Software Alternatives & Reviews

Amazon Textract VS OpenCV

Compare Amazon Textract VS OpenCV and see what are their differences

Amazon Textract logo Amazon Textract

Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Amazon Textract Landing page
    Landing page //
    2023-04-13
  • OpenCV Landing page
    Landing page //
    2023-07-29

Amazon Textract videos

Amazon Textract: First Look

More videos:

  • Review - AWS re:Invent 2018 – Announcing Amazon Textract
  • Review - Introducing Amazon Textract: Now in Preview

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Amazon Textract and OpenCV)
OCR
63 63%
37% 37
Data Science And Machine Learning
Image Recognition
100 100%
0% 0
Data Science Tools
0 0%
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 Amazon Textract and OpenCV

Amazon Textract Reviews

2019 Examples to Compare OCR Services: Amazon Textract/Rekognition vs Google Vision vs Microsoft Cognitive Services
Pricing: Amazon Rekognition, Amazon Textract, Google, Microsoft. We don't really care which one you use, but Microsoft did best by our sample data. Textract was a very close second if you only need its headline feature: extracting text from digital documents. If someone wants to email bill -at- amplenote.com with comparable data for other images/services, I can try to...

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

OpenCV might be a bit more popular than Amazon Textract. We know about 50 links to it since March 2021 and only 34 links to Amazon Textract. 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.

Amazon Textract mentions (34)

  • Classifying and Extracting Data using Amazon Textract
    Amazon Textract has an Analyze Lending API for evaluating and categorizing the documents contained in mortgage loan application packages, as well as extracting the data they contain. The new API can assist in processing applications quicker and with minimal errors, therefore improving the end-customer experience and lowering operational costs. - Source: dev.to / 3 months ago
  • Ask HN: OCR for 100 year old (German) handwritten cursive script?
    You could try something like https://aws.amazon.com/textract/ or https://cloud.google.com/vision/docs/handwriting. Both have support for modern handwriting. I don't know if it will work with a script written a century ago though. - Source: Hacker News / 3 months ago
  • Deploy and Test AWS Step Functions with Node.js
    Create a main.js file inside the look-for-github-profile-step project folder. Implement the code that parses the resume and plucks the GitHub profile URL. This step function is responsible for using Textract (an AI service from AWS) and passing state back to the state machine. - Source: dev.to / 7 months ago
  • Automate invoice processing using AWS Textract
    The primary challenge in processing invoices is extracting the relevant data. This is where Amazon Textract can help. It is a service provided by Amazon Web Services (AWS) that uses advanced Machine Learning (ML) algorithms to automatically extract structured and unstructured data from scanned documents, images, and PDF files. It can detect typed and handwritten text in different types of documents including... - Source: dev.to / 8 months ago
  • Case study: PDF Insights with AWS Textract and OpenAI integration
    First, we’ve decided to leave open-source solutions behind. We’ve used AWS Textract to parse PDF files. This way we don’t rely on the internal structure of the PDF to get text from it (or to get nothing - like in the case of the Uber example). Textract uses OCR and machine learning to get not only text but also spatial information from the document. - Source: dev.to / 8 months ago
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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 / 4 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 Amazon Textract and OpenCV, you can also consider the following products

DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.

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

ABBYY FineReader - ABBYY's latest PDF editor software, FineReader 16 you can easily convert files like PDF to Excel, PDF to Word, edit, share, collaborate & more with this PDF editor!

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

FlexiCapture - ABBYY FlexiCapture brings together the best NLP, machine learning, and advanced recognition capabilities into a single, enterprise-scale platform to handle every type of document. Available in the Cloud, on premise or as SDK.

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