TextSniper VS Nanonets

TextSniper is an easy-to-use desktop Mac OCR app that can extract and recognize any non-searchable and non-editable text on your Mac's screen. As an extra feature, it can turn OCR text into speech. It is a super convenient alternative to complicated optical character recognition tools.

The tool is intuitive to use and makes extracting text from your images, scanned paper documents, PDFs, or even videos simple and easy. No training or special skills required, fits perfectly home and business mac users. Easily accessible from the menu bar whenever you need it and has a simple user interface.

If you ever have used a built-in mac's screen capture application before, then it wouldn't be any trouble to work with TextSniper too. Select with a mouse any part of an image, photo, PDF document, or anything on your screen, and the app will process and recognize any text within this selection. The text output will be saved into a clipboard, so you could paste it into your favorite macOS text editing or note-taking software.

Finally, the app's optical character recognition engine doesn't need an internet connection to process documents. Great OCR solution for those who are concerned about privacy. The application does not collect any users' data.

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