Ready-to-use tool for reading text from images using the OCR technique.
|inOcrModel||OcrModel||OCR model specific to a particular font|
|inMinScore||Real||0.0 - 1.0||Minimal score of reading a character|
|outCharacters||String?Array||Array of characters. NIL indicates invalid read when inMinScore is set,|
|outScores||RealArray||Reading scores for each character|
|outIsTextValid||Bool||Returns False if any ad score smaller than inMinScore|
This operation reads a text from the array of regions. Each region corresponds to a single letter at the filter output outText. Empty regions are omitted.
Typically this filter are connected with ExtractText which prepares input regions for reading.
- Connect an array of character regions to the inCharacters input. Usually it will be the output of the ExtractText filter. Make sure that these regions are available (the program was previously run).
- Enter the graphical editor for the inOcrModel input. Create the OCR model by gathering and annotating character samples.
- Alternatively, you can use one of the pre-trained models. To do so, right-click on the inOcrModel input and select "Link from AVDATA file...". Then browse to the directory C:\ProgramData\Adaptive Vision\Adaptive Vision Studio 4.x Professional\PretrainedFonts\ (Windows 7) and select the model you need.
To read more about how to use OCR technique, refer to Machine Vision Guide: Optical Character Recognition
This filter can throw an exception to report error. Read how to deal with errors in Error Handling.
List of possible exceptions:
|DomainError||Uninitialized OCR model in ReadText. OCR model must be trained before use.|
This filter is available on Basic Complexity Level.
- ExtractText – Ready-to-use tool for extracting and splitting character to single characters.
- RecognizeCharacters – Classifies input regions into characters. Based on the Multi-Layer Perceptron model.
- TrainOcr_MLP – Trains an OCR multilayer perceptron classifier.
- TrainOcr_SVM – Trains an OCR support vector machines classifier.