Pillow快速入门

使用 Image 类

PIL最重要的类是 Image class, 你可以通过多种方法创建这个类的实例；你可以从文件加载图像，或者处理其他图像, 或者从 scratch 创建。

要从文件加载图像，使用 open() 函数， 在 Image 模块:

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

加载成功将返回一个 Image 对象。 你现在可以使用示例属性检查文件内容:

>>> from __future__ import print_function
>>> print(im.format, im.size, im.mode)
PPM (512, 512) RGB

format 这个属性标识了图像来源。如果图像不是从文件读取它的值就是None。size属性是一个二元tuple，包含width和height（宽度和高度，单位都是px）。 mode 属性定义了图像bands的数量和名称，以及像素类型和深度。常见的modes 有 “L” (luminance) 表示灰度图像, “RGB” 表示真彩色图像, and “CMYK” 表示出版图像。

如果文件打开错误，返回 IOError 错误。

只要你有了 Image 类的实例，你就可以通过类的方法处理图像。比如，下列方法可以显示图像:

>>> im.show()

注解

标准的 show() 效率并不高，它需要保存图像到临时文件然后通过 xv 显示图像。你需要先安装 xv ，显示图像有助于调试和测试。

下面的部分提供了这个库其他函数的概览。

读写图像

PIL 模块支持大量图片格式。使用在 Image 模块的 open() 函数从磁盘读取文件。你不需要知道文件格式就能打开它，这个库能够根据文件内容自动确定文件格式。

要保存文件，使用 Image 类的 save() 方法。保存文件的时候文件名变得重要了。除非你指定格式，否则这个库将会以文件名的扩展名作为格式保存。

转换文件格式到JPEG

from __future__ import print_function
import os, sys
from PIL import Image

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

save() 方法的第二个参数可以指定文件格式，如果你使用非标准的扩展名你必须这样做：

创建 JPEG 缩略图

from __future__ import print_function
import os, sys
from PIL import Image

size = (128, 128)

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

很重要的一点是这个库不会直接解码或者加载图像栅格数据。当你打开一个文件，只会读取文件头信息用来确定格式，颜色模式，大小等等，文件的剩余部分不会主动处理。这意味着打开一个图像文件的操作十分快速，跟图片大小和压缩方式无关。下面是一个简单的脚本用来快速验证大量图片。

验证图像文件

from __future__ import print_function
import sys
from PIL import Image

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

剪切，粘贴，合并图像

Image 类包含的方法允许你操作图像部分选区。使用:py:meth:~PIL.Image.Image.crop 方法获取图像的一个子矩形选区。

从图像中复制出一个矩形选区

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

矩形选区有一个4元元组定义，分别表示左、上、右、下的坐标。这个库以左上角为坐标原点，单位是px，所以上诉代码复制了一个 300x300 pixels 的矩形选区。这个选区现在可以被处理并且粘贴到原图。

处理复制的矩形选区并粘贴到原图

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

当你粘贴矩形选区的时候必须保证尺寸一致。此外，矩形选区不能在图像外。然而你不必保证矩形选区和原图的颜色模式一致，因为矩形选区会被自动转换颜色（参看下面的 颜色变换 部分），下面是一个例子：

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:

分离和合并颜色通道

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

Note that for a single-band image, split() returns the image itself. To work with individual color bands, you may want to convert the image to “RGB” first.

几何变换

The PIL.Image.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.

简单的几何变换

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

To rotate the image in 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.

旋转图像

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.

颜色变换

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

颜色模式转换

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).

颜色增强

The Python Imaging Library provides a number of methods and modules that can be used to enhance images.

过滤器

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

应用过滤器

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

点操作

The point() method can be used to translate the pixel values of an image (e.g. image contrast manipulation). In most cases, a function object expecting one argument can be passed to the this method. Each pixel is processed according to that function:

应用点操作

# 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:

处理个别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 the portion 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.

增强

For more advanced image enhancement, you can 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, color balance and sharpness in this way.

增强图形

from PIL import ImageEnhance

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

多帧图像序列

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 move between different frames:

读取序列

from PIL 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 allow 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:

序列迭代 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 打印

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

Drawing Postscript

from PIL import Image
from PIL 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()

更多关于读取图像

As described earlier, the open() function of the Image module is used to open an image file. In most cases, you simply pass it the filename as an argument:

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

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

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

从文件读取

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

To read an image from string data, use the StringIO class:

从 string 读取

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.

从压缩包读取

from PIL import TarIO

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

控制解码器

Some decoders allow you to manipulate the image while reading it from a file. This can often be used to speed up decoding when creating thumbnails (when speed is usually 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.

Reading in draft mode

from __future__ import print_function
im = Image.open(file)
print("original =", im.mode, im.size)

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

This prints something like:

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.

https://pillow-cn.readthedocs.io/zh_CN/latest/handbook/tutorial.html