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  1. Stackups
  2. Utilities
  3. API Tools
  4. File Uploads
  5. Tesseract OCR vs Uploadcare

Tesseract OCR vs Uploadcare

OverviewDecisionsComparisonAlternatives

Overview

Uploadcare
Uploadcare
Stacks85
Followers122
Votes27
Tesseract OCR
Tesseract OCR
Stacks98
Followers287
Votes8
GitHub Stars70.7K
Forks10.4K

Tesseract OCR vs Uploadcare: What are the differences?

What is Tesseract OCR? Tesseract Open Source OCR Engine. 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.

What is Uploadcare? File uploads, media processing, and adaptive delivery for web and mobile. Uploadcare is a complete file handling platform for online business. Receive files from you users via File Uploader or File Upload API, implement image optimization and transformations with Image CDN API, and get HIPAA-compliant storage.

Tesseract OCR and Uploadcare are primarily classified as "Image Analysis API" and "File Uploads" tools respectively.

Tesseract OCR is an open source tool with 28.1K GitHub stars and 5.38K GitHub forks. Here's a link to Tesseract OCR's open source repository on GitHub.

According to the StackShare community, Uploadcare has a broader approval, being mentioned in 13 company stacks & 4 developers stacks; compared to Tesseract OCR, which is listed in 6 company stacks and 6 developer stacks.

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Advice on Uploadcare, Tesseract OCR

Vladyslav
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.

53.4k views53.4k
Comments

Detailed Comparison

Uploadcare
Uploadcare
Tesseract OCR
Tesseract OCR

Uploadcare is file management platform and a CDN for user-generated content. It is a robust file API for uploading, managing, processing, rendering, optimizing, and delivering users’ content.

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.

Stores files in Uploadcare Storage or connects to your AWS S3 buckets; Delivers content in an instant across 5 continents with Uploadcare CDN; Takes minutes to integrate thanks to series of guides for most popular Web platforms, programming languages, and frameworks; Well-documented and provides live chat or email support; Provides on-the-fly image processing and tools for editing images in desktop and mobile browsers; Lets you resize, crop, rotate, enhance, extract colors, detect faces, and whatnot; Provides REST API to manage your cloud storage; Lets you upload files from multiple sources using File Uploader, raw API, libraries or plugins; Provides HIPAA-compliance and PHI protection;
-
Statistics
GitHub Stars
-
GitHub Stars
70.7K
GitHub Forks
-
GitHub Forks
10.4K
Stacks
85
Stacks
98
Followers
122
Followers
287
Votes
27
Votes
8
Pros & Cons
Pros
  • 10
    Great team
  • 6
    Simple image upload with widget
  • 5
    Easy to integrate into any website
  • 5
    Awesome support
  • 1
    <a href="http://fixbit.com/">useful tool</a>
Cons
  • 1
    Upload widget is large (114KB)
  • 0
    no cons
Pros
  • 5
    Building training set is easy
  • 2
    Very lightweight library
Cons
  • 1
    Works best with white background and black text
Integrations
React
React
Stripe
Stripe
Google Drive
Google Drive
Squarespace
Squarespace
Django
Django
WordPress
WordPress
Shopify
Shopify
Zapier
Zapier
Rails
Rails
Ruby
Ruby
No integrations available

What are some alternatives to Uploadcare, Tesseract OCR?

Transloadit

Transloadit

Transloadit handles file uploading & file processing for your websites and mobile apps. We can process video, audio, images and documents.

Bytescale

Bytescale

Bytescale is the best way to serve images, videos, and audio for web apps. Includes: Fast CDN, Storage, and Media Processing APIs.

Google Cloud Vision API

Google Cloud Vision API

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.

Uppy

Uppy

Uppy is a sleek modular file uploader for web browsers. Add it to your app with one line of code, or build a custom version with just the plugins you need via Webpack/Browserify. 100% open source, backed by a company (Transloadit).

Filestack

Filestack

Filepicker helps developers connect to their users' content. Connect, Store, and Process any file from anywhere on the Internet.

Amazon Rekognition

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.

CarrierWave

CarrierWave

This gem provides a simple and extremely flexible way to upload files from Ruby applications. It works well with Rack based web applications, such as Ruby on Rails.

Tesseract.js

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.

jpg-to-excel-utils

jpg-to-excel-utils

A powerful image-to-table extraction utility. It allows developers to parse JPG/PNG images containing tabular data and convert them into machine-readable formats (Excel, CSV, JSON) for data processing pipelines.

AI Detect Lab

AI Detect Lab

A high-performance AI detection infrastructure designed to identify synthetic media. AI Detect Lab leverages advanced neural network analysis to distinguish between human-generated content and AI outputs (Midjourney v7, Stable Diffusion 3.5, DALL-E 3,Flux2.0) with 99%+ accuracy. Supports multi-language text analysis and high-resolution image processing via a streamlined web interface.

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