Recherche avancée

Sur d’autres sites (9941)

• A Primer to Ethical Marketing : How to Build Trust in a Privacy-First World

  11 mars, par Alex Carmona — Marketing, Privacy, ethical marketing

  Imagine a marketing landscape where transparency replaces tactics, where consumer privacy is prioritised over exploitation, and where authentic value builds genuine relationships.

  This isn’t just an ideal—it’s the future of marketing. And it starts with ethical marketing practices.

  76% of consumers refuse to buy from companies they do not trust with their data. Ethical marketing has become essential for business survival. As privacy regulations tighten and third-party cookies phase out, marketers face a critical question : how can they balance effective, personalised campaigns whilst respecting privacy ?

  This comprehensive guide explores what ethical marketing is, the key principles behind ethical marketing practices, and practical strategies to implement an ethical approach that builds trust while driving growth.

  What is ethical marketing ? A comprehensive definition

  Ethical marketing places respect for consumer boundaries at its core whilst delivering genuine value. It prioritises transparent practices, honest communication, and fair value exchange with consumers. This approach represents a significant shift from traditional marketing, which often relied on collecting vast amounts of user data through invasive tracking methods and obscure policies.

  The modern approach to ethical marketing creates a foundation built on three key pillars :

  • User Control : Giving people genuine choice and agency over their data
  • Fair Value : Providing clear benefits in exchange for any data shared
  • Transparency : Being honest about how data is collected, used, and protected

  

  Key principles of ethical marketing

  Transparency

  Transparency means being clear and forthright about your marketing practices, data collection policies, and business operations. It involves :

  • Using plain language to explain how you collect and use customer data
  • Being upfront about pricing, product limitations, and terms of service
  • Disclosing sponsored content and affiliate relationships
  • Making privacy policies accessible and understandable

  When Matomo surveyed 2,000 consumers, 81% said they believe an organisation’s data practices reflect their overall treatment of customers. Transparency isn’t just about compliance—it’s about demonstrating respect.

  Honesty

  While similar to transparency, honesty focuses specifically on truthfulness in communications :

  • Avoiding misleading claims or exaggerations about products and services
  • Not manipulating statistics or research findings to support marketing narratives
  • Representing products accurately in advertisements and marketing materials
  • Acknowledging mistakes and taking responsibility when things go wrong

  Social responsibility

  Ethical marketing requires consideration of a brand’s impact on society as a whole :

  • Considering environmental impacts of marketing campaigns and business practices
  • Promoting diversity and inclusion in marketing representations
  • Supporting social causes authentically rather than through “purpose-washing”
  • Ensuring marketing activities don’t promote harmful stereotypes or behaviours

  Ethical marketing dilemmas : Navigating complex business decisions

  Data privacy concerns

  The digital marketing landscape has been transformed by increasing awareness of data privacy issues and stricter regulations like GDPR, CCPA, and upcoming legislation. Key challenges include :

  • The phase-out of third-party cookies, impacting targeting and measurement
  • Growing consumer resistance to invasive tracking technologies
  • Balancing personalisation with privacy (71% of consumers expect personalised experiences, yet demand privacy)
  • Ensuring compliance across different jurisdictional requirements

  Cultural sensitivity

  Global brands must navigate complex cultural landscapes :

  • Avoiding cultural appropriation in marketing campaigns
  • Understanding varied cultural expectations around privacy
  • Respecting local customs and values in international marketing
  • Adapting messaging appropriately for diverse audiences

  Environmental sustainability

  The environmental impact of marketing activities is under increasing scrutiny :

  • Digital carbon footprints from ad serving and website hosting
  • Waste generated from physical marketing materials
  • Promoting sustainable products honestly without greenwashing
  • Aligning marketing messages with actual business practices

  The benefits of ethical marketing

  For years, digital marketing has relied on third-party data collection and broad-scale tracking. However, new regulations such as GDPR, CCPA, and the end of third-party cookies are pushing brands to adopt ethical data practices.

  Increased customer loyalty

  Ethical marketing fosters deeper relationships with customers by building trust. Research consistently shows that consumers are more loyal to brands they trust, with 71% indicating they would stop buying from a brand if trust is broken.

  These trust-based relationships are more resilient during business challenges. When customers believe in a company’s integrity, they’re more likely to give the benefit of the doubt during controversies or service issues. They’re also more likely to provide constructive feedback rather than simply leaving for competitors.

  Perhaps most importantly, loyal customers become advocates, sharing positive experiences with others and defending the brand against criticism. This organic advocacy is far more powerful than paid promotions and reduces customer acquisition costs significantly over time.

  Enhanced brand reputation

  A strong ethical stance improves overall brand perception across multiple dimensions. Media outlets are increasingly focused on corporate behaviour, providing positive coverage for ethical practices that extends a brand’s reach organically.

  Social conversations about ethical brands tend to be more positive, with consumers sharing experiences and values rather than just discussing products. This creates a halo effect that benefits all aspects of the business.

  This enhanced reputation also provides resilience during public relations challenges. Organisations with strong ethical foundations find it easier to navigate controversies because they’ve built a reservoir of goodwill with customers, employees, and other stakeholders.

  Competitive advantage

  Ethical marketing provides several distinct competitive advantages in modern markets. It helps brands access privacy-conscious consumer segments that actively avoid companies with questionable data practices. These segments often include higher-income, educated consumers who are valuable long-term customers.

  Ethical approaches also reduce vulnerability to regulatory changes and potential penalties. As privacy laws continue to evolve globally, organisations with strong ethical foundations find compliance easier and less disruptive than those scrambling to meet minimum requirements.

  Perhaps most significantly, ethical marketing supports more sustainable growth trajectories. While manipulative tactics might drive short-term results, they typically lead to higher churn rates and increasing acquisition costs. Ethical approaches build foundations for long-term success and stable growth.

  For a detailed roadmap, download the Ethical Marketing Guide.

  Case studies : Ethical marketing in action

  Patagonia : Purpose-driven marketing

  Patagonia integrates sustainability into its marketing, reinforcing its commitment to ethical business practices. By aligning with social causes, the brand strengthens customer loyalty.

  Apple : Privacy as a competitive advantage

  Apple positions itself as a leader in consumer privacy, ensuring data protection remains central to its marketing strategy. This commitment has become a key differentiator in the tech industry.

  Matomo : The ethical analytics tool

  Matomo offers privacy-first analytics that prioritise data ownership and compliance. Businesses using Matomo benefit from accurate insights while respecting user privacy.

  These companies demonstrate that ethical marketing is not just a compliance requirement—it is a long-term competitive advantage.

  Strategies for implementing ethical marketing

  Aligning marketing efforts with brand values

  Consistency between values and actions is essential for ethical marketing. This alignment starts with a clear understanding of what your organisation truly stands for—not just aspirational statements, but genuine commitments that inform daily decisions.

  Implementing this alignment requires cross-functional collaboration. Marketing teams need to work closely with product development, customer service, and leadership to ensure consistency across all touchpoints. When different departments send contradictory messages about company values, trust erodes quickly.

  Clear guidelines help marketing teams apply values in practical decisions, from campaign concepts to media placements. Regular ethical reviews of marketing plans can identify potential issues before campaigns launch, avoiding reactive corrections that damage credibility.

  Privacy-first data strategies

  Developing robust approaches to customer data is fundamental to ethical marketing. This starts with prioritising first-party data (collected directly from your own channels) and zero-party data (actively shared by customers through preference centres, surveys, and similar mechanisms).

  Measuring success doesn’t have to come at the expense of privacy. Ethical analytics provide accurate insights while protecting user data, ensuring compliance, and enhancing customer trust.

  Ethical personalisation approaches focus on using aggregated or anonymised data rather than individual tracking. This allows for relevant experiences without the invasive feeling that erodes trust when consumers feel watched across the internet.

  Most importantly, ethical data strategies create transparent value exchanges where users clearly understand what benefits they receive in return for sharing information. This reciprocity transforms data collection from exploitation to fair exchange.

  Measuring success ethically

  Traditional marketing measurement often relies on individual-level tracking across sites and platforms. Ethical approaches require adapting these frameworks to respect privacy while still demonstrating impact.

  Focusing on aggregate patterns rather than individual behaviour provides valuable insights without privacy invasions. For example, understanding that 30% of visitors to a specific page subsequently make purchases is actionable intelligence that doesn’t require tracking specific people.

  Incrementality testing measures campaign impact by comparing outcomes between exposed and control groups at an aggregate level. This provides more accurate attribution than traditional last-click models while respecting privacy boundaries.

  Server-side conversion tracking offers another ethical measurement approach, collecting necessary data on your servers rather than through client-side scripts vulnerable to blocking. This improves data accuracy while reducing reliance on cookies and browser storage.

  Implementing ethical marketing strategies : A practical framework

  1. Align marketing with brand values – Ensure campaigns reflect transparency and trust

  2. Leverage first-party data – Collect insights directly from consumers with clear consent

  3. Respect privacy and consent – Give users control over their data and clearly communicate its use

  4. Create value-driven content – Offer educational and relevant resources instead of relying solely on advertising

  5. Use privacy-compliant analytics – Switch to ethical platforms such as Matomo for responsible performance measurement

  For a step-by-step guide to implementing ethical marketing strategies, download the full report here.

  

  The future of ethical marketing

  With the decline of third-party cookies and the rise of privacy regulations, ethical marketing is no longer optional. Brands that adopt privacy-first practices now will gain a sustainable competitive edge in the long term. The future of marketing belongs to brands that earn consumer trust, not those that exploit it.

  Key trends shaping the future of marketing include :

  • Privacy-first analytics to replace invasive tracking
  • First-party and zero-party data strategies for direct consumer engagement
  • Consent-driven personalisation to balance relevance and privacy
  • Greater emphasis on corporate social responsibility in marketing initiatives

  Companies that proactively address these changes will build stronger customer relationships, enhance brand reputation, and ensure long-term success.

  Take the next step

  Ready to transform your marketing approach for 2025 and beyond ?

  Download Matomo’s comprehensive “2025 Ethical Marketing Field Guide” to get practical frameworks, implementation strategies, and real-world case studies that will help you build trust while driving growth.

  With detailed guidance on first-party data activation, consent-based personalisation techniques, and privacy-preserving analytics methods, this guide provides everything you need to future-proof your marketing strategy in a privacy-first world.

  

  Download the ethical marketing guide now to start building stronger, more trusted relationships with your customers through ethical marketing practices.

• CCPA vs GDPR : Understanding Their Impact on Data Analytics

  19 mars, par Alex Carmona

  With over 400 million internet users in Europe and 331 million in the US (11% of which reside in California alone), understanding the nuances of privacy laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) is crucial for compliant and ethical consumer data collection.

  Navigating this compliance landscape can be challenging for businesses serving European and Californian markets.

  This guide explores the key differences between CCPA and GDPR, their impact on data analytics, and how to ensure your business meets these essential privacy requirements.

  What is the California Consumer Privacy Act (CCPA) ?

  The California Consumer Privacy Act (CCPA) is a data privacy law that gives California consumers control over their personal information. It applies to for-profit businesses operating in California that meet specific criteria related to revenue, data collection and sales.

  Origins and purpose

  The CCPA addresses growing concerns about data privacy and how businesses use personal information in California. The act passed in 2018 and went into effect on 1 January 2020.

  Key features

  • Grants consumers the right to know what personal information is collected
  • Provides the right to delete personal information
  • Allows consumers to opt out of the sale of their personal information
  • Prohibits discrimination against consumers who exercise their CCPA rights

  Key definitions under the CCPA framework

  • Business : A for-profit entity doing business in California and meeting one or more of these conditions :
    • Has annual gross revenues over $25 million ;
    • Buys, receives, sells or shares 50,000 or more consumers’ personal information ; or
    • Derives 50% or more of its annual revenues from selling consumers’ personal information
  • Consumer : A natural person who is a California resident
  • Personal Information : Information that could be linked to, related to or used to identify a consumer or household, such as online identifiers, IP addresses, email addresses, social security numbers, cookie identifiers and more

  What is the General Data Protection Regulation (GDPR) ?

  The General Data Protection Regulation (GDPR) is a data privacy and protection law passed by the European Union (EU). It’s one of the strongest and most influential data privacy laws worldwide and applies to all organisations that process the personal data of individuals in the EU.

  Origins and purpose

  The GDPR was passed in 2016 and went into effect on 25 May 2018. It aims to harmonise data privacy laws in Europe and give people in the European Economic Area (EEA) privacy rights and control over their data.

  Key features

  • Applies to all organisations that process the personal data of individuals in the EEA
  • Grants individuals a wide range of privacy rights over their data
  • Requires organisations to obtain explicit and informed consent for most data processing
  • Mandates appropriate security measures to protect personal data
  • Imposes significant fines and penalties for non-compliance

  Key definitions under the GDPR framework

  • Data Subject : An identified or identifiable person
  • Personal Data : Any information relating to a data subject
  • Data Controller : The entity or organisation that determines how personal data is processed and what for
  • Data Processor : The entity or organisation that processes the data on behalf of the controller

  CCPA vs. GDPR : Key similarities

  The CCPA and GDPR enhance consumer privacy rights and give individuals greater control over their data.

  Dimension	CCPA	GDPR
  Purpose	Protect consumer privacy	Protect individual data rights
  Key Rights	Right to access, delete and opt out of sale	Right to access, rectify, erase and restrict processing
  Transparency	Requires transparency around data collection and use	Requires transparency about data collection, processing and use

  CCPA vs. GDPR : Key differences

  While they have similar purposes, the CCPA and GDPR differ significantly in their scope, approach and specific requirements.

  Dimension	CCPA	GDPR
  Scope	For-profit businesses only	All organisations processing EU consumer data
  Territorial Reach	California-based natural persons	All data subjects within the EEA
  Consent	Opt-out system	Opt-in system
  Penalties	Per violation based on its intentional or negligent nature	Case-by-case based on comprehensive assessment
  Individual Rights	Narrower (relative to GDPR)	Broader (relative to CCPA)

  CCPA vs. GDPR : A multi-dimensional comparison

  The previous sections gave a broad overview of the similarities and differences between CCPA and GDPR. Let’s now examine nine key dimensions where these regulations converge or diverge and discuss their impact on data analytics.

  

  #1. Scope and territorial reach

  The GDPR has a much broader scope than the CCPA. It applies to all organisations that process the personal data of individuals in the EEA, regardless of their business model, purpose or physical location.

  The CCPA applies to medium and large for-profit businesses that derive a substantial portion of their earnings from selling Californian consumers’ personal information. It doesn’t apply to non-profits, government agencies or smaller for-profit companies.

  Impact on data analytics

  The difference in scope significantly impacts data analytics practices. Smaller businesses may not need to comply with either regulation, some may only need to follow the CCPA, while most global businesses must comply with both. This often requires different methods for collecting and processing data in California, Europe, and elsewhere.

  #2. Penalties and fines for non-compliance

  Both the CCPA and GDPR impose penalties for non-compliance, but the severity of fines differs significantly :

  CCPA	Maximum penalty
  	$2,500 per unintentional violation $7,500 per intentional violation

  “Per violation” means per violation per impacted consumer. For example, three intentional CCPA violations affecting 1,000 consumers would result in 3,000 total violations and a $22.5 million maximum penalty (3,000 × $7,500).

  

  The largest CCPA fine to date was Zoom’s $85 million settlement in 2021.

  

  In contrast, the GDPR has resulted in 2,248 fines totalling almost €6.6 billion since 2018 — €2.4 billion of which were for non-compliance.

  GDPR	Maximum penalty
  	€20 million or 4% of all revenue earned the previous year

  So far, the biggest fine imposed under the GDPR was Meta’s €1.2 billion fine in May 2023 — 15 times more than Zoom had to pay California.

  Impact on data analytics

  The significant difference in potential fines demonstrates the importance of regulatory compliance for data analytics professionals. Non-compliance can have severe financial consequences, directly affecting budget allocation and business operations.

  Businesses must ensure their data collection, storage and processing practices comply with regulations in both Europe and California.

  Choosing privacy-first, compliance-ready analytics platforms like Matomo is instrumental for mitigating non-compliance risks.

  #3. Data subject rights and consumer rights

  The CCPA and GDPR give people similar rights over their data, but their limitations and details differ.

  Rights common to the CCPA and GDPR

  • Right to Access/Know : People can access their personal information and learn what data is collected, its source, its purpose and how it’s shared
  • Right to Delete/Erasure : People can request the deletion of their personal information, with some exceptions
  • Right to Non-Discrimination : Businesses can’t discriminate against people who exercise their privacy rights

  Consumer rights unique to the CCPA

  • Right to Opt Out of Sale : Consumers can prohibit the sale of their personal information
  • Right to Notice : Businesses must inform consumers about data collection practices
  • Right to Disclosure : Consumers can request specific information collected about them

  Data subject rights unique to the GDPR

  • Right to be Informed : Broader transparency requirements encompass data retention, automated decision-making and international transfers
  • Right to Rectification : Data subjects may request the correction of inaccurate data
  • Right to Restrict Processing : Consumers may limit data use in certain situations
  • Right to Data Portability : Businesses must provide individual consumer data in a secure, portable format when requested
  • Right to Withdraw Consent : Consumers may withdraw previously granted consent to data processing

  	CCPA	GDPR
  Right to Access or Know	✓	✓
  Right to Delete or Erase	✓	✓
  Right to Non-Discrimination	✓	✓
  Right to Opt-Out	✓
  Right to Notice	✓
  Right to Disclosure	✓
  Right to be Informed		✓
  Right to Rectification		✓
  Right to Restrict Processing		✓
  Right to Data Portability		✓
  Right to Withdraw Consent		✓

  Impact on data analytics

  Data analysts must understand these rights and ensure compliance with both regulations, which could potentially require separate data handling processes for EU and California consumers.

  #4. Opt-out vs. opt-in

  The CCPA generally follows an opt-out model, while the GDPR requires explicit consent from individuals before processing their data.

  Impact on data analytics

  For CCPA compliance, businesses can collect data by default if they provide opt-out mechanisms. Failing to process opt-out requests can result in severe penalties, like Sephora’s $1.2 million fine.

  Under GDPR, organisations must obtain explicit consent before collecting any data, which can limit the amount of data available for analysis.

  #5. Parental consent

  The CCPA and GDPR have provisions regarding parental consent for processing children’s data. The CCPA requires parental consent for children under 13, while the GDPR sets the age at 16, though member states can lower it to 13.

  Impact on data analytics

  This requirement significantly impacts businesses targeting younger audiences. In Europe and the US, companies must implement different methods to verify users’ ages and obtain parental consent when necessary.

  The California Attorney General’s Office recently fined Tilting Point Media LLC $500,000 for sharing children’s data without parental consent.

  #6. Data security requirements

  Both regulations require businesses to implement adequate security measures to protect personal data. However, the GDPR has more prescriptive requirements, outlining specific security measures and emphasising a risk-based approach.

  Impact on data analytics

  Data analytics professionals must ensure that data is processed and stored securely to avoid breaches and potential fines.

  #7. International data transfers

  Both the CCPA and GDPR address international data transfers. Under the CCPA, businesses must only inform consumers about international transfers. The GDPR has stricter requirements, including ensuring adequate data protection safeguards for transfers outside the EEA.

  

  Other rules, like the Payment Services Directive 2 (PSD2), also affect international data transfers, especially in the financial industry.

  PSD2 requires strong customer authentication and secure communication channels for payment services. This adds complexity to cross-border data flows.

  Impact on data analytics

  The primary impact is on businesses serving European residents from outside Europe. Processing data within the European Union is typically advisable. Meta’s record-breaking €1.2 billion fine was specifically for transferring data from the EEA to the US without sufficient safeguards.

  Choosing the right analytics platform helps avoid these issues.

  For example, Matomo offers a free, open-source, self-hosted analytics platform you can deploy anywhere. You can also choose a managed, GDPR-compliant cloud analytics solution with all data storage and processing servers within the EU (in Germany), ensuring your data never leaves the EEA.

  #8. Enforcement mechanisms

  The California Attorney General is responsible for enforcing CCPA requirements, while in Europe, the Data Protection Authority (DPA) in each EU member state enforces GDPR requirements.

  Impact on data analytics

  Data analytics professionals should be familiar with their respective enforcement bodies and their powers to support compliance efforts and minimise the risk of fines and penalties.

  #9. Legal basis for personal data processing

  The GDPR outlines six legal grounds for processing personal data :

  • Consent
  • Contract
  • Legal obligation
  • Vital interests
  • Public task
  • Legitimate interests

  The CCPA doesn’t explicitly define lawful bases but focuses on consumer rights and transparency in general.

  Impact on data analytics

  Businesses subject to the GDPR must identify and document a valid lawful basis for each processing activity.

  Compliance rules under CCPA and GDPR

  Complying with the CCPA and GDPR requires a comprehensive approach to data privacy. Here’s a summary of the essential compliance rules for each framework :

  

  CCPA compliance rules

  • Create clear and concise privacy policies outlining data collection and use practices
  • Give consumers the right to opt-out
  • Respond to consumer requests to access, delete and correct their personal information
  • Implement reasonable security measures for consumers’ personal data protection
  • Never discriminate against consumers who exercise their CCPA rights

  GDPR compliance rules

  • Obtain explicit and informed consent for data processing activities
  • Implement technical and organisational controls to safeguard personal data
  • Designate a Data Protection Officer (DPO) if necessary
  • Perform data protection impact assessments (DPIAs) for high-risk processing activities
  • Maintain records of processing activities
  • Promptly report data breaches to supervisory authorities

  Navigating the CCPA and GDPR with confidence

  Understanding the nuances of the CCPA and GDPR is crucial for businesses operating in the US and Europe. These regulations significantly impact data collection and analytics practices.

  Implementing robust data security practices and prioritising privacy and compliance are essential to avoid severe penalties and build trust with today’s privacy-conscious consumers.

  Privacy-centric analytics platforms like Matomo enable businesses to collect, analyse and use data responsibly and transparently, extracting valuable insights while maintaining compliance with both CCPA and GDPR requirements.

  Start your 21-day free trial today !

  no credit card required

• Can't set seeker in GSTREAMER cv2, python

  29 avril, par Alperen Ölçer

  I want to skip n seconds forward and backward in gstreamer cv2 capture for recorded videos. But when I use cap_gstreamer.set(cv2.CAP_PROP_POS_FRAMES, fps*skip_second) it resets seeker to beginning of video. How can I solve it ? I wrote an example, used recorded clock video.

  


  import cv2

video_p = '/home/alperenlcr/Videos/clock.mp4'

cap_gstreamer = cv2.VideoCapture(video_p, cv2.CAP_GSTREAMER)
cap_ffmpeg = cv2.VideoCapture(video_p, cv2.CAP_FFMPEG)

fps = cap_gstreamer.get(cv2.CAP_PROP_FPS)
skip_second = 100

im1 = cv2.resize(cap_gstreamer.read()[1], (960, 540))
im1_ffmpeg = cv2.resize(cap_ffmpeg.read()[1], (960, 540))

cap_gstreamer.set(cv2.CAP_PROP_POS_FRAMES, fps*skip_second)
cap_ffmpeg.set(cv2.CAP_PROP_POS_FRAMES, fps*skip_second)

im2 = cv2.resize(cap_gstreamer.read()[1], (960, 540))
im2_ffmpeg = cv2.resize(cap_ffmpeg.read()[1], (960, 540))

merge_gstreamer = cv2.hconcat([im1, im2])
merge_ffmpeg = cv2.hconcat([im1_ffmpeg, im2_ffmpeg])

cv2.imshow(str(skip_second) + ' gstreamer', merge_gstreamer)
cv2.imshow(str(skip_second) + ' ffmpeg', merge_ffmpeg)
cv2.waitKey(0)
cv2.destroyAllWindows()

cap_gstreamer.release()
cap_ffmpeg.release()



  


  Result :


  


  My cv2 build is like :

  


  >>> print(cv2.getBuildInformation())

General configuration for OpenCV 4.8.1 =====================================
  Version control:               4.8.1-dirty

  Extra modules:
    Location (extra):            /home/alperenlcr/SourceInstalls/opencv_contrib/modules
    Version control (extra):     4.8.1

  Platform:
    Timestamp:                   2024-12-02T13:44:58Z
    Host:                        Linux 6.8.0-49-generic x86_64
    CMake:                       3.22.1
    CMake generator:             Unix Makefiles
    CMake build tool:            /usr/bin/gmake
    Configuration:               RELEASE

  CPU/HW features:
    Baseline:                    SSE SSE2 SSE3
      requested:                 SSE3
    Dispatched code generation:  SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX
      requested:                 SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX
      SSE4_1 (18 files):         + SSSE3 SSE4_1
      SSE4_2 (2 files):          + SSSE3 SSE4_1 POPCNT SSE4_2
      FP16 (1 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
      AVX (8 files):             + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
      AVX2 (37 files):           + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2
      AVX512_SKX (8 files):      + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_COMMON AVX512_SKX

  C/C++:
    Built as dynamic libs?:      NO
    C++ standard:                11
    C++ Compiler:                /usr/bin/c++  (ver 10.5.0)
    C++ flags (Release):         -fsigned-char -ffast-math -W -Wall -Wreturn-type -Wnon-virtual-dtor -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG  -DNDEBUG
    C++ flags (Debug):           -fsigned-char -ffast-math -W -Wall -Wreturn-type -Wnon-virtual-dtor -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -g  -O0 -DDEBUG -D_DEBUG
    C Compiler:                  /usr/bin/cc
    C flags (Release):           -fsigned-char -ffast-math -W -Wall -Wreturn-type -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fvisibility=hidden -O3 -DNDEBUG  -DNDEBUG
    C flags (Debug):             -fsigned-char -ffast-math -W -Wall -Wreturn-type -Waddress -Wsequence-point -Wformat -Wformat-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fvisibility=hidden -g  -O0 -DDEBUG -D_DEBUG
    Linker flags (Release):      -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a   -Wl,--gc-sections -Wl,--as-needed -Wl,--no-undefined  
    Linker flags (Debug):        -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a   -Wl,--gc-sections -Wl,--as-needed -Wl,--no-undefined  
    ccache:                      NO
    Precompiled headers:         NO
    Extra dependencies:          /usr/lib/x86_64-linux-gnu/libjpeg.so /usr/lib/x86_64-linux-gnu/libpng.so /usr/lib/x86_64-linux-gnu/libtiff.so /usr/lib/x86_64-linux-gnu/libz.so /usr/lib/x86_64-linux-gnu/libfreetype.so /usr/lib/x86_64-linux-gnu/libharfbuzz.so Iconv::Iconv m pthread cudart_static dl rt nppc nppial nppicc nppidei nppif nppig nppim nppist nppisu nppitc npps cublas cudnn cufft -L/usr/lib/x86_64-linux-gnu -L/usr/lib/cuda/lib64
    3rdparty dependencies:       libprotobuf ade ittnotify libwebp libopenjp2 IlmImf quirc ippiw ippicv

  OpenCV modules:
    To be built:                 aruco bgsegm bioinspired calib3d ccalib core cudaarithm cudabgsegm cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev datasets dnn dnn_objdetect dnn_superres dpm face features2d flann freetype fuzzy gapi hfs highgui img_hash imgcodecs imgproc intensity_transform line_descriptor mcc ml objdetect optflow phase_unwrapping photo plot python3 quality rapid reg rgbd saliency shape stereo stitching structured_light superres surface_matching text tracking ts video videoio videostab wechat_qrcode xfeatures2d ximgproc xobjdetect xphoto
    Disabled:                    cudacodec world
    Disabled by dependency:      -
    Unavailable:                 alphamat cvv hdf java julia matlab ovis python2 sfm viz
    Applications:                tests perf_tests examples apps
    Documentation:               NO
    Non-free algorithms:         NO

  GUI:                           GTK2
    QT:                          NO
    GTK+:                        YES (ver 2.24.33)
      GThread :                  YES (ver 2.72.4)
      GtkGlExt:                  NO
    OpenGL support:              NO
    VTK support:                 NO

  Media I/O: 
    ZLib:                        /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.11)
    JPEG:                        /usr/lib/x86_64-linux-gnu/libjpeg.so (ver 80)
    WEBP:                        build (ver encoder: 0x020f)
    PNG:                         /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.6.37)
    TIFF:                        /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42 / 4.3.0)
    JPEG 2000:                   build (ver 2.5.0)
    OpenEXR:                     build (ver 2.3.0)
    HDR:                         YES
    SUNRASTER:                   YES
    PXM:                         YES
    PFM:                         YES

  Video I/O:
    DC1394:                      NO
    FFMPEG:                      YES
      avcodec:                   YES (58.134.100)
      avformat:                  YES (58.76.100)
      avutil:                    YES (56.70.100)
      swscale:                   YES (5.9.100)
      swresample:                YES (3.9.100)
    GStreamer:                   YES (1.20.3)
    v4l/v4l2:                    YES (linux/videodev2.h)

  Parallel framework:            TBB (ver 2021.5 interface 12050)

  Trace:                         YES (with Intel ITT)

  Other third-party libraries:
    Intel IPP:                   2021.8 [2021.8.0]
           at:                   /home/alperenlcr/SourceInstalls/opencv/build/3rdparty/ippicv/ippicv_lnx/icv
    Intel IPP IW:                sources (2021.8.0)
              at:                /home/alperenlcr/SourceInstalls/opencv/build/3rdparty/ippicv/ippicv_lnx/iw
    VA:                          NO
    Lapack:                      NO
    Eigen:                       NO
    Custom HAL:                  NO
    Protobuf:                    build (3.19.1)
    Flatbuffers:                 builtin/3rdparty (23.5.9)

  NVIDIA CUDA:                   YES (ver 11.5, CUFFT CUBLAS NVCUVID NVCUVENC FAST_MATH)
    NVIDIA GPU arch:             86
    NVIDIA PTX archs:

  cuDNN:                         YES (ver 8.6.0)

  OpenCL:                        YES (no extra features)
    Include path:                /home/alperenlcr/SourceInstalls/opencv/3rdparty/include/opencl/1.2
    Link libraries:              Dynamic load

  ONNX:                          NO

  Python 3:
    Interpreter:                 /usr/bin/python3 (ver 3.10.12)
    Libraries:                   /usr/lib/x86_64-linux-gnu/libpython3.10.so (ver 3.10.12)
    numpy:                       /usr/lib/python3/dist-packages/numpy/core/include (ver 1.21.5)
    install path:                lib/python3.10/dist-packages/cv2/python-3.10

  Python (for build):            /usr/bin/python3

  Java:                          
    ant:                         NO
    Java:                        NO
    JNI:                         NO
    Java wrappers:               NO
    Java tests:                  NO

  Install to:                    /usr/local
-----------------------------------------------------------------