Welcome to the Perfectly Clear SDK!. This guide will explain how to use the Perfectly Clear SDK, Command Line application, or our Docker solution to enable fully-automatic or interactive image corrections in your applications. In the Table of Contents on the left, the first several pages provide an overview of the SDK. Next you'll find several examples for various platforms, and finally a full reference section.

NOTE: This version of the SDK requires using Presets from Workbench v4.6 or newer.

Perfectly Clear AI makes use of Artificial Intelligence tools for both AI Preset Detection as well as image corrections, together with our classical image correction suite, retouching correction tools, and creative LOOKs.

This SDK includes following main components:

Our Command Line Application - a ready-for-production application for Linux, Windows and Mac OS. It supports several workflow styles and wide array of processing controls. This is usually the fastest way to start using Perfectly Clear in server-side production environments.
The Docker Container solution - a ready-for-production "private" version of our WebAPI correction system. This docker container can be deployed in seconds, providing a self-hosted HTTP API to correct your photos.
The SDK for C and C# - libraries and sample projects to allow you to embed Perfectly Clear within new or existing applications that your team develops.
iOS and Android SDK's and sample projects

There are two main functional reference sections - one for the standard C library (PerfectlyClearPro.h), one for .NET development platform (PerfectlyClearAdapter.cs). The function names are very similar, and the calling patterns are nearly identical. They are easy to confuse when looking back and forth through examples and this document. The correction parameter structures are also slightly different across the three platforms. Our Perfectly Clear Workbench application allows exporting these parameters into code ready to copy/paste into your projects.

There are sample projects (Linux & OSX Sample Code, Windows Sample Code, C# Sample Code, iOS Sample Code) that show this in all platforms we support. Our sample applications also read and write from JPEG, PNG and WebP image files and well as images embedded in un-flattened PDF files, and can read .preset files, as exported from Perfectly Clear Workbench, to make setting the correction parameters as easy as possible.

This was build from 36f1832770069ee3bd2eacd045ed87ff42555cb9 on Wed 05-21-202514:17:22.97