## Aspose.OMR for .NET

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![Aspose.OMR for .NET Product Logo](logo_omr_net.png)

**Welcome to the Aspose.OMR for .NET**

Aspose.OMR for .NET is an API to recognize optical marks from OMR digitized sheet images. It can be used to recognize optical marks in a variety of image formats like BMP, JPG, TIF, TIFF, GIF. The API allows capturing human-marked data from document forms such as surveys, questionnaires, multiple-choice examination papers, and other tests. With this solution, it is possible to recognize scanned images and even photos with high accuracy. Recognition is based on a template markup which contains a graphical mapping of the elements to be recognized from the scanned images.

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These are links to some useful resources:
- [Aspose.OMR for .NET API Reference](/omr/net/)


## Aspose.OMR for Java

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![Aspose.OMR for Java Product Logo](logo_omr_java.png)

**Welcome to the Aspose.OMR for Java**

Aspose.OMR for Java is an API to recognize optical marks from OMR digitized sheet images. It can be used to recognize optical marks in a variety of image formats like BMP, JPG, TIF, TIFF, GIF. The API allows capturing human-marked data from document forms such as surveys, questionnaires, multiple-choice examination papers, and other tests. With this solution, it is possible to recognize scanned images and even photos with high accuracy. Recognition is based on a template markup which contains a graphical mapping of the elements to be recognized from the scanned images.

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These are links to some useful resources:

- [Aspose.OMR for Java API Reference](/omr/java/)


## Aspose.OMR for C++

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![Aspose.OMR for C++ Product Logo](logo_omr_cpp.png)

**Welcome to the Aspose.OMR for C++**

Aspose.OMR for C++ is an API to recognize optical marks from OMR digitized sheet images. It can be used to recognize optical marks in a variety of image formats like BMP, JPG, TIF, TIFF, GIF. The API allows capturing human-marked data from document forms such as surveys, questionnaires, multiple-choice examination papers, and other tests. With this solution, it is possible to recognize scanned images and even photos with high accuracy. Recognition is based on a template markup which contains a graphical mapping of the elements to be recognized from the scanned images.

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These are links to some useful resources:
- [Aspose.OMR for C++ API Reference](/omr/cpp/)