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Dillinger VS OpenCV

Compare Dillinger VS OpenCV and see what are their differences

DocRaptor
As the only API powered by the Prince HTML-to-PDF engine, DocRaptor provides the best support for complex PDFs with powerful support for headers, page breaks, page numbers, flexbox, watermarks, accessible PDFs, and much more featured
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Dillinger logo Dillinger

joemccann has 95 repositories available. Follow their code on GitHub.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Dillinger Landing page
    Landing page //
    2024-10-09
  • OpenCV Landing page
    Landing page //
    2023-07-29

Dillinger features and specs

  • Real-time Markdown Rendering
    Dillinger provides live rendering of Markdown text, allowing users to see a side-by-side preview of their formatted text.
  • Cloud Integration
    It offers integration with cloud services like Dropbox, Google Drive, OneDrive, and GitHub, making it easy to save and manage documents.
  • User-friendly Interface
    The platform boasts an intuitive and clean interface, which makes it easy for both beginners and experienced users to navigate and use effectively.
  • Export Options
    Dillinger supports exporting documents in multiple formats, including Markdown, HTML, and PDF, providing flexibility in how users can use their content.
  • Open Source
    As an open-source platform, Dillinger allows developers to contribute to the project or customize the tool for their specific needs.

Possible disadvantages of Dillinger

  • Limited Offline Support
    Dillinger is primarily a web-based application and requires an internet connection for full functionality, limiting its usability offline.
  • Basic Markdown Features
    While it covers the basics well, advanced Markdown features or plugins might be missing compared to more comprehensive editors.
  • Dependency on External Services
    Heavy reliance on third-party cloud services may be a drawback for users who prefer to keep their data localized or have privacy concerns.
  • No Native Desktop Application
    Dillinger does not offer a native desktop application, which might be a disadvantage for users who prefer or require desktop-based tools.
  • Limited Customization
    While the interface is user-friendly, it offers limited customization options in terms of themes and editor settings compared to some other Markdown editors.

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.

Dillinger videos

+ Add

The Dillinger Escape Plan - Dissociation ALBUM REVIEW

More videos:

  • Review - The Dillinger Escape Plan - One Of Us Is The Killer ALBUM REVIEW
  • Review - DILLINGER ESCAPE PLAN Dissociation Album Review | Overkill Reviews

OpenCV videos

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AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Dillinger and OpenCV)

Dillinger

OpenCV

Markdown Editor
100 100%
Markdown Editor
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Text Editors
100 100%
Text Editors
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 Dillinger and OpenCV

Dillinger Reviews

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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 should be more popular than Dillinger. It has been mentiond 60 times since March 2021. 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.

Dillinger mentions (26)

  • Markdown Syntax & Features: A Comprehensive 2025 Guide
    Dillinger - A cloud-enabled, mobile-ready, offline-storage, AngularJS-powered, HTML5 Markdown editor. - Source: dev.to / 4 months ago
  • 100+ Must-Have Web Development Resources
    Dillinger: An online editor that offers cloud storage and supports various export formats like HTML5 and PDF. - Source: dev.to / 7 months ago
  • Converting Markdown to PDF
    Simply access https://dillinger.io and paste your markdown code there. It has the option to export to PDF, as well as some other formats. - Source: dev.to / 10 months ago
  • Building a simple but scalable blog using Astro
    I have used Markdown before (https://dillinger.io/) so wouldn't have a problem with using it again as long as on page SEO isn't any extra effort. I am not sure how I would use Markdown and then add the content to the blog to be deployed and if that is going to be much harder than a headless CMS, I would go for the headless. Source: over 1 year ago
  • Getting Started with Git and GitHub: A simple roadmap
    Useful rescources for this are: Markdown Cheatsheet and Markdown Editor. - Source: dev.to / almost 2 years ago
View more

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 / 9 days ago
  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 23 days 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 / 5 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 / 6 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 / 8 months ago
View more

What are some alternatives?

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

Typora - A minimal Markdown reading & writing app.

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

StackEdit - Full-featured, open-source Markdown editor based on PageDown, the Markdown library used by Stack Overflow and the other Stack Exchange sites.

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

Markdown by DaringFireball - Text-to-HTML conversion tool/syntax for web writers, by John Gruber

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

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