| Метод | Описание | |
|---|---|---|
| CascadeClassifier ( String fileName ) : System |
Create a CascadeClassifier from the specific file
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DetectMultiScale ( Byte>.Image |
Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. The function scans the image several times at different scales. Each time it considers overlapping regions in the image. It may also apply some heuristics to reduce number of analyzed regions, such as Canny prunning. After it has proceeded and collected the candidate rectangles (regions that passed the classifier cascade), it groups them and returns a sequence of average rectangles for each large enough group.
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| Метод | Описание | |
|---|---|---|
| DisposeObject ( ) : void |
Release the CascadeClassifier Object and all the memory associate with it
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| public CascadeClassifier ( String fileName ) : System | ||
| fileName | String | The name of the file that contains the CascadeClassifier |
| Результат | System | |
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public DetectMultiScale ( Byte>.Image |
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| image | Byte>.Image | The image where the objects are to be detected from |
| scaleFactor | double | The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10% |
| minNeighbors | int | Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure |
| minSize | Minimum window size. Use Size.Empty for default, where it is set to the size of samples the classifier has been trained on (~20x20 for face detection) | |
| maxSize | Maxumum window size. Use Size.Empty for default, where the parameter will be ignored. | |
| Результат | System.Drawing.Rectangle[] | |
