’s experience and drive sales.
7. Traffic source (category : channel segmentation)
You can also segment your audience based on traffic sources. For example, you can determine if your website visitors arrived through Google and other search engines, email newsletters, social media platforms or referrals.
In other words, you’ll create specific audience segments based on the original source. Matomo’s Acquisition feature can provide insights into five different types of traffic sources — search engines, social media, external websites, direct traffic and campaigns — to help you understand how users enter your website.
You may find that most visitors arrive at your website through social media ads or predominantly discover your brand through search engines. Either way, by learning where they’re coming from, you’ll be able to determine which conversion paths you should prioritise and optimise further.
8. Device type (category : technographic segmentation)
Device type is customer segmentation based on the devices that potential customers may use to access your website and view your content.
It’s worth noting that, on a global level, most people (96%) use mobile devices — primarily smartphones — for internet access. So, there’s a high chance that most of your website visitors are coming from mobile devices, too.
However, it’s best not to assume anything. Matomo can detect the operating system and the type of device — desktop, mobile device, tablet, console or TV, for example.
By introducing the device type variable into your customer segmentation efforts, you’ll be able to determine if there’s a preference for mobile or desktop devices. In return, you’ll have a better idea of how to optimise your website — and whether you should consider developing an app to meet the needs of mobile users.
Try Matomo for Free
Get the web insights you need, while respecting user privacy.
9. Browser type (category : technographic segmentation)
Besides devices, another type of segmentation that belongs to the technographic category and can provide valuable insights is browser-related. In this case, you’re tracking the internet browser your customers use.
Many browser types are available — including Google Chrome, Microsoft Edge, Safari, Firefox and Brave — and each may display your website and other content differently.
So, keeping track of your customers’ preferred choices is important. Otherwise, you won’t be able to fully understand their online experience — or ensure that these browsers are displaying your content properly.
10. Ecommerce activity (category : purchase history, value based, channel or product based segmentation)
Similar to website activity, looking at ecommerce activity can tell your sales teams more about which pages the customer has seen and how they have interacted with them.
With Matomo’s Ecommerce Tracking, you’ll be able to keep an eye on customers’ on-site behaviours, conversion rates, cart abandonment, purchased products and transaction data — including total revenue and average order value.
Considering that the focus is on sales channels — such as your online store — this approach to customer segmentation can help you improve the sales experience and increase profitability.
Start implementing these customer segments examples
With ever-evolving demographics and rapid technological advancements, customer segmentation is increasingly complex. The tips and real-world examples in this article break down and simplify customer segmentation so that you can adapt to your customer base.
Customer segmentation lays the groundwork for your personalised marketing campaigns to take off. By understanding your users better, you can effectively tailor each campaign to different segments.
If you’re ready to see how Matomo can elevate your personalised marketing campaigns, try it for free for 21 days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
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What Is Data Misuse & How to Prevent It ? (With Examples)
13 mai 2024, par ErinYour data is everywhere. Every time you sign up for an email list, log in to Facebook or download a free app onto your smartphone, your data is being taken.
This can scare customers and users who fear their data will be misused.
While data can be a powerful asset for your business, it’s important you manage it well, or you could be in over your head.
In this guide, we break down what data misuse is, what the different types are, some examples of major data misuse and how you can prevent it so you can grow your brand sustainably.
What is data misuse ?
Data is a good thing.
It helps analysts and marketers understand their customers better so they can serve them relevant information, products and services to improve their lives.
But it can quickly become a bad thing for both the customers and business owners when it’s mishandled and misused.
Data misuse is when a business uses data outside of the agreed-upon terms. When companies collect data, they need to legally communicate how that data is being used.
Who or what determines when data is being misused ?
Several bodies :
- User agreements
- Data privacy laws
- Corporate policies
- Industry regulations
There are certain laws and regulations around how you can collect and use data. Failure to comply with these guidelines and rules can result in several consequences, including legal action.
Keep reading to discover the different types of data misuse and how to prevent it.
3 types of data misuse
There are a few different types of data misuse.
If you fail to understand them, you could face penalties, legal trouble and a poor brand reputation.
1. Commingling
When you collect data, you need to ensure you’re using it for the right purpose. Commingling is when an organisation collects data from a specific audience for a specific reason but then uses the data for another purpose.
One example of commingling is if a company shares sensitive customer data with another company. In many cases, sister companies will share data even if the terms of the data collection didn’t include that clause.
Another example is if someone collects data for academic purposes like research but then uses the data later on for marketing purposes to drive business growth in a for-profit company.
In either case, the company went wrong by not being clear on what the data would be used for. You must communicate with your audience exactly how the data will be used.
2. Personal benefit
The second common way data is misused in the workplace is through “personal benefit.” This is when someone with access to data abuses it for their own gain.
The most common example of personal benefit data muse is when an employee misuses internal data.
While this may sound like each instance of data misuse is caused by malicious intent, that’s not always the case. Data misuse can still exist even if an employee didn’t have any harmful intent behind their actions.
One of the most common examples is when an employee mistakenly moves data from a company device to personal devices for easier access.
3. Ambiguity
As mentioned above, when discussing commingling, a company must only use data how they say they will use it when they collect it.
A company can misuse data when they’re unclear on how the data is used. Ambiguity is when a company fails to disclose how user data is being collected and used.
This means communicating poorly on how the data will be used can be wrong and lead to misuse.
One of the most common ways this happens is when a company doesn’t know how to use the data, so they can’t give a specific reason. However, this is still considered misuse, as companies need to disclose exactly how they will use the data they collect from their customers.
Laws on data misuse you need to follow
Data misuse can lead to poor reputations and penalties from big tech companies. For example, if you step outside social media platforms’ guidelines, you could be suspended, banned or shadowbanned.
But what’s even more important is certain types of data misuse could mean you’re breaking laws worldwide. Here are some laws on data misuse you need to follow to avoid legal trouble :
General Data Protection Regulation (GDPR)
The GDPR, or General Data Protection Regulation, is a law within the European Union (EU) that went into effect in 2018.
The GDPR was implemented to set a standard and improve data protection in Europe. It was also established to increase accountability and transparency for data breaches within businesses and organisations.
The purpose of the GDPR is to protect residents within the European Union.
The penalties for breaking GDPR laws are fines up to 20 million Euros or 4% of global revenues (whatever the higher amount is).
The GDPR doesn’t just affect companies in Europe. You can break the GDPR’s laws regardless of where your organisation is located worldwide. As long as your company collects, processes or uses the personal data of any EU resident, you’re subject to the GDPR’s rules.
If you want to track user data to grow your business, you need to ensure you’re following international data laws. Tools like Matomo—the world’s leading privacy-friendly web analytics solution—can help you achieve GDPR compliance and maintain it.
With Matomo, you can confidently enhance your website’s performance, knowing that you’re adhering to data protection laws.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
California Consumer Privacy Act (CCPA)
The California Consumer Privacy Act (CCPA) is another important data law companies worldwide must follow.
Like GDPR, the CCPA is a data privacy law established to protect residents of a certain region — in this case, residents of California in the United States.
The CCPA was implemented in 2020, and businesses worldwide can be penalised for breaking the regulations. For example, if you’re found violating the CCPA, you could be fined $7,500 for each intentional violation.
If you have unintentional violations, you could still be fined, but at a lesser fee of $2,500.
The Gramm-Leach-Bliley Act (GLBA)
If your business is located within the United States, then you’re subject to a federal law implemented in 1999 called The Gramm-Leach-Bliley Act (GLB Act or GLBA).
The GLBA is also known as the Financial Modernization Act of 1999. Its purpose is to control the way American financial institutions handle consumer data.
In the GLBA, there are three sections :
- The Financial Privacy Rule : regulates the collection and disclosure of private financial data.
- Safeguards Rule : Financial institutions must establish security programs to protect financial data.
- Pretexting Provisions : Prohibits accessing private data using false pretences.
The GLBA also requires financial institutions in the U.S. to give their customers written privacy policy communications that explain their data-sharing practices.
4 examples of data misuse in real life
If you want to see what data misuse looks like in real life, look no further.
Big tech is central to some of the biggest data misuses and scandals.
Here are a few examples of data misuse in real life you should take note of to avoid a similar scenario :
1. Facebook election interference
One of history’s most famous examples of data misuse is the Facebook and Cambridge Analytica scandal in 2018.
During the 2018 U.S. midterm elections, Cambridge Analytica, a political consulting firm, acquired personal data from Facebook users that was said to have been collected for academic research.
Instead, Cambridge Analytica used data from roughly 87 million Facebook users.
This is a prime example of commingling.
The result ? Cambridge Analytica was left bankrupt and dissolved, and Facebook was fined $5 billion by the Federal Trade Commission (FTC).
2. Uber “God View” tracking
Another big tech company, Uber, was caught misusing data a decade ago.
Why ?
Uber implemented a new feature for its employees in 2014 called “God View.”
The tool enabled Uber employees to track riders using their app. The problem was that they were watching them without the users’ permission. “God View” lets Uber spy on their riders to see their movements and locations.
The FTC ended up slapping them with a major lawsuit, and as part of their settlement agreement, Uber agreed to have an outside firm audit their privacy practices between 2014 and 2034.
3. Twitter targeted ads overstep
In 2019, Twitter was found guilty of allowing advertisers to access its users’ personal data to improve advertisement targeting.
Advertisers were given access to user email addresses and phone numbers without explicit permission from the users. The result was that Twitter ad buyers could use this contact information to cross-reference with Twitter’s data to serve ads to them.
Twitter stated that the data leak was an internal error.
4. Google location tracking
In 2020, Google was found guilty of not explicitly disclosing how it’s using its users’ personal data, which is an example of ambiguity.
The result ?
The French data protection authority fined Google $57 million.
8 ways to prevent data misuse in your company
Now that you know the dangers of data misuse and its associated penalties, it’s time to understand how you can prevent it in your company.
Here are eight ways you can prevent data misuse :
1. Track data with an ethical web analytics solution
You can’t get by in today’s business world without tracking data. The question is whether you’re tracking it safely or not.
If you want to ensure you aren’t getting into legal trouble with data misuse, then you need to use an ethical web analytics solution like Matomo.
With it, you can track and improve your website performance while remaining GDPR-compliant and respecting user privacy. Unlike other web analytics solutions that monetise your data and auction it off to advertisers, with Matomo, you own your data.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
2. Don’t share data with big tech
As the data misuse examples above show, big tech companies often violate data privacy laws.
And while most of these companies, like Google, appear to be convenient, they’re often inconvenient (and much worse), especially regarding data leaks, privacy breaches and the sale of your data to advertisers.
Have you ever heard the phrase : “You are the product ?” When it comes to big tech, chances are if you’re getting it for free, you (and your data) are the products they’re selling.
The best way to stop sharing data with big tech is to stop using platforms like Google. For more ideas on different Google product alternatives, check out this list of Google alternatives.
3. Identity verification
Data misuse typically isn’t a company-wide ploy. Often, it’s the lack of security structure and systems within your company.
An important place to start is to ensure proper identity verification for anyone with access to your data.
4. Access management
After establishing identity verification, you should ensure you have proper access management set up. For example, you should only give specific access to specific roles in your company to prevent data misuse.
5. Activity logs and monitoring
One way to track data misuse or breaches is by setting up activity logs to ensure you can see who is accessing certain types of data and when they’re accessing it.
You should ensure you have a team dedicated to continuously monitoring these logs to catch anything quickly.
6. Behaviour alerts
While manually monitoring data is important, it’s also good to set up automatic alerts if there is unusual activity around your data centres. You should set up behaviour alerts and notifications in case threats or compromising events occur.
7. Onboarding, training, education
One way to ensure quality data management is to keep your employees up to speed on data security. You should ensure data security is a part of your employee onboarding. Also, you should have regular training and education to keep people informed on protecting company and customer data.
8. Create data protocols and processes
To ensure long-term data security, you should establish data protocols and processes.
To protect your user data, set up rules and systems within your organisation that people can reference and follow continuously to prevent data misuse.
Leverage data ethically with Matomo
Data is everything in business.
But it’s not something to be taken lightly. Mishandling user data can break customer trust, lead to penalties from organisations and even create legal trouble and massive fines.
You should only use privacy-first tools to ensure you’re handling data responsibly.
Matomo is a privacy-friendly web analytics tool that collects, stores and tracks data across your website without breaking privacy laws.
With over 1 million websites using Matomo, you can track and improve website performance with :
- Accurate data (no data sampling)
- Privacy-friendly and compliant with privacy regulations like GDPR, CCPA and more
- Advanced features like heatmaps, session recordings, A/B testing and more
Try Matomo free for 21-days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
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Capture from multiple streams concurrently, best way to do it and how to reduce CPU usage
19 juin 2019, par DRONE_6969I am currently in the process of writing an application that will capture a lot of RTSP streams(in my case its 12) and display it on the QT widget. The problem arouses when I am going beyond around 6-7 streams, the CPU usage spikes and there is visible stutter.
The reason why I think that it is not QT draw function is because I have done some checking to measure how much time it takes to draw an incoming image from camera and just sample images I had, it is always a lot less than 33 milliseconds(even if there are 12 widgets being updated).
I also just ran opencv capture method without drawing and got pretty much the same CPU consumption as if I was drawing the frames (lost like 10% CPU at most and GPU usage went to zero).
IMPORTANT : I am using RTSP stream which is a h264 stream.
IF IT MATTERS MY SPECS :
Intel Core i7-6700 @ 3.40GHZ(8 CPUS)
Memory : 16gb
GPU : Intel HD Graphics 530(Also I ran my code on a computer with dedicated Graphics card, it did eliminate some stutter but CPU usage is still pretty high)
I am currently using OPENCV 4.1.0 with GSTREAMER enabled and built, I also have the OPENCV-WORLD version, there is no difference in performance.
I have created a special class called Camera that holds its frame size constraints and various control functions as well stream function. The stream function is being ran on a separate thread, whenever stream() function is done with current frame it sends ready Mat via onNewFrame event I created which converts to QPixmap and updates widget’s lastImage variable. This way I can update image in a more thread safe way.
I have tried to manipulate those VideoCapture.set() values, but it didn’t really help.
This is my stream function (Ignore the bool return, it doesn’t do anything it is a remnant from couple of minutes ago when I was trying to use std::async) :
bool Camera::stream() {
/* This function is meant to run on a separate thread and fill up the buffer independantly of
main stream thread */
//cv::setNumThreads(100);
/* Rules for these slightly changed! */
Mat pre; // Grab initial undoctored frame
//pre = Mat::zeros(size, CV_8UC1);
Mat frame; // Final modified frame
frame = Mat::zeros(size, CV_8UC1);
if (!pre.isContinuous()) pre = pre.clone();
ipCam.open(streamUrl, CAP_FFMPEG);
while (ipCam.isOpened() && capture) {
// If camera is opened wel need to capture and process the frame
try {
auto start = std::chrono::system_clock::now();
ipCam >> pre;
if (pre.empty()) {
/* Check for blank frame, return error if there is a blank frame*/
cerr << id << ": ERROR! blank frame grabbed\n";
for (FrameListener* i : clients) {
i->onNotification(1); // Notify clients about this shit
}
break;
}
else {
// Only continue if frame not empty
if (pre.cols != size.width && pre.rows != size.height) {
resize(pre, frame, size);
pre.release();
}
else {
frame = pre;
}
dPacket* pack = new dPacket{id,&frame};
for (auto i : clients) {
i->onPNewFrame(pack);
}
frame.release();
delete pack;
}
}
catch (int e) {
cout << endl << "-----Exception during capture process! CODE " << e << endl;
}
// End camera manipulations
}
cout << "Camera timed out, or connection is closed..." << endl;
if (tryResetConnection) {
cout << "Reconnection flag is set, retrying after 3 seconds..." << endl;
for (FrameListener* i : clients) {
i->onNotification(-1); // Notify clients about this shit
}
this_thread::sleep_for(chrono::milliseconds(3000));
stream();
}
return true;
}This is my onPNewFrame function. The conversion is still being done on camera’s thread because it was called within stream() and therefore is within that scope(and I also checked) :
void GLWidget::onPNewFrame(dPacket* inPack) {
lastFlag = 0;
if (bufferEnabled) {
buffer.push(QPixmap::fromImage(toQImageFromPMat(inPack->frame)));
}
else {
if (playing) {
/* Only process if this widget is playing */
frameProcessing = true;
lastImage.convertFromImage(toQImageFromPMat(inPack->frame));
frameProcessing = false;
}
}
if (lastFlag != -1 && !lastImage.isNull()) {
connecting = false;
}
else {
connecting = true;
}
}This is my Mat to QImage :
QImage GLWidget::toQImageFromPMat(cv::Mat* mat) {
return QImage(mat->data, mat->cols, mat->rows, QImage::Format_RGB888).rgbSwapped();NOTE : not converting does not result in CPU boost (at least not a significant one).
Minimal verifiable example
This program is large. I am going to paste GLWidget.cpp and GLWidget.h as well as Camera.h and Camera.cpp. You can put GLWidget into anything just as long as you spawn more than 6 of it. Camera relies on the CamUtils, but it is possible to just paste url in videocapture
I also supplied CamUtils, just in case
Camera.h :
#pragma once
#include <iostream>
#include <vector>
#include <fstream>
#include <map>
#include <string>
#include <sstream>
#include <algorithm>
#include "FrameListener.h"
#include
#include <thread>
#include "CamUtils.h"
#include <ctime>
#include "dPacket.h"
using namespace std;
using namespace cv;
class Camera
{
/*
CLEANED UP!
Camera now is only responsible for streaming and echoing captured frames.
Frames are now wrapped into dPacket struct.
*/
private:
string id;
vector clients;
VideoCapture ipCam;
string streamUrl;
Size size;
bool tryResetConnection = false;
//TODO: Remove these as they are not going to be used going on:
bool isPlaying = true;
bool capture = true;
//SECRET FEATURES:
bool detect = false;
public:
Camera(string url, int width = 480, int height = 240, bool detect_=false);
bool stream();
void setReconnectable(bool newReconStatus);
void addListener(FrameListener* client);
vector<bool> getState(); // Returns current state: vector[0] stream state; vector[1] stream state; TODO: Remove this as this is no longer should control behaviour
void killStream();
bool getReconnectable();
};
</bool></ctime></thread></algorithm></sstream></string></map></fstream></vector></iostream>Camera.cpp
#include "Camera.h"
Camera::Camera(string url, int width, int height, bool detect_) // Default 240p
{
streamUrl = url; // Prepare url
size = Size(width, height);
detect = detect_;
}
void Camera::addListener(FrameListener* client) {
clients.push_back(client);
}
/*
TEST CAMERAS(Paste into cameras.dViewer):
{"id":"96a73796-c129-46fc-9c01-40acd8ed7122","ip":"176.57.73.231","password":"null","username":"null"},
{"id":"96a73796-c129-46fc-9c01-40acd8ed7122","ip":"176.57.73.231","password":"null","username":"null"},
{"id":"96a73796-c129-46fc-9c01-40acd8ed7144","ip":"172.20.101.13","password":"admin","username":"root"}
{"id":"96a73796-c129-46fc-9c01-40acd8ed7144","ip":"172.20.101.13","password":"admin","username":"root"}
*/
bool Camera::stream() {
/* This function is meant to run on a separate thread and fill up the buffer independantly of
main stream thread */
//cv::setNumThreads(100);
/* Rules for these slightly changed! */
Mat pre; // Grab initial undoctored frame
//pre = Mat::zeros(size, CV_8UC1);
Mat frame; // Final modified frame
frame = Mat::zeros(size, CV_8UC1);
if (!pre.isContinuous()) pre = pre.clone();
ipCam.open(streamUrl, CAP_FFMPEG);
while (ipCam.isOpened() && capture) {
// If camera is opened wel need to capture and process the frame
try {
auto start = std::chrono::system_clock::now();
ipCam >> pre;
if (pre.empty()) {
/* Check for blank frame, return error if there is a blank frame*/
cerr << id << ": ERROR! blank frame grabbed\n";
for (FrameListener* i : clients) {
i->onNotification(1); // Notify clients about this shit
}
break;
}
else {
// Only continue if frame not empty
if (pre.cols != size.width && pre.rows != size.height) {
resize(pre, frame, size);
pre.release();
}
else {
frame = pre;
}
auto end = std::chrono::system_clock::now();
std::time_t ts = std::chrono::system_clock::to_time_t(end);
dPacket* pack = new dPacket{ id,&frame};
for (auto i : clients) {
i->onPNewFrame(pack);
}
frame.release();
delete pack;
}
}
catch (int e) {
cout << endl << "-----Exception during capture process! CODE " << e << endl;
}
// End camera manipulations
}
cout << "Camera timed out, or connection is closed..." << endl;
if (tryResetConnection) {
cout << "Reconnection flag is set, retrying after 3 seconds..." << endl;
for (FrameListener* i : clients) {
i->onNotification(-1); // Notify clients about this shit
}
this_thread::sleep_for(chrono::milliseconds(3000));
stream();
}
return true;
}
void Camera::killStream(){
tryResetConnection = false;
capture = false;
ipCam.release();
}
void Camera::setReconnectable(bool reconFlag) {
tryResetConnection = reconFlag;
}
bool Camera::getReconnectable() {
return tryResetConnection;
}
vector<bool> Camera::getState() {
vector<bool> states;
states.push_back(isPlaying);
states.push_back(ipCam.isOpened());
return states;
}
</bool></bool>GLWidget.h :
#ifndef GLWIDGET_H
#define GLWIDGET_H
#include <qopenglwidget>
#include <qmouseevent>
#include "FrameListener.h"
#include "Camera.h"
#include "FrameListener.h"
#include
#include "Camera.h"
#include "CamUtils.h"
#include
#include "dPacket.h"
#include <chrono>
#include <ctime>
#include
#include "FullScreenVideo.h"
#include <qmovie>
#include "helper.h"
#include <iostream>
#include <qpainter>
#include <qtimer>
class Helper;
class GLWidget : public QOpenGLWidget, public FrameListener
{
Q_OBJECT
public:
GLWidget(std::string camId, CamUtils *cUtils, int width, int height, bool denyFullScreen_ = false, bool detectFlag_=false, QWidget* parent = nullptr);
void killStream();
~GLWidget();
public slots:
void animate();
void setBufferEnabled(bool setState);
void setCameraRetryConnection(bool setState);
void GLUpdate(); // Call to update the widget
void onRightClickMenu(const QPoint& point);
protected:
void paintEvent(QPaintEvent* event) override;
void onPNewFrame(dPacket* frame);
void onNotification(int alert_code);
private:
// Objects and resourses
Helper* helper;
Camera* cam;
CamUtils* camUtils;
QTimer* timer; // Keep track of update
QPixmap lastImage;
QMovie* connMov;
QMovie* test;
QPixmap logo;
// Control fields
int width;
int height;
int camUtilsAddr;
int elapsed;
std::thread* camThread;
std::string camId;
bool denyFullScreen = false;
bool playing = true;
bool streaming = true;
bool debug = false;
bool connecting = true;
int lastFlag = 0;
// Debug fields
std::chrono::high_resolution_clock::time_point lastFrameAt;
std::chrono::high_resolution_clock::time_point now;
std::chrono::duration<double> painTime; // time took to draw last frame
//Buffer stuff
std::queue<qpixmap> buffer;
bool bufferEnabled = false;
bool initialBuffer = false;
bool buffering = true;
bool frameProcessing = false;
//Functions
QImage toQImageFromPMat(cv::Mat* inFrame);
void mousePressEvent(QMouseEvent* event) override;
void drawImageGLLatest(QPainter* painter, QPaintEvent* event, int elapsed);
void drawOnPaused(QPainter* painter, QPaintEvent* event, int elapsed);
void drawOnStatus(int statusFlag, QPainter* painter, QPaintEvent* event, int elapsed);
};
#endif
</qpixmap></double></qtimer></qpainter></iostream></qmovie></ctime></chrono></qmouseevent></qopenglwidget>GLWidget.cpp :
#include "glwidget.h"
#include <future>
FullScreenVideo* fullScreen;
GLWidget::GLWidget(std::string camId_, CamUtils* cUtils, int width_, int height_, bool denyFullScreen_, bool detectFlag_, QWidget* parent)
: QOpenGLWidget(parent), helper(helper)
{
cout << "Player for CAMERA " << camId_ << endl;
/* Underlying properties */
camUtils = cUtils;
cout << "GLWidget Incoming CamUtils addr " << camUtils << endl;
cout << "GLWidget Set CamUtils addr " << camUtils << endl;
camId = camId_;
elapsed = 0;
width = width_ + 5;
height = height_ + 5;
helper = new Helper();
setFixedSize(width, height);
denyFullScreen = denyFullScreen_;
/* Camera capture thread */
cam = new Camera(camUtils->getCameraStreamURL(camId), width_, height_, detectFlag_);
cam->addListener(this);
/* Sync states */
vector<bool> initState = cam->getState();
playing = initState[0];
streaming = initState[1];
cout << "Initial states: " << playing << " " << streaming << endl;
camThread = new std::thread(&Camera::stream, cam);
cout << "================================================" << endl;
// Right click set up
setContextMenuPolicy(Qt::CustomContextMenu);
/* Loading gif */
connMov = new QMovie("establishingConnection.gif");
connMov->start();
QString url = R"(RLC-logo.png)";
logo = QPixmap(url);
QTimer* timer = new QTimer(this);
connect(timer, SIGNAL(timeout()), this, SLOT(GLUpdate()));
timer->start(1000/30);
playing = true;
}
/* SYSTEM */
void GLWidget::animate()
{
elapsed = (elapsed + qobject_cast(sender())->interval()) % 1000;
std::cout << elapsed << "\n";
}
void GLWidget::GLUpdate() {
/* Process descisions before update call */
if (bufferEnabled) {
/* Process buffer before update */
now = chrono::high_resolution_clock::now();
std::chrono::duration timeSinceLastUpdate = now - lastFrameAt;
if (timeSinceLastUpdate.count() > 25) {
if (buffer.size() > 1 && playing) {
lastImage.swap(buffer.front());
buffer.pop();
lastFrameAt = chrono::high_resolution_clock::now();
}
}
//update(); // Update
}
else {
/* No buffer */
}
repaint();
}
/* EVENTS */
void GLWidget::onRightClickMenu(const QPoint& point) {
cout << "Right click request got" << endl;
QPoint globPos = this->mapToGlobal(point);
QMenu myMenu;
if (!denyFullScreen) {
myMenu.addAction("Open Full Screen");
}
myMenu.addAction("Toggle Debug Info");
QAction* selected = myMenu.exec(globPos);
if (selected) {
string optiontxt = selected->text().toStdString();
if (optiontxt == "Open Full Screen") {
cout << "Chose to open full screen of " << camId << endl;
fullScreen = new FullScreenVideo(bufferEnabled, this);
fullScreen->setUpView(camUtils, camId);
fullScreen->show();
playing = false;
}
if (optiontxt == "Toggle Debug Info") {
cout << "Chose to toggle debug of " << camId << endl;
debug = !debug;
}
}
else {
cout << "Chose nothing!" << endl;
}
}
void GLWidget::onPNewFrame(dPacket* inPack) {
lastFlag = 0;
if (bufferEnabled) {
buffer.push(QPixmap::fromImage(toQImageFromPMat(inPack->frame)));
}
else {
if (playing) {
/* Only process if this widget is playing */
frameProcessing = true;
lastImage.convertFromImage(toQImageFromPMat(inPack->frame));
frameProcessing = false;
}
}
if (lastFlag != -1 && !lastImage.isNull()) {
connecting = false;
}
else {
connecting = true;
}
}
void GLWidget::onNotification(int alert) {
lastFlag = alert;
}
/* Paint events*/
void GLWidget::paintEvent(QPaintEvent* event)
{
QPainter painter(this);
if (lastFlag != 0 || connecting) {
drawOnStatus(lastFlag, &painter, event, elapsed);
}
else {
/* Actual frame drawing */
if (playing) {
if (!frameProcessing) {
drawImageGLLatest(&painter, event, elapsed);
}
}
else {
drawOnPaused(&painter, event, elapsed);
}
}
painter.end();
}
/* DRAWING STUFF */
void GLWidget::drawOnStatus(int statusFlag, QPainter* bgPaint, QPaintEvent* event, int elapsed) {
QString str;
QFont font("times", 15);
bgPaint->eraseRect(QRect(0, 0, width, height));
if (!lastImage.isNull()) {
bgPaint->drawPixmap(QRect(0, 0, width, height), lastImage);
}
/* Test background painting */
if (connecting) {
string k = "Connecting to " + camUtils->getIp(camId);
str.append(k.c_str());
}
else {
switch (statusFlag) {
case 1:
str = "Blank frame received...";
break;
case -1:
if (cam->getReconnectable()) {
str = "Connection lost, will try to reconnect.";
bgPaint->setOpacity(0.3);
}
else {
str = "Connection lost...";
bgPaint->setOpacity(0.3);
}
break;
}
}
bgPaint->drawPixmap(QRect(0, 0, width, height), QPixmap::fromImage(connMov->currentImage()));
bgPaint->setPen(Qt::red);
bgPaint->setFont(font);
QFontMetrics fm(font);
const QRect kek(0, 0, fm.width(str), fm.height());
QRect bound;
bgPaint->setOpacity(1);
bgPaint->drawText(bgPaint->viewport().width()/2 - kek.width()/2, bgPaint->viewport().height()/2 - kek.height(), str);
bgPaint->drawPixmap(bgPaint->viewport().width() / 2 - logo.width()/2, height - logo.width() - 15, logo);
}
void GLWidget::drawOnPaused(QPainter* painter, QPaintEvent* event, int elapsed) {
painter->eraseRect(0, 0, width, height);
QFont font = painter->font();
font.setPointSize(18);
painter->setPen(Qt::red);
QFontMetrics fm(font);
QString str("Paused");
painter->drawPixmap(QRect(0, 0, width, height),lastImage);
painter->drawText(QPoint(painter->viewport().width() - fm.width(str), 50), str);
if (debug) {
QFont font = painter->font();
font.setPointSize(25);
painter->setPen(Qt::red);
string camMess = "CAMID: " + camId;
QString mess(camMess.c_str());
string camIp = "IP: " + camUtils->getIp(camId);
QString ipMess(camIp.c_str());
QString bufferSize("Buffer size: " + QString::number(buffer.size()));
QString lastFrameText("Last frame draw time: " + QString::number(painTime.count()) + "s");
painter->drawText(QPoint(10, 50), mess);
painter->drawText(QPoint(10, 60), ipMess);
QString bufferState;
if (bufferEnabled) {
bufferState = QString("Experimental BUFFER is enabled!");
QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
painter->drawText(QPoint(10, 80), currentBufferSize);
}
else {
bufferState = QString("Experimental BUFFER is disabled!");
}
painter->drawText(QPoint(10, 70), bufferState);
painter->drawText(QPoint(10, height - 25), lastFrameText);
}
}
void GLWidget::drawImageGLLatest(QPainter* painter, QPaintEvent* event, int elapsed) {
auto start = chrono::high_resolution_clock::now();
painter->drawPixmap(QRect(0, 0, width, height), lastImage);
if (debug) {
QFont font = painter->font();
font.setPointSize(25);
painter->setPen(Qt::red);
string camMess = "CAMID: " + camId;
QString mess(camMess.c_str());
string camIp = "IP: " + camUtils->getIp(camId);
QString ipMess(camIp.c_str());
QString bufferSize("Buffer size: " + QString::number(buffer.size()));
QString lastFrameText("Last frame draw time: " + QString::number(painTime.count()) + "s");
painter->drawText(QPoint(10, 50), mess);
painter->drawText(QPoint(10, 60), ipMess);
QString bufferState;
if(bufferEnabled){
bufferState = QString("Experimental BUFFER is enabled!");
QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
painter->drawText(QPoint(10,80), currentBufferSize);
}
else {
bufferState = QString("Experimental BUFFER is disabled!");
QString currentBufferSize("Current buffer load: " + QString::number(buffer.size()));
painter->drawText(QPoint(10, 80), currentBufferSize);
}
painter->drawText(QPoint(10, 70), bufferState);
painter->drawText(QPoint(10, height - 25), lastFrameText);
}
auto end = chrono::high_resolution_clock::now();
painTime = end - start;
}
/* END DRAWING STUFF */
/* UI EVENTS */
void GLWidget::mousePressEvent(QMouseEvent* e) {
if (e->button() == Qt::LeftButton) {
if (fullScreen == nullptr || !fullScreen->isVisible()) { // Do not unpause if window is opened
playing = !playing;
}
}
if (e->button() == Qt::RightButton) {
onRightClickMenu(e->pos());
}
}
/* Utilities */
QImage GLWidget::toQImageFromPMat(cv::Mat* mat) {
return QImage(mat->data, mat->cols, mat->rows, QImage::Format_RGB888).rgbSwapped();
}
/* State control */
void GLWidget::killStream() {
cam->killStream();
camThread->join();
}
void GLWidget::setBufferEnabled(bool newBufferState) {
cout << "Player: " << camId << ", buffer state updated: " << newBufferState << endl;
bufferEnabled = newBufferState;
buffer.empty();
}
void GLWidget::setCameraRetryConnection(bool newState) {
cam->setReconnectable(newState);
}
/* Destruction */
GLWidget::~GLWidget() {
cam->killStream();
camThread->join();
}
</bool></future>CamUtils.h :
#pragma once
#include <iostream>
#include <vector>
#include <fstream>
#include <map>
#include <string>
#include <sstream>
#include <algorithm>
#include <nlohmann></nlohmann>json.hpp>
using namespace std;
using json = nlohmann::json;
class CamUtils
{
private:
string camDb = "cameras.dViewer";
map> cameraList; // Legacy
json cameras;
ofstream dbFile;
bool dbExists(); // Always hard coded
/* Old IMPLEMENTATION */
void writeLineToDb_(const string& content, bool append = false);
void loadCameras_();
/* JSON based */
void loadCameras();
public:
CamUtils();
string generateRandomString(size_t length);
string getCameraStreamURL(string cameraId) const;
string saveCamera(string ip, string username, string pass); // Return generated id
vector<string> listAllCameraIds();
string getIp(string cameraId);
};
</string></algorithm></sstream></string></map></fstream></vector></iostream>CamUtils.cpp :
#include "CamUtils.h"
#pragma comment(lib, "rpcrt4.lib") // UuidCreate - Minimum supported OS Win 2000
#include
#include <iostream>
CamUtils::CamUtils()
{
if (!dbExists()) {
ofstream dbFile;
dbFile.open(camDb);
cameras["cameras"] = json::array();
dbFile << cameras << std::endl;
dbFile.close();
}
else {
loadCameras();
}
}
vector<string> CamUtils::listAllCameraIds() {
vector<string> ids;
cout << "IN LIST " << endl;
for (auto& cam : cameras["cameras"]) {
ids.push_back(cam["id"].get<string>());
//cout << cam["id"].get<string>() << std::endl;
}
return ids;
}
string CamUtils::getIp(string id) {
vector<string> camDetails = cameraList[id];
string ip = "NO IP WILL DISPLAYED UNTIL I FIGURE OUT A BUG";
for (auto& cam : cameras["cameras"]) {
if (id == cam["id"]) {
ip = cam["ip"].get<string>();
}
}
return ip;
}
string CamUtils::getCameraStreamURL(string id) const {
string url = "err"; // err is the default, it will be overwritten in case id is found, dont forget to check for it
for (auto& cam : cameras["cameras"]) {
if (id == cam["id"]) {
if (cam["username"].get<string>() == "null") {
url = "rtsp://" + cam["ip"].get<string>() + ":554/axis-media/media.amp?tcp";
}
else {
url = "rtsp://" + cam["username"].get<string>() + ":" + cam["password"].get<string>() + "@" + cam["ip"].get<string>() + ":554/axis-media/media.amp?streamprofile=720_30";
}
}
}
return url; // Dont forget to check for err when using this shit
}
string CamUtils::saveCamera(string ip, string username, string password) {
UUID uid;
UuidCreate(&uid);
char* str;
UuidToStringA(&uid, (RPC_CSTR*)&str);
string id = str;
cout << "GEN: " << id << endl;
json cam = json({}); //Create emtpy object
cam["id"] = id;
cam["ip"] = ip;
cam["username"] = username;
cam["password"] = password;
cameras["cameras"].push_back(cam);
std::ofstream out(camDb);
out << cameras << std::endl;
cout << cameras["cameras"] << endl;
cout << "Saved camera as " << id << endl;
return id;
}
bool CamUtils::dbExists() {
ifstream dbFile(camDb);
return (bool)dbFile;
}
void CamUtils::loadCameras() {
cout << "Load call" << endl;
ifstream dbFile(camDb);
string line;
string wholeFile;
while (std::getline(dbFile, line)) {
cout << line << endl;
wholeFile += line;
}
try {
cameras = json::parse(wholeFile);
//cout << cameras["cameras"] << endl;
}
catch (exception e) {
cout << e.what() << endl;
}
dbFile.close();
}
/*
LEGACY CODE, TO BE REMOVED!
*/
void CamUtils::loadCameras_() {
/*
LEGACY CODE:
This used to be the way to load cameras, but I moved on to JSON based configuration so this is no longer needed and will be removed soon
*/
ifstream dbFile(camDb);
string line;
while (std::getline(dbFile, line)) {
/*
This function load camera data to the map:
The order MUST be the following: 0:ID, 1:IP, 2:USERNAME, 3:PASSWORD.
Always delimited with | no spaces between!
*/
if (!line.empty()) {
stringstream ss(line);
string item;
vector<string> splitString;
while (std::getline(ss, item, '|')) {
splitString.push_back(item);
}
if (splitString.size() > 0) {
/* Dont even parse if the program didnt split right*/
//cout << "Split string: " << splitString.size() << "\n";
for (int i = 0; i < (splitString.size()); i++) cameraList[splitString[0]].push_back(splitString[i]);
}
}
}
}
void CamUtils::writeLineToDb_(const string & content, bool append) {
ofstream dbFile;
cout << "Creating?";
if (append) {
dbFile.open(camDb, ios_base::app);
}
else {
dbFile.open(camDb);
}
dbFile << content.c_str() << "\r\n";
dbFile.flush();
}
/* JSON Reworx */
string CamUtils::generateRandomString(size_t length)
{
const char* charmap = "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
const size_t charmapLength = strlen(charmap);
auto generator = [&]() { return charmap[rand() % charmapLength]; };
string result;
result.reserve(length);
generate_n(back_inserter(result), length, generator);
return result;
}
</string></string></string></string></string></string></string></string></string></string></string></string></iostream>End of example
How would I go about decreasing CPU usage when dealing with large amount of streams ?
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