Software Alternatives & Reviews

ABBYY VS OpenCV

Compare ABBYY VS OpenCV and see what are their differences

ABBYY logo ABBYY

ABBYY's leading AI and machine learning technology solutions range from process analysis, data capture, pdf editor, text and content recognition (OCR) and extraction, combining process and content insights to deliver digital intelligence.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • ABBYY Landing page
    Landing page //
    2022-05-04
  • OpenCV Landing page
    Landing page //
    2023-07-29

ABBYY videos

ABBYY Lingvo Dictionaries - Live-translation

More videos:

  • Review - ABBYY FineReader 15 - Video Review
  • Review - ABBYY FineReader 14 Video Review
  • Review - ABBYY Lingvo x3.mp4
  • Review - Abbyy Finereader 15 Overview of OCR

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to ABBYY and OpenCV)
Translation Service
100 100%
0% 0
Data Science And Machine Learning
Localization
100 100%
0% 0
Data Science Tools
0 0%
100% 100

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Reviews

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

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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.
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.

Social recommendations and mentions

Based on our record, OpenCV seems to be more popular. It has been mentiond 50 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.

ABBYY mentions (0)

We have not tracked any mentions of ABBYY yet. Tracking of ABBYY recommendations started around Mar 2021.

OpenCV mentions (50)

  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
  • Looking for a Windows auto-clicker with conditions
    You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 5 months ago
  • Looking to recreate a cool AI assistant project with free tools
    - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 9 months ago
  • Looking to recreate a cool AI assistant project with free tools
    I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 9 months ago
  • What are the limits of blueprints?
    You also need C++ if you're going to do things which aren't built in as part of the engine. As an example if you're looking at using compute shaders, inbuilt native APIs such as a mobile phone's location services, or a third-party library such as OpenCV, then you're going to need C++. Source: 11 months ago
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What are some alternatives?

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

One Hour Translation - Professional translation services for 75 languages on a 24/7 basis.

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

Tomedes - Translation Services - 24 HR Service, Reliable, Great Prices. Get an Instant Free Quote!

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

Rev.com - Transcriptions, captions, and subtitles that are affordable, fast, and high-quality.

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