Examples with Kernel1D_S32 boofcv.struct.convolve.Kernel1D_S32 used on opensource projects

Example 6 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class TestFactoryConvolveDown method convolve1D_I32.

@Test
void convolve1D_I32() {
    Kernel1D_S32 kernel = FactoryKernel.random1D_I32(kernelWidth, radius, 1, 6, rand);
    FilterImageInterface conv;
    GrayU8 input = new GrayU8(width, height);
    GrayS16 found = new GrayS16(width / skip, height);
    GrayS16 expected = new GrayS16(width / skip, height);
    ImageMiscOps.fillUniform(input, rand, 0, 5);
    // CHECK NO BORDER
    conv = FactoryConvolveDown.convolveSB(kernel, BorderType.SKIP, true, skip, GrayU8.class, GrayI16.class);
    conv.process(input, found);
    ConvolveImageDownNoBorder.horizontal(kernel, input, expected, skip);
    BoofTesting.assertEquals(expected, found, 0);
    // CHECK EXTENDED
    // conv = FactoryConvolveDown.convolve( kernel,GrayU8.class, ImageInt16.class,BorderType.EXTENDED,true);
    // conv.process(input,found);
    // ConvolveWithBorder.horizontal(kernel,input,expected);
    // BoofTesting.assertEquals(expected,found,0);
    // CHECK NORMALIZED
    GrayU8 found8 = new GrayU8(width / skip, height);
    GrayU8 expected8 = new GrayU8(width / skip, height);
    conv = FactoryConvolveDown.convolveSB(kernel, BorderType.NORMALIZED, true, skip, GrayU8.class, GrayI8.class);
    conv.process(input, found8);
    ConvolveImageDownNormalized.horizontal(kernel, input, expected8, skip);
    BoofTesting.assertEquals(expected8, found8, 0);
}

Example 7 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageMean method horizontal.

/**
 * Performs a horizontal 1D mean box filter. Outside pixels are specified by a border.
 *
 * @param input The input image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param offset Start offset from pixel coordinate
 * @param binput Used to process image borders. If null borders are not processed.
 * @param length How long the mean filter is
 */
public static void horizontal(GrayS16 input, GrayI16 output, int offset, int length, @Nullable ImageBorder_S32<GrayS16> binput) {
    output.reshape(input.width, output.height);
    if (binput != null) {
        binput.setImage(input);
        Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
        ConvolveJustBorder_General_SB.horizontal(kernel, binput, output, kernel.computeSum());
    }
    if (length <= input.width) {
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.horizontal(input, output, offset, length);
        } else {
            ImplConvolveMean.horizontal(input, output, offset, length);
        }
    }
}

Example 8 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageMean method vertical.

/**
 * Performs a vertical 1D mean box filter. Borders are handled by reducing the box size.
 *
 * @param input The input image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param offset Start offset from pixel coordinate
 * @param length How long the mean filter is
 * @param work (Optional) Storage for work array
 */
public static void vertical(GrayU8 input, GrayI8 output, int offset, int length, @Nullable GrowArray<DogArray_I32> workspaces) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeVertical(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.height) {
        ConvolveImageNormalized.vertical(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.vertical(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.vertical(input, output, offset, length, workspaces);
        } else {
            ImplConvolveMean.vertical(input, output, offset, length, workspaces);
        }
    }
}

Example 9 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageMean method horizontal.

/**
 * Performs a horizontal 1D mean box filter. Borders are handled by reducing the box size.
 *
 * @param input The input image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param offset Start offset from pixel coordinate
 * @param length How long the mean filter is
 */
public static void horizontal(GrayS16 input, GrayI16 output, int offset, int length) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeHorizontal(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.width) {
        ConvolveImageNormalized.horizontal(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.horizontal(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.horizontal(input, output, offset, length);
        } else {
            ImplConvolveMean.horizontal(input, output, offset, length);
        }
    }
}

Example 10 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageMean method vertical.

/**
 * Performs a vertical 1D mean box filter. Outside pixels are specified by a border.
 *
 * @param input The input image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param offset Start offset from pixel coordinate
 * @param binput Used to process image borders. If null borders are not processed.
 * @param work (Optional) Storage for work array
 */
public static void vertical(GrayU8 input, GrayI8 output, int offset, int length, @Nullable ImageBorder_S32<GrayU8> binput, @Nullable GrowArray<DogArray_I32> workspaces) {
    output.reshape(input);
    if (binput != null) {
        binput.setImage(input);
        Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
        ConvolveJustBorder_General_SB.vertical(kernel, binput, output, kernel.computeSum());
    }
    if (length <= input.height) {
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.vertical(input, output, offset, length, workspaces);
        } else {
            ImplConvolveMean.vertical(input, output, offset, length, workspaces);
        }
    }
}