// public ImageFactory DetectObjects(HaarCascade cascade, bool drawRectangles = true, Color color = default(Color))
// {
// if (this.ShouldProcess)
// {
// DetectObjects detectObjects = new DetectObjects { DynamicParameter = cascade };
// this.CurrentImageFormat.ApplyProcessor(detectObjects.ProcessImage, this);
// }
// return this;
// }
/// <summary>
/// Crops an image to the area of greatest entropy.
/// </summary>
/// <param name="threshold">
/// The threshold in bytes to control the entropy.
/// </param>
/// <returns>
/// The current instance of the <see cref="T:ImageProcessor.ImageFactory"/> class.
/// </returns>
public ImageFactory EntropyCrop(byte threshold = 128)
{
if (this.ShouldProcess)
{
EntropyCrop autoCrop = new EntropyCrop {
DynamicParameter = threshold
};
this.CurrentImageFormat.ApplyProcessor(autoCrop.ProcessImage, this);
}
return(this);
}
/// <summary>
/// Crops an image to the area of greatest entropy.
/// </summary>
/// <param name="source">The image to crop.</param>
/// <param name="threshold">The threshold for entropic density.</param>
/// <param name="progressHandler">A delegate which is called as progress is made processing the image.</param>
/// <returns>The <see cref="Image"/></returns>
public static Image EntropyCrop(this Image source, float threshold = .5f, ProgressEventHandler progressHandler = null)
{
EntropyCrop processor = new EntropyCrop(threshold);
processor.OnProgress += progressHandler;
try
{
return source.Process(source.Width, source.Height, source.Bounds, source.Bounds, processor);
}
finally
{
processor.OnProgress -= progressHandler;
}
}
