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Checkmarx VS OpenCV

Compare Checkmarx VS OpenCV and see what are their differences

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Checkmarx logo Checkmarx

The industry’s most comprehensive AppSec platform, Checkmarx One is fast, accurate, and accelerates your business.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Checkmarx Landing page
    Landing page //
    2022-07-29
  • OpenCV Landing page
    Landing page //
    2023-07-29

Checkmarx features and specs

  • Comprehensive Coverage
    Checkmarx provides extensive support for multiple programming languages and frameworks, allowing for a broad range of applications to be scanned.
  • Integration Capabilities
    The platform integrates well with various DevOps tools and CI/CD pipelines, making it easier to incorporate security checks into the software development lifecycle.
  • Customization
    Offers highly customizable rule sets that can be tailored to specific security requirements and coding standards of the organization.
  • User-Friendly Interface
    Features an intuitive and easy-to-navigate user interface that allows users to efficiently manage and analyze security vulnerabilities.
  • Scalability
    Designed to scale efficiently, Checkmarx can handle large codebases and multiple projects concurrently without significant performance degradation.
  • Strong Reporting Capabilities
    Provides detailed and actionable reports that help developers and security teams quickly understand and address vulnerabilities.
  • Automation
    Supports automated scanning, which helps reduce manual efforts and accelerates the vulnerability detection process.

Possible disadvantages of Checkmarx

  • Cost
    Checkmarx can be expensive, especially for small to medium-sized organizations with limited budgets for security tools.
  • False Positives
    Although comprehensive, the platform sometimes generates false positives, which can lead to unnecessary work and distractions for development teams.
  • Learning Curve
    New users may face a steep learning curve due to the wide range of features and customization options available.
  • Performance Overhead
    In some cases, scanning large and complex codebases can be time-consuming and resource-intensive, potentially impacting development timelines.
  • Customer Support
    Some users have reported that customer support can be slow to respond and may not always provide satisfactory solutions to issues.
  • Initial Setup
    The initial setup process can be complex and time-consuming, requiring considerable effort to properly configure all settings and integrations.

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

Analysis of Checkmarx

Overall verdict

  • Yes, Checkmarx is generally regarded as a reliable and effective application security testing solution. Its robust features and proactive approach to identifying and mitigating security risks make it a valuable tool for organizations focused on maintaining a secure software development process.

Why this product is good

  • Checkmarx is considered a good choice for application security due to its comprehensive suite of tools designed to identify vulnerabilities early in the software development lifecycle. It offers features like Static Application Security Testing (SAST), Software Composition Analysis (SCA), and Interactive Application Security Testing (IAST). The platform provides a high level of accuracy, integrates well with various development environments, and supports numerous programming languages. Additionally, Checkmarx is known for its ease of use and detailed reporting capabilities, which help developers quickly address security issues.

Recommended for

  • Companies looking for a comprehensive application security platform.
  • Development teams that need seamless integration with CI/CD pipelines.
  • Organizations that require support for multiple programming languages.
  • Security professionals who prioritize early vulnerability detection and detailed reporting.

Analysis of OpenCV

Overall verdict

  • Yes, OpenCV is considered a good and reliable choice for computer vision tasks, particularly due to its extensive functionality, active community, and flexibility.

Why this product is good

  • OpenCV (Open Source Computer Vision Library) is widely regarded as a robust and versatile library for computer vision applications. It offers a comprehensive collection of functions and algorithms for image processing, video capture, machine learning, and more. Its open-source nature encourages community involvement, making it highly adaptable and continuously improving. OpenCV's cross-platform support and ease of integration with other libraries and languages further enhance its appeal.

Recommended for

  • Developers and researchers working on computer vision projects
  • People looking to implement real-time video analysis
  • Individuals exploring machine learning applications related to image and video processing
  • Anyone interested in experimenting with or learning computer vision concepts

Checkmarx videos

+ Add

Viewing results and understanding security issues via Checkmarx online scanner

More videos:

  • Demo - Checkmarx CxSAST Demonstration
  • Review - Meetups at Checkmarx: An Introduction to API Security
  • Review - Source code review with Checkmarx
  • Review - Checkmarx Results Review

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Checkmarx and OpenCV)

Checkmarx

OpenCV

Code Analysis
100 100%
Code Analysis
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Web Application Security
100 100%
Web Application Security
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Checkmarx and OpenCV

Checkmarx Reviews

The Top 11 Static Application Security Testing (SAST) Tools
Why We Picked Checkmarx SAST: We like Checkmarx SAST for its early detection of vulnerabilities, which enables faster and safer code development. Its AI-assisted prioritization of vulnerabilities according to severity and risk helps reduce false positives.
Source: expertinsights.com
Top 11 SonarQube Alternatives in 2024
Checkmarx is a developer-centric security tool that specializes in secure coding practices and compliance. It helps developers identify and fix security vulnerabilities in their code, ensuring that their applications are secure and compliant with regulatory standards. Checkmarx offers a range of tools and features to help developers build secure applications, including...
Source: www.codeant.ai
The 5 Best SonarQube Alternatives in 2024
While SonarQube offers some security features, Checkmarx provides a more holistic approach to application security, covering a more comprehensive range of security aspects throughout the SDLC. Checkmarx One's consolidation of multiple AppSec tools into a single platform could simplify management and reduce the total cost of ownership compared to using SonarQube alongside...
Source: blog.codacy.com
Ten Best SonarQube alternatives in 2021
CheckMarx has been used to test the programs to rectify vulnerability in the code and try the security lapses. Checkmarx is the software program exposure Platform for the enterprise. It has an impressive Codebashing characteristic that has the threshold over SonarQube. The software tracking-reporting function is good too. The "delta-experiment" function is it's far genuinely...
Source: duecode.io

OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, OpenCV seems to be a lot more popular than Checkmarx. While we know about 60 links to OpenCV, we've tracked only 3 mentions of Checkmarx. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Checkmarx mentions (3)

  • Penetration Testing for API Security: Protecting Digital Gateways
    Tools like SonarQube, Checkmarx, or Snyk can automate parts of this process by scanning for known vulnerability patterns. While white box testing may not reflect real-world attack scenarios (as attackers rarely access source code), it provides the most thorough assessment of security posture. - Source: dev.to / about 2 months ago
  • A Guide to DevSecOps with API Gateway
    Automate security testing: Use tools such as OWASP ZAP, SonarQube, or Checkmarx to automate security testing. This will help you identify security issues early in the development process and reduce the risk of vulnerabilities being introduced into your code. - Source: dev.to / over 2 years ago
  • 11 Top DevSecOps Tools
    Application Security (AppSec) is the forte of Checkmarx, which is an award-winning AppSec Testing tool that integrates security policies into the DevOps workflow and ensures security across the application lifecycle. Checkmarx scans all your code and provides actionable insights for critical vulnerabilities. Checkmarx also offers developer-friendly AppSec training that makes the transition to DevSecOps more... - Source: dev.to / over 3 years ago

OpenCV mentions (60)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / about 1 month ago
  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / about 2 months ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 6 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 7 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Checkmarx and OpenCV, you can also consider the following products

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Coverity Scan - Find and fix defects in your Java, C/C++ or C# open source project for free

NumPy - NumPy is the fundamental package for scientific computing with Python

Veracode - Veracode's application security software products are simpler and more scalable to increase the resiliency of your application infrastructure.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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