Threshold for large objects.
public int LargeObjectThreshold {get; set;}
@property (nonatomic, assign) NSInteger largeObjectThreshold;
public int getLargeObjectThreshold();
public void setLargeObjectThreshold(
int intValue
);
public:
property Int32 LargeObjectThreshold
{
Int32 get()
void set(Int32 value)
}
LargeObjectThreshold # get and set (ExObjFilterOptions)
The threshold for large objects. The default value is 0.
Objects with a maximum dimension larger than the specified value will be filtered. Use -1 to disable large object filtering.
If SmallObjectThreshold is not -1, this value must be larger.
using Leadtools;
using Leadtools.Codecs;
using Leadtools.ImageProcessing;
using Leadtools.ImageProcessing.Core;
public void ExtractObjectsCommandExample()
{
using (RasterCodecs codecs = new RasterCodecs())
// Load the original image
using (RasterImage inputImage = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "demoicr2.tif")))
{
// Setup the extraction options
ExtractObjectsCommand command = new ExtractObjectsCommand()
{
DetectChildren = true,
EightConnectivity = true,
Outline = true
};
// Extract the objects
command.Run(inputImage);
using (ExObjData data = command.Data)
{
// Log the number of objects from the first list
ExObjObjectList objects = data[0].Objects;
Console.WriteLine($"Number of objects (before filtering): {objects.Count}");
// Log the number of points around the first object (braces for scope)
{
int count = 0;
foreach (ExObjOutlinePoint point in objects.First().Outline)
count++;
Console.WriteLine($"First object's outline length: {count}");
}
// Setup the filter options
ExObjFilterOptions filterOptions = new ExObjFilterOptions()
{
LargeObjectThreshold = -1, // No upper limit on size
SmallObjectThreshold = 10 // Remove objects smaller than 10x10 pixels
};
// Filter the objects
data.FilterList(objects, filterOptions);
// Log the number of objects again
Console.WriteLine($"Number of objects (after filtering): {objects.Count}");
// Setup the content bound options
ExObjContentBound contentBound = new ExObjContentBound(new LeadRect(192, 260, 323, 146));
ExObjContentBoundOptions contentBoundOptions = new ExObjContentBoundOptions()
{
ObjectsOfInterest = null // Pass null to use every object in data
};
// Calculate the content bounds
data.CalculateContentBound(new ExObjContentBound[] { contentBound }, contentBoundOptions);
// Setup the region options
ExObjRegionOptions regionOptions = new ExObjRegionOptions()
{
Horizontal = true
};
// Calculate each object's region
data.CalculateRegion(objects, regionOptions);
// Create an output image
using (RasterImage outputImage = RasterImage.Create(inputImage.Width, inputImage.Height, 24, inputImage.XResolution, RasterColor.White))
{
// Fill the output image with white
new FillCommand(RasterColor.White).Run(outputImage);
// Draw the content bound rects for the first word. Red for the input, green for the output.
outputImage.AddRectangleToRegion(null, contentBound.Input, RasterRegionCombineMode.Set);
new FillCommand(new RasterColor(255, 0, 0)).Run(outputImage);
outputImage.AddRectangleToRegion(null, contentBound.Content, RasterRegionCombineMode.Set);
new FillCommand(new RasterColor(0, 255, 0)).Run(outputImage);
// Populate the output image with each object's region
foreach (ExObjObject @object in objects)
foreach (ExObjSegment segment in @object.RegionHorizontal)
{
// Update the region to the current segment
outputImage.AddRectangleToRegion(null, segment.Bounds, RasterRegionCombineMode.Set);
// Fill the region with black
new FillCommand(RasterColor.Black).Run(outputImage);
}
// Clear the output image's region
outputImage.MakeRegionEmpty();
// Save the output image
codecs.Save(outputImage, Path.Combine(LEAD_VARS.ImagesDir, "ExtractObjects.png"), RasterImageFormat.Png, 0);
}
}
}
}
static class LEAD_VARS
{
public const string ImagesDir = @"C:\LEADTOOLS22\Resources\Images";
}
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