Nanonets
Docsumo
DocParser
DocuClipper
Rossum
Nanonets OCR
Invoice Data Extraction
Free Online OCR [Docsumo]
OCR.Space Free OCR API
python pdf
PDF-XChange Editor
Adobe PDF Editor
PDF Editify
Foxit PhantomPDF
Onlineocr.net
ApowerPDF
NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
Nanonets OCR.Space Free OCR APINo features have been listed yet.
Nanonets is particularly recommended for businesses of all sizes that deal with large volumes of documents and require efficient data extraction and automation. Industries like finance, healthcare, logistics, and retail, which often handle invoices, forms, and contracts, can benefit significantly. It's also suitable for developers looking for an API solution to integrate OCR capabilities into their own applications.
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Based on our record, Nanonets should be more popular than OCR.Space Free OCR API. It has been mentiond 6 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.
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: almost 3 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: almost 3 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: about 3 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 3 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 3 years ago
We scan everything with ocr functionallity by an office all-in one printer by canon. So a big portion of the files will be searchable anyways. The rest of the files can be uploaded to https://ocr.space/ocrapi. To extract the text in a filemaker textfield I use the MBS Plugin which is highly recommended anyway with the following call: MBS( "PDFKit.GetPDFText"; MEDIEN::Container_m ). Source: almost 3 years ago
Are you okay with paying for APIs? If so fair enough: https://ocr.space/ocrapi or browse https://rapidapi.com/marketplace for a good OCR API. As far as I know the only way to do it within python is with tesseract, which you could look into. Here's a resource on dealing with the PDF part. Source: almost 4 years ago
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
python pdf - In this step-by-step tutorial, you'll learn how to work with a PDF in Python. You'll see how to extract metadata from preexisting PDFs . You'll also learn how to merge, split, watermark, and rotate pages in PDFs using Python and PyPDF2.
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.
PDF-XChange Editor - The smallest, fastest, most feature-rich PDF editor/viewer available
DocuClipper - Automate data extraction from bank statements, invoices, tax forms and more.
Adobe PDF Editor - Learn how to edit PDF files using Adobe Acrobat DC and change text and images quickly and easily in PDF documents. Start your free trial and try the PDF editor.
