# Tutorial

## Using the Image Class

The most important class in the Python Imaging Library is the `Image` class, defined in the module with the same name. You can create instances of this class in several ways; either by loading images from files, processing other images, or creating images from scratch.

To load an image from a file, use the `open` function in the `Image` module.

        >>> import Image
        >>> im = Image.open("lena.ppm")

If successful, this function returns an `Image` object. You can now use instance attributes to see what the file really contained.

        >>> print im.format, im.size, im.mode
        PPM (512, 512) RGB

The `format` attribute identifies the source of an image. If the image was not read from a file, it is set to `None`. The `size` attribute is a 2-tuple containing width and height (in pixels). The `mode` attribute defines the number and names of the bands in the image, and also the pixel type and depth. Common modes are "L" (for luminance) for greyscale images, "RGB" for true colour images, and "CMYK" for pre-press images.

If the file cannot be opened, an `IOError` exception is raised.

Once you have an instance of the `Image` class, you can use the methods defined by this class to process and manipulate the image. For example, let's display the image we just loaded:

        >>> im.show()

(The standard version of `show` is not very efficient, since it saves the image to a temporary file and calls the `xv` utility to display the image. If you don't have `xv` installed, it won't even work. When it does work, it is very handy for debugging and tests, though.)

The following sections provide an overview of the different functions provided in this library.

## Reading and Writing Images

The Python Imaging Library supports a wide variety of image file formats. To read files from disk, you use the `open` function in the `Image` module. You don't have to know the file format to open a file. The library automatically determines the format based on the contents of the file.

To save a file, use the `save` method in the `Image` class. When saving files, the name becomes important. Unless you specify the format, the library use the filename extension to figure out which file format to use when storing the file.

Example: Convert files to JPEG

    import os, sys
    import Image

    for infile in sys.argv[1:]:
        outfile = os.path.splitext(infile)[0] + ".jpg"
        if infile != outfile:
            try:
                Image.open(infile).save(outfile)
            except IOError:
                print "cannot convert", infile

You can use a second argument to the `save` method in order to explicitly specify a file format. If you use a non-standard extension, you must always specify the format this way:

Example: Create JPEG Thumbnails

    import os, sys
    import Image

    for infile in sys.argv[1:]:
        outfile = os.path.splitext(infile)[0] + ".thumbnail"
        if infile != outfile:
            try:
                im = Image.open(infile)
                im.thumbnail((128, 128))
                im.save(outfile, "JPEG")
            except IOError:
                print "cannot create thumbnail for", infile

An important detail is that the library doesn't decode or load the raster data unless it really has to. When you open a file, the file header is read to determine the file format and extract things like mode, size, and other properties required to decode the file, but the rest of the file is not processed until later.

This also means that opening an image file is a fast operation, independent of the file size and compression type. Here's a simple script to quickly identify a set of image files:

Example: Identify Image Files

    import sys
    import Image

    for infile in sys.argv[1:]:
        try:
            im = Image.open(infile)
            print infile, im.format, "%dx%d" % im.size, im.mode
        except IOError:
            pass

## Cutting, Pasting and Merging Images

The `Image` class contains methods allowing you to manipulate regions within an image. To extract a sub-rectangle from an image, use the `crop` method.

Example: Copying a subrectangle from an image

        box = (100, 100, 400, 400)
        region = im.crop(box)

The region is defined by a 4-tuple, where coordinates are (left, upper, right, lower). The Python Imaging Library uses a coordinate system with (0, 0) in the upper left corner. Also note that coordinates refer to positions between the pixels, so the region in the above example is 300x300 pixels and nothing else.

You can now process the region in some fashion, and possibly paste it back.

Example: Processing a subrectangle, and pasting it back

        region = region.transpose(Image.ROTATE_180)
        im.paste(region, box)

When pasting regions back, the size of the region must match the given region exactly. In addition, the region cannot extend outside the image. However, the modes of the original image and the region do not need to match. If they don't, the region is automatically converted before being pasted (see the section on Colour Transforms below for details).

Here's an additional example:

Example: "Rolling" an image

    def roll(image, delta):
        "Roll an image sideways"

        xsize, ysize = image.size

        delta = delta % xsize
        if delta == 0: return image

        part1 = image.crop((0, 0, delta, ysize))
        part2 = image.crop((delta, 0, xsize, ysize))
        image.paste(part2, (0, 0, xsize-delta, ysize))
        image.paste(part1, (xsize-delta, 0, xsize, ysize))

        return image

For more advanced tricks, the paste method can also take a transparency mask as an optional argument. In this mask, the value 255 indicates that the pasted image is opaque in that position (that is, the pasted image should be used as is). The value 0 means that the pasted image is completely transparent. Values in between indicate different levels of transparency.

The Python Imaging Library also allows you to work with the individual bands of an multi-band image, such as an RGB image. The split method creates a set of new images, each containing one band from the original multi-band image. The merge function takes a mode and a tuple of images, and combines them into a new image. The following sample swaps the three bands of an RGB image:

Example: Splitting and merging bands

    r, g, b = im.split()
    im = Image.merge("RGB", (b, g, r))

## Geometrical Transforms

The `Image` class contains methods to `resize` and `rotate` an image. The former takes a tuple giving the new size, the latter the angle in degrees counter-clockwise.

Example: Simple geometry transforms

    out = im.resize((128, 128))
    out = im.rotate(45) # degrees counter-clockwise

To rotate the image in full 90 degree steps, you can either use the `rotate` method or the `transpose` method. The latter can also be used to flip an image around its horizontal or vertical axis.

Example: Transposing an image

    out = im.transpose(Image.FLIP_LEFT_RIGHT)
    out = im.transpose(Image.FLIP_TOP_BOTTOM)
    out = im.transpose(Image.ROTATE_90)
    out = im.transpose(Image.ROTATE_180)
    out = im.transpose(Image.ROTATE_270)

There's no difference in performance or result between `transpose(ROTATE)` and corresponding `rotate` operations.

A more general form of image transformations can be carried out via the `transform` method. See the reference section for details.

## Colour Transforms

The Python Imaging Library allows you to convert images between different pixel representations using the convert function.

Example: Converting between modes

        im = Image.open("lena.ppm").convert("L")

The library supports transformations between each supported mode and the "L" and "RGB" modes. To convert between other modes, you may have to use an intermediate image (typically an "RGB" image).

## Image Enhancement

The Python Imaging Library provides a number of methods and modules that can be used for image enhancement.

### Filters

The `ImageFilter` module contains a number of pre-defined enhancement filters that can be used with the `filter` method.

Example: Applying filters

    import ImageFilter
    out = im.filter(ImageFilter.DETAIL)

### Point Operations

The `point` method can be used to translate the pixel values of an image. This can for example be used to manipulate the image contrast. In most cases, you can use pass this function a function object expecting one argument. Each pixel is processed according to that function:

Example: Applying point transforms

    # multiply each pixel by 1.2
    out = im.point(lambda i: i * 1.2)

Using the above technique, you can quickly apply any simple expression to an image. You can also combine the `point` and `paste` methods to selectively modify an image:

Example: Processing individual bands

    # split the image into individual bands
    source = im.split()

    R, G, B = 0, 1, 2

    # select regions where red is less than 100
    mask = source[R].point(lambda i: i < 100 and 255)

    # process the green band
    out = source[G].point(lambda i: i * 0.7)

    # paste the processed band back, but only where red was < 100
    source[G].paste(out, None, mask)

    # build a new multiband image
    im = Image.merge(im.mode, source)

Note the syntax used to create the mask:

        imout = im.point(lambda i: expression and 255)

Python only evaluates as much of a logical expression as is necessary to determine the outcome, and returns the last value examined as the result of the expression. So if the expression above is false (0), Python does not look at the second operand, and thus returns 0. Otherwise, it returns 255.

### Enhancement

For more advanced image enhancement, use the classes in the `ImageEnhance` module. Once created from an image, an enhancement object can be used to quickly try out different settings.

You can adjust contrast, brightness, colour balance and sharpness in this way.

Example: Enhancing images

    import ImageEnhance

    enh = ImageEnhance.Contrast(im)
    enh.enhance(1.3).show("30% more contrast")

## Image Sequences

The Python Imaging Library contains some basic support for image sequences (also called animation formats). Supported sequence formats include FLI/FLC, GIF, and a few experimental formats. TIFF files can also contain more than one frame.

When you open a sequence file, PIL automatically loads the first frame in the sequence. You can use the `seek` and `tell` methods to change which frame to work with:

Example: Reading sequences

    import Image

    im = Image.open("animation.gif")
    im.seek(1) # skip to the second frame

    try:
        while 1:
            im.seek(im.tell()+1)
            # do something to im
    except EOFError:
        pass # end of sequence

As seen in this example, you'll get an `EOFError` exception when the sequence ends.

Note that most drivers in the current version of the library only allows you to seek to the next frame (as in the above example). To rewind the file, you may have to reopen it.

The following iterator class lets you to use the for-statement to loop over the sequence:

Example: A sequence iterator class

    class ImageSequence:
        def __init__(self, im):
            self.im = im
        def __getitem__(self, ix):
            try:
                if ix:
                    self.im.seek(ix)
                return self.im
            except EOFError:
                raise IndexError # end of sequence

    for frame in ImageSequence(im):
        # ...do something to frame...

## Postscript Printing

The Python Imaging Library includes functions to print images, text and graphics on Postscript printers. Here's a simple example:

Example: Drawing Postscript

    import Image
    import PSDraw

    im = Image.open("lena.ppm")
    title = "lena"
    box = (1*72, 2*72, 7*72, 10*72) # in points

    ps = PSDraw.PSDraw() # default is sys.stdout
    ps.begin_document(title)

    # draw the image (75 dpi)
    ps.image(box, im, 75)
    ps.rectangle(box)

    # draw centered title
    ps.setfont("HelveticaNarrow-Bold", 36)
    w, h, b = ps.textsize(title)
    ps.text((4*72-w/2, 1*72-h), title)

    ps.end_document()

## More on Reading Images

As described earlier, you use the open function in the `Image` module to open an image file. In most cases, you simply pass it the filename as argument:

    im = Image.open("lena.ppm")

If everything goes well, the result is an `Image` object. Otherwise, an `IOError` exception is raised.

You can use a file-like object instead of the filename. The file object must implement the `read`, `seek` and `tell` methods, and be opened in binary mode.

Example: Reading from an open file

    fp = open("lena.ppm", "rb")
    im = Image.open(fp)

To read an image from data that you have in a string, use the `StringIO` class:

Example: Reading from a string

    import StringIO

    im = Image.open(StringIO.StringIO(buffer))

Note that the library rewinds the file (using `seek(0)`) before reading the image header. In addition, seek will also be used when the image data is read (by the load method). If the image file is embedded in a larger file, such as a tar file, you can use the `ContainerIO` or `TarIO` modules to access it.

Example: Reading from a tar archive

    import TarIO

    fp = TarIO.TarIO("Imaging.tar", "Imaging/test/lena.ppm")
    im = Image.open(fp)

See comments in these modules for details.

### Controlling the Decoder

Some decoders allow you to manipulate the image while reading it from file. This can often be used to speed up decoding when creating thumbnails (when speed is usually be more important than quality) and printing to a monochrome laser printer (when only a greyscale version of the image is needed).

The `draft` method manipulates an opened but not yet loaded image so it as closely as possible matches the given mode and size. This is done by reconfiguring the image decoder.

Example: Reading in draft mode

    im = Image.open(file)
    print "original =", im.mode, im.size

    im.draft("L", (100, 100))
    print "draft =", im.mode, im.size

        original = RGB (512, 512)
        draft = L (128, 128)

Note that the resulting image may not exactly match the requested mode and size. To make sure that the image is not larger than the given size, use the `thumbnail` method instead.