[![Optical mark recognition] We are pleased to announce the launch of Aspose.OMR Cloud. It deals with optical mark reader operations. Being a REST API with responses delivered in JSON format, it allows developers to add Optical Mark Recognition functionality to their applications using a simple set of requests. It can recognize optical marks from different types of documents with the ability to extract data from photos as well.
Aspose.OMR CloudWe would like to introduce Aspose.OMR Cloud, an intuitive REST API which is powerful enough to handle optical mark recognition. The main functionality of Aspose.OMR Cloud is to capture human-marked data from documents like surveys, questionnaires, examination papers etc. With the use of Aspose.OMR Cloud, it is possible to recognize scanned images and even photos with high accuracy. Recognition is processed based on a template mark-up that contains graphical mapping of the elements to be recognized from the scanned images.
API OverviewThe Aspose.OMR Cloud API is accessed via HTTP in the following format:
https://api.aspose.com/v1.1/omr/ ```Requests are sent in HTTP POST and server returns the response in JSON format. ## FeaturesThe list of supported functionality is given below: * Aspose.OMR Cloud performs recognition on the scanned images and photos. * It can process rotated and perspective corrupted (side viewed) images. * Ability to recognize data from tests, exams, questionnaires, surveys, etc is present in Aspose.OMR Cloud. * Our product team has made improvements to make OMR operation more fast and robust. * High recognition accuracy is another salient feature of Aspose.OMR Cloud. * Aspose.OMR Cloud offers the functionality to export the results to CSV file. * It allows addition, deletion of OMR elements from the uploaded template. ## LimitationsAspose.OMR Cloud is a fully equipped REST API. However, there are certain limitations: * Recognition process works well with the bubbles at least 75% filled. * API will work on perspective corrupted (side viewed/out of focus) and rotated images under certain conditions. For example, angle of rotation should be within 25 degrees. * Recognition of barcode is not supported. * Performing OCR operation is not supported. * OMR operation will show results only in text format. ## Supported Operations * Correct Template: The API can be used to perform **CorrectTemplate** action on the OMR template. * Finalize Template: Once the correct OMR template operation is completed successfully, **FinalizeTemplate** action can be performed. * [Recognize Image](https://docs.aspose.cloud/display/omrcloud/Home): **RecognizeImage** action requires an image to recognize optical mark on it. **RecognizeImage** action can only be perform after successful completion of above to two actions. ## Supported Image Formats * JPEG * PNG * GIF * BMP * TIFF ## Getting Started with Aspose.OMR CloudIn order to get started with Aspose.OMR Cloud, create an account at [Aspose Cloud] and get the API Key and API Secret (SID) to be used for authentication. Access the REST URL and you are ready to consume Aspose.OMR Cloud. ## .NET ExamplesCode examples have been published on the social coding website **GitHub.com**. Anyone could explore the code examples for learning purposes. [Examples] repository under Aspose.OMR Cloud contains sample .NET console application along with sample input data that helps you learn the product features. Aspose.OMR.Client GUI application is an open source .NET application that helps you work with OMR templates. ## Documentation and API Reference GuideDetailed [documentation] to get familiar with the resources and operations of Aspose.OMR Cloud REST API is available for the developers. ## Any Question?Customers can contact us via [Aspose.OMR support forum] in case of any query or comments. : https://blog.aspose.com/wp-content/uploads/sites/2/2017/09/aspose_omr-for-cloud-1-150x150.png)](https://products.aspose.cloud/omr : http://aspose.cloud/ : https://github.com/aspose-omr-cloud/ : https://docs.aspose.cloud/display/omrcloud/Home : https://forum.aspose.cloud/c/omr