Image

A container for image data.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
}

Stub code in Image.sdsstub

@Experimental
class Image {
    /**
     * Get the width of the image in pixels.
     */
    attr width: Int
    /**
     * Get the height of the image in pixels.
     */
    attr height: Int
    /**
     * Get the number of channels of the image.
     */
    attr channel: Int
    /**
     * Get the `ImageSize` of the image.
     */
    attr size: ImageSize

    /**
     * Create an image from a file.
     *
     * @param path The path to the image file.
     *
     * @result image The image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     * }
     */
    @Impure([ImpurityReason.FileReadFromParameterizedPath("path")])
    @PythonName("from_file")
    @Category(DataScienceCategory.DataImport)
    static fun fromFile(
        path: String
    ) -> image: Image

    /**
     * Save the image as a JPEG file.
     *
     * @param path The path to the JPEG file.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     image.toJpegFile("output.jpeg");
     * }
     */
    @Impure([ImpurityReason.FileWriteToParameterizedPath("path")])
    @PythonName("to_jpeg_file")
    @Category(DataScienceCategory.DataExport)
    fun toJpegFile(
        path: String
    )

    /**
     * Save the image as a PNG file.
     *
     * @param path The path to the PNG file.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     image.toPngFile("output.png");
     * }
     */
    @Impure([ImpurityReason.FileWriteToParameterizedPath("path")])
    @PythonName("to_png_file")
    @Category(DataScienceCategory.DataExport)
    fun toPngFile(
        path: String
    )

    /**
     * Return a new `Image` that has the given number of channels.
     *
     * The original image is not modified.
     *
     * @param channel The new number of channels. 1 will result in a grayscale image.
     *
     * @result newImage The image with the given number of channels.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.changeChannel(channel = 1);
     * }
     */
    @Pure
    @PythonName("change_channel")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun changeChannel(
        channel: Int
    ) -> newImage: Image

    /**
     * Return a new `Image` that has been resized to a given size.
     *
     * The original image is not modified.
     *
     * @param newWidth The new width of the image.
     * @param newHeight The new height of the image.
     *
     * @result newImage The image with the given width and height.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.resize(newWidth = 100, newHeight = 50);
     * }
     */
    @Pure
    @Category(DataScienceCategory.DataProcessingQImage)
    fun resize(
        @PythonName("new_width") const newWidth: Int,
        @PythonName("new_height") const newHeight: Int
    ) -> newImage: Image where {
        newWidth >= 0,
        newHeight >= 0
    }

    /**
     * Return a new `Image` that is converted to grayscale.
     *
     * The new image will have the same amount of channels as the original image. If you want to change the amount of
     * channels used, please use the method {@link Image.changeChannel}.
     *
     * The original image is not modified.
     *
     * @result newImage The grayscale image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.convertToGrayscale();
     * }
     */
    @Pure
    @PythonName("convert_to_grayscale")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun convertToGrayscale() -> newImage: Image

    /**
     * Return a new `Image` that has been cropped to a given bounding rectangle.
     *
     * The original image is not modified.
     *
     * @param x The x coordinate of the top-left corner of the bounding rectangle.
     * @param y The y coordinate of the top-left corner of the bounding rectangle.
     * @param width The width of the bounding rectangle.
     * @param height The height of the bounding rectangle.
     *
     * @result newImage The cropped image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.crop(20, 20, 80, 40);
     * }
     */
    @Pure
    @Category(DataScienceCategory.DataProcessingQImage)
    fun crop(
        const x: Int,
        const y: Int,
        const width: Int,
        const height: Int
    ) -> newImage: Image where {
        x >= 0,
        y >= 0,
        width >= 0,
        height >= 0
    }

    /**
     * Return a new `Image` where top and bottom are flipped along a horizontal axis.
     *
     * The original image is not modified.
     *
     * @result newImage The flipped image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.flipTopAndBottom();
     * }
     */
    @Pure
    @PythonName("flip_top_and_bottom")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun flipTopAndBottom() -> result: Image

    /**
     * Return a new `Image` where left and right sides are flipped along a vertical axis.
     *
     * The original image is not modified.
     *
     * @result newImage The flipped image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.flipLeftAndRight();
     * }
     */
    @Pure
    @PythonName("flip_left_and_right")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun flipLeftAndRight() -> result: Image

    /**
     * Return a new `Image` with an adjusted brightness.
     *
     * The original image is not modified.
     *
     * @param factor The brightness factor.
     * 1.0 will not change the brightness.
     * Below 1.0 will result in a darker image.
     * Above 1.0 will resolut in a brighter image.
     * Has to be bigger than or equal to 0 (black).
     *
     * @result newImage The Image with adjusted brightness.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.adjustBrightness(factor = 2.0);
     * }
     */
    @Pure
    @PythonName("adjust_brightness")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun adjustBrightness(
        const factor: Float
    ) -> newImage: Image where {
        factor >= 0.0
    }

    /**
     * Return a new `Image` with noise added to the image.
     *
     * The original image is not modified.
     *
     * @param standardDeviation The standard deviation of the normal distribution. Has to be bigger than or equal to 0.
     *
     * @result newImage The image with added noise.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.addNoise(standardDeviation = 1.0);
     * }
     */
    @Pure
    @PythonName("add_noise")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun addNoise(
        @PythonName("standard_deviation") const standardDeviation: Float
    ) -> newImage: Image where {
        standardDeviation >= 0.0
    }

    /**
     * Return a new `Image` with adjusted contrast.
     *
     * The original image is not modified.
     *
     * @param factor If factor > 1, increase contrast of image.
     * If factor = 1, no changes will be made.
     * If factor < 1, make image greyer.
     * Has to be bigger than or equal to 0 (gray).
     *
     * @result newImage New image with adjusted contrast.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.adjustContrast(factor = 2.0);
     * }
     */
    @Pure
    @PythonName("adjust_contrast")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun adjustContrast(
        const factor: Float
    ) -> newImage: Image where {
        factor >= 0.0
    }

    /**
     * Return a new `Image` with adjusted color balance.
     *
     * The original image is not modified.
     *
     * @param factor Has to be bigger than or equal to 0.
     * If 0 <= factor < 1, make image greyer.
     * If factor = 1, no changes will be made.
     * If factor > 1, increase color balance of image.
     *
     * @result newImage The new, adjusted image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.adjustColorBalance(factor = 2.0);
     * }
     */
    @Pure
    @PythonName("adjust_color_balance")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun adjustColorBalance(
        const factor: Float
    ) -> newImage: Image where {
        factor >= 0.0
    }

    /**
     * Return a blurred version of the image.
     *
     * The original image is not modified.
     *
     * @param radius Radius is directly proportional to the blur value. The radius is equal to the amount of pixels united in
     * each direction. A radius of 1 will result in a united box of 9 pixels.
     *
     * @result newImage The blurred image.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.blur(radius = 50);
     * }
     */
    @Pure
    @Category(DataScienceCategory.DataProcessingQImage)
    fun blur(
        const radius: Int
    ) -> newImage: Image where {
        radius >= 0
    }

    /**
     * Return a sharpened version of the image.
     *
     * The original image is not modified.
     *
     * @param factor If factor > 1, increase the sharpness of the image.
     * If factor = 1, no changes will be made.
     * If factor < 1, blur the image.
     * Has to be bigger than or equal to 0 (blurred).
     *
     * @result newImage The image sharpened by the given factor.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.sharpen(factor = 5.0);
     * }
     */
    @Pure
    @Category(DataScienceCategory.DataProcessingQImage)
    fun sharpen(
        const factor: Float
    ) -> newImage: Image where {
        factor >= 0.0
    }

    /**
     * Return a new `Image` with colors inverted.
     *
     * The original image is not modified.
     *
     * @result newImage The image with inverted colors.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.invertColors();
     * }
     */
    @Pure
    @PythonName("invert_colors")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun invertColors() -> newImage: Image

    /**
     * Return a new `Image` that is rotated 90 degrees clockwise.
     *
     * The original image is not modified.
     *
     * @result newImage The image rotated 90 degrees clockwise.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.rotateRight();
     * }
     */
    @Pure
    @PythonName("rotate_right")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun rotateRight() -> newImage: Image

    /**
     * Return a new `Image` that is rotated 90 degrees counter-clockwise.
     *
     * The original image is not modified.
     *
     * @result newImage The image rotated 90 degrees counter-clockwise.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.rotateLeft();
     * }
     */
    @Pure
    @PythonName("rotate_left")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun rotateLeft() -> newImage: Image

    /**
     * Return a grayscale version of the image with the edges highlighted.
     *
     * The original image is not modified.
     *
     * @result newImage The image with edges found.
     *
     * @example
     * pipeline example {
     *     val image = Image.fromFile("example.png");
     *     val newImage = image.findEdges();
     * }
     */
    @Pure
    @PythonName("find_edges")
    @Category(DataScienceCategory.DataProcessingQImage)
    fun findEdges() -> newImage: Image
}

channel

Get the number of channels of the image.

Type: Int

height

Get the height of the image in pixels.

Type: Int

size

Get the ImageSize of the image.

Type: ImageSize

width

Get the width of the image in pixels.

Type: Int

addNoise

Return a new Image with noise added to the image.

The original image is not modified.

Parameters:

Name	Type	Description	Default
standardDeviation	Float	The standard deviation of the normal distribution. Has to be bigger than or equal to 0.	-

Results:

Name	Type	Description
newImage	Image	The image with added noise.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.addNoise(standardDeviation = 1.0);
}

Stub code in Image.sdsstub

@Pure
@PythonName("add_noise")
@Category(DataScienceCategory.DataProcessingQImage)
fun addNoise(
    @PythonName("standard_deviation") const standardDeviation: Float
) -> newImage: Image where {
    standardDeviation >= 0.0
}

adjustBrightness

Return a new Image with an adjusted brightness.

The original image is not modified.

Parameters:

Name	Type	Description	Default
factor	Float	The brightness factor. 1.0 will not change the brightness. Below 1.0 will result in a darker image. Above 1.0 will resolut in a brighter image. Has to be bigger than or equal to 0 (black).	-

Results:

Name	Type	Description
newImage	Image	The Image with adjusted brightness.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.adjustBrightness(factor = 2.0);
}

Stub code in Image.sdsstub

@Pure
@PythonName("adjust_brightness")
@Category(DataScienceCategory.DataProcessingQImage)
fun adjustBrightness(
    const factor: Float
) -> newImage: Image where {
    factor >= 0.0
}

adjustColorBalance

Return a new Image with adjusted color balance.

The original image is not modified.

Parameters:

Name	Type	Description	Default
factor	Float	Has to be bigger than or equal to 0. If 0 <= factor < 1, make image greyer. If factor = 1, no changes will be made. If factor > 1, increase color balance of image.	-

Results:

Name	Type	Description
newImage	Image	The new, adjusted image.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.adjustColorBalance(factor = 2.0);
}

Stub code in Image.sdsstub

@Pure
@PythonName("adjust_color_balance")
@Category(DataScienceCategory.DataProcessingQImage)
fun adjustColorBalance(
    const factor: Float
) -> newImage: Image where {
    factor >= 0.0
}

adjustContrast

Return a new Image with adjusted contrast.

The original image is not modified.

Parameters:

Name	Type	Description	Default
factor	Float	If factor > 1, increase contrast of image. If factor = 1, no changes will be made. If factor < 1, make image greyer. Has to be bigger than or equal to 0 (gray).	-

Results:

Name	Type	Description
newImage	Image	New image with adjusted contrast.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.adjustContrast(factor = 2.0);
}

Stub code in Image.sdsstub

@Pure
@PythonName("adjust_contrast")
@Category(DataScienceCategory.DataProcessingQImage)
fun adjustContrast(
    const factor: Float
) -> newImage: Image where {
    factor >= 0.0
}

blur

Return a blurred version of the image.

The original image is not modified.

Parameters:

Name	Type	Description	Default
radius	Int	Radius is directly proportional to the blur value. The radius is equal to the amount of pixels united in each direction. A radius of 1 will result in a united box of 9 pixels.	-

Results:

Name	Type	Description
newImage	Image	The blurred image.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.blur(radius = 50);
}

Stub code in Image.sdsstub

@Pure
@Category(DataScienceCategory.DataProcessingQImage)
fun blur(
    const radius: Int
) -> newImage: Image where {
    radius >= 0
}

changeChannel

Return a new Image that has the given number of channels.

The original image is not modified.

Parameters:

Name	Type	Description	Default
channel	Int	The new number of channels. 1 will result in a grayscale image.	-

Results:

Name	Type	Description
newImage	Image	The image with the given number of channels.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.changeChannel(channel = 1);
}

Stub code in Image.sdsstub

@Pure
@PythonName("change_channel")
@Category(DataScienceCategory.DataProcessingQImage)
fun changeChannel(
    channel: Int
) -> newImage: Image

convertToGrayscale

Return a new Image that is converted to grayscale.

The new image will have the same amount of channels as the original image. If you want to change the amount of channels used, please use the method Image.changeChannel.

The original image is not modified.

Results:

Name	Type	Description
newImage	Image	The grayscale image.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.convertToGrayscale();
}

Stub code in Image.sdsstub

@Pure
@PythonName("convert_to_grayscale")
@Category(DataScienceCategory.DataProcessingQImage)
fun convertToGrayscale() -> newImage: Image

crop

Return a new Image that has been cropped to a given bounding rectangle.

The original image is not modified.

Parameters:

Name	Type	Description	Default
x	Int	The x coordinate of the top-left corner of the bounding rectangle.	-
y	Int	The y coordinate of the top-left corner of the bounding rectangle.	-
width	Int	The width of the bounding rectangle.	-
height	Int	The height of the bounding rectangle.	-

Results:

Name	Type	Description
newImage	Image	The cropped image.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.crop(20, 20, 80, 40);
}

Stub code in Image.sdsstub

@Pure
@Category(DataScienceCategory.DataProcessingQImage)
fun crop(
    const x: Int,
    const y: Int,
    const width: Int,
    const height: Int
) -> newImage: Image where {
    x >= 0,
    y >= 0,
    width >= 0,
    height >= 0
}

findEdges

Return a grayscale version of the image with the edges highlighted.

The original image is not modified.

Results:

Name	Type	Description
newImage	Image	The image with edges found.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.findEdges();
}

Stub code in Image.sdsstub

@Pure
@PythonName("find_edges")
@Category(DataScienceCategory.DataProcessingQImage)
fun findEdges() -> newImage: Image

flipLeftAndRight

Return a new Image where left and right sides are flipped along a vertical axis.

The original image is not modified.

Results:

Name	Type	Description
result	Image	-

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.flipLeftAndRight();
}

Stub code in Image.sdsstub

@Pure
@PythonName("flip_left_and_right")
@Category(DataScienceCategory.DataProcessingQImage)
fun flipLeftAndRight() -> result: Image

flipTopAndBottom

Return a new Image where top and bottom are flipped along a horizontal axis.

The original image is not modified.

Results:

Name	Type	Description
result	Image	-

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.flipTopAndBottom();
}

Stub code in Image.sdsstub

@Pure
@PythonName("flip_top_and_bottom")
@Category(DataScienceCategory.DataProcessingQImage)
fun flipTopAndBottom() -> result: Image

invertColors

Return a new Image with colors inverted.

The original image is not modified.

Results:

Name	Type	Description
newImage	Image	The image with inverted colors.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.invertColors();
}

Stub code in Image.sdsstub

@Pure
@PythonName("invert_colors")
@Category(DataScienceCategory.DataProcessingQImage)
fun invertColors() -> newImage: Image

resize

Return a new Image that has been resized to a given size.

The original image is not modified.

Parameters:

Name	Type	Description	Default
newWidth	Int	The new width of the image.	-
newHeight	Int	The new height of the image.	-

Results:

Name	Type	Description
newImage	Image	The image with the given width and height.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.resize(newWidth = 100, newHeight = 50);
}

Stub code in Image.sdsstub

@Pure
@Category(DataScienceCategory.DataProcessingQImage)
fun resize(
    @PythonName("new_width") const newWidth: Int,
    @PythonName("new_height") const newHeight: Int
) -> newImage: Image where {
    newWidth >= 0,
    newHeight >= 0
}

rotateLeft

Return a new Image that is rotated 90 degrees counter-clockwise.

The original image is not modified.

Results:

Name	Type	Description
newImage	Image	The image rotated 90 degrees counter-clockwise.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.rotateLeft();
}

Stub code in Image.sdsstub

@Pure
@PythonName("rotate_left")
@Category(DataScienceCategory.DataProcessingQImage)
fun rotateLeft() -> newImage: Image

rotateRight

Return a new Image that is rotated 90 degrees clockwise.

The original image is not modified.

Results:

Name	Type	Description
newImage	Image	The image rotated 90 degrees clockwise.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.rotateRight();
}

Stub code in Image.sdsstub

@Pure
@PythonName("rotate_right")
@Category(DataScienceCategory.DataProcessingQImage)
fun rotateRight() -> newImage: Image

sharpen

Return a sharpened version of the image.

The original image is not modified.

Parameters:

Name	Type	Description	Default
factor	Float	If factor > 1, increase the sharpness of the image. If factor = 1, no changes will be made. If factor < 1, blur the image. Has to be bigger than or equal to 0 (blurred).	-

Results:

Name	Type	Description
newImage	Image	The image sharpened by the given factor.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    val newImage = image.sharpen(factor = 5.0);
}

Stub code in Image.sdsstub

@Pure
@Category(DataScienceCategory.DataProcessingQImage)
fun sharpen(
    const factor: Float
) -> newImage: Image where {
    factor >= 0.0
}

toJpegFile

Save the image as a JPEG file.

Parameters:

Name	Type	Description	Default
path	String	The path to the JPEG file.	-

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    image.toJpegFile("output.jpeg");
}

Stub code in Image.sdsstub

@Impure([ImpurityReason.FileWriteToParameterizedPath("path")])
@PythonName("to_jpeg_file")
@Category(DataScienceCategory.DataExport)
fun toJpegFile(
    path: String
)

toPngFile

Save the image as a PNG file.

Parameters:

Name	Type	Description	Default
path	String	The path to the PNG file.	-

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
    image.toPngFile("output.png");
}

Stub code in Image.sdsstub

@Impure([ImpurityReason.FileWriteToParameterizedPath("path")])
@PythonName("to_png_file")
@Category(DataScienceCategory.DataExport)
fun toPngFile(
    path: String
)

fromFile

Create an image from a file.

Parameters:

Name	Type	Description	Default
path	String	The path to the image file.	-

Results:

Name	Type	Description
image	Image	The image.

Examples:

pipeline example {
    val image = Image.fromFile("example.png");
}

Stub code in Image.sdsstub

@Impure([ImpurityReason.FileReadFromParameterizedPath("path")])
@PythonName("from_file")
@Category(DataScienceCategory.DataImport)
static fun fromFile(
    path: String
) -> image: Image