Python使用scipy和numpy操作处理图像

之前使用Python处理数据的时候都是一些简单的plot。今天遇见了需要处理大量像素点，并且显示成图片的问题，无奈水浅，一筹莫展。遂Google之。

找到如下站点，真心不错。准备翻译之~~~

http://scipy-lectures.github.io/advanced/image_processing/index.html

2.6.1. Opening and writing to image files

Writing an array to a file:

from scipy import miscl = misc.lena()misc.imsave('lena.png', l) # uses the Image module (PIL)import matplotlib.pyplot as pltplt.imshow(l)plt.show()

Creating a numpy array from an image file:

>>>

>>> from scipy import misc>>> lena = misc.imread('lena.png')>>> type(lena)<type 'numpy.ndarray'>>>> lena.shape, lena.dtype((512, 512), dtype('uint8'))

dtype is uint8 for 8-bit images (0-255)

Opening raw files (camera, 3-D images)

>>>

>>> l.tofile('lena.raw') # Create raw file>>> lena_from_raw = np.fromfile('lena.raw', dtype=np.int64)>>> lena_from_raw.shape(262144,)>>> lena_from_raw.shape = (512, 512)>>> import os>>> os.remove('lena.raw')

Need to know the shape and dtype of the image (how to separate databytes).

For large data, use np.memmap for memory mapping:

>>>

>>> lena_memmap = np.memmap('lena.raw', dtype=np.int64, shape=(512, 512))

(data are read from the file, and not loaded into memory)

Working on a list of image files

>>>

>>> for i in range(10):...     im = np.random.random_integers(0, 255, 10000).reshape((100, 100))...     misc.imsave('random_%02d.png' % i, im)>>> from glob import glob>>> filelist = glob('random*.png')>>> filelist.sort()

2.6.2. Displaying images

Use matplotlib and imshow to display an image inside amatplotlibfigure:

>>>

>>> l = misc.lena()>>> import matplotlib.pyplot as plt>>> plt.imshow(l, cmap=plt.cm.gray)<matplotlib.image.AxesImage object at 0x3c7f710>

Increase contrast by setting min and max values:

>>>

>>> plt.imshow(l, cmap=plt.cm.gray, vmin=30, vmax=200)<matplotlib.image.AxesImage object at 0x33ef750>>>> # Remove axes and ticks>>> plt.axis('off')(-0.5, 511.5, 511.5, -0.5)

Draw contour lines:

>>>

>>> plt.contour(l, [60, 211])<matplotlib.contour.ContourSet instance at 0x33f8c20>

[Python source code]