Google Cloud Vision API vs Tesseract OCR

Overview

Tesseract OCR

Stacks96

Followers286

Votes7

GitHub Stars70.7K

Forks10.4K

Google Cloud Vision API

Stacks139

Followers276

Votes16

Google Cloud Vision API vs Tesseract OCR: What are the differences?

Introduction

In this Markdown document, we will compare and highlight the key differences between Google Cloud Vision API and Tesseract OCR.

Accuracy: Google Cloud Vision API utilizes state-of-the-art machine learning models to deliver highly accurate results. It supports a wide range of image recognition tasks with excellent precision. On the other hand, Tesseract OCR is an open-source OCR engine that performs well for standard text recognition, but may not deliver the same level of accuracy for complex or specialized image recognition tasks.
Ease of Use: Google Cloud Vision API offers a user-friendly interface and provides comprehensive documentation, making it easy for developers to integrate image recognition capabilities into their applications. Tesseract OCR, while also accessible, may require additional configuration and customization to achieve optimal results, especially for more complex scenarios.
Language Support: Google Cloud Vision API supports a wide range of languages for text recognition, including both Latin-based and non-Latin scripts. It offers robust language detection and supports text in multiple languages within a single image. Tesseract OCR, while capable of recognizing various languages, may have limitations when it comes to complex scripts or rare languages, as it relies heavily on training data availability.
Additional Features: Apart from optical character recognition, Google Cloud Vision API offers additional features like face detection, image labeling, landmark recognition, and content moderation. These features enable developers to build more advanced image recognition applications. Tesseract OCR, being primarily an OCR engine, focuses solely on text recognition without offering extended functionalities like face detection or image labeling.
Scalability and Performance: Google Cloud Vision API operates as a cloud-based service, allowing for easy scalability based on application requirements. It provides high performance and can handle large volumes of image processing requests efficiently. Tesseract OCR, being an open-source engine, may face limitations in terms of scalability and might require additional resources for handling high-volume image recognition tasks.
Cost Considerations: Google Cloud Vision API is a commercial service and charges are based on the number of API requests made and the additional features used. While it offers premium capabilities, this might come with associated costs. Tesseract OCR, being an open-source solution, is free to use, making it a cost-effective option for basic text recognition needs.

In summary, Google Cloud Vision API provides highly accurate results with robust language support, additional features, and scalability options, but comes with associated costs. Tesseract OCR, as an open-source OCR engine, offers a cost-effective solution with decent accuracy for standard text recognition needs, but may lack some of the advanced features and scalability of Google Cloud Vision API.

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Advice on Tesseract OCR, Google Cloud Vision API

Vladyslav

Sr. Directory of Technology at Shelf

Oct 25, 2019

Decided

AWS Rekognition has an OCR feature but can recognize only up to 50 words per image, which is a deal-breaker for us. (see my tweet).

Also, we discovered fantastic speed and quality improvements in the 4.x versions of Tesseract. Meanwhile, the quality of AWS Rekognition's OCR remains to be mediocre in comparison.

We run Tesseract serverlessly in AWS Lambda via aws-lambda-tesseract library that we made open-source.

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Detailed Comparison

Tesseract OCR	Google Cloud Vision API
Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. Since 2006 it is developed by Google.	Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API.
-	Powerful Image Analysis; Insight From Your Images; Detect Inappropriate Content; Image Sentiment Analysis; Extract Text
Statistics
GitHub Stars 70.7K	GitHub Stars -
GitHub Forks 10.4K	GitHub Forks -
Stacks 96	Stacks 139
Followers 286	Followers 276
Votes 7	Votes 16
Pros & Cons
Pros 5 Building training set is easy 2 Very lightweight library Cons 1 Works best with white background and black text	Pros 9 Image Recognition 7 Built by Google

What are some alternatives to Tesseract OCR, Google Cloud Vision API?

Amazon Rekognition

Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications.

Tesseract.js

This library supports over 60 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browser and on a server with NodeJS.

Image to Prompt AI

Free AI-powered image to prompt generator. Upload images and get detailed prompts for AI art generation with our advanced converter.

Free AI Image Detector

Is this image AI-generated? Free AI detector with 99.7% accuracy detects fake photos, deepfakes, and AI images from DALL-E, Midjourney, Stable Diffusion. No signup required.

SAM 3D

Meta's SAM 3D brings human-level 3D perception to computer vision. Reconstruct objects and bodies from single images with unprecedented accuracy and speed.

libpng

It is the official Portable Network Graphics (PNG) reference library. It is a platform-independent library that contains C functions for handling PNG images. It supports almost all of PNG's features, is extensible, and has been widely used and tested.

OpenJPEG

It is an open-source JPEG 2000 codec written in C language.

ZXing

It is a barcode scanning library for Java, Android. Decode a 1D or 2D barcode from an image on the web.

EasyOCR

It is ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai.

libjpeg

It is a free library for JPEG image compression.

Related Comparisons

Google Cloud Vision API vs Tesseract OCR: What are the differences?

Introduction

In this Markdown document, we will compare and highlight the key differences between Google Cloud Vision API and Tesseract OCR.

Accuracy: Google Cloud Vision API utilizes state-of-the-art machine learning models to deliver highly accurate results. It supports a wide range of image recognition tasks with excellent precision. On the other hand, Tesseract OCR is an open-source OCR engine that performs well for standard text recognition, but may not deliver the same level of accuracy for complex or specialized image recognition tasks.
Ease of Use: Google Cloud Vision API offers a user-friendly interface and provides comprehensive documentation, making it easy for developers to integrate image recognition capabilities into their applications. Tesseract OCR, while also accessible, may require additional configuration and customization to achieve optimal results, especially for more complex scenarios.
Language Support: Google Cloud Vision API supports a wide range of languages for text recognition, including both Latin-based and non-Latin scripts. It offers robust language detection and supports text in multiple languages within a single image. Tesseract OCR, while capable of recognizing various languages, may have limitations when it comes to complex scripts or rare languages, as it relies heavily on training data availability.
Additional Features: Apart from optical character recognition, Google Cloud Vision API offers additional features like face detection, image labeling, landmark recognition, and content moderation. These features enable developers to build more advanced image recognition applications. Tesseract OCR, being primarily an OCR engine, focuses solely on text recognition without offering extended functionalities like face detection or image labeling.
Scalability and Performance: Google Cloud Vision API operates as a cloud-based service, allowing for easy scalability based on application requirements. It provides high performance and can handle large volumes of image processing requests efficiently. Tesseract OCR, being an open-source engine, may face limitations in terms of scalability and might require additional resources for handling high-volume image recognition tasks.
Cost Considerations: Google Cloud Vision API is a commercial service and charges are based on the number of API requests made and the additional features used. While it offers premium capabilities, this might come with associated costs. Tesseract OCR, being an open-source solution, is free to use, making it a cost-effective option for basic text recognition needs.

Google Cloud Vision API vs Tesseract OCR

Overview

Google Cloud Vision API vs Tesseract OCR: What are the differences?