Some of these examples use Visvis to visualize the image data, but one can also use Matplotlib to show the images.
Imageio provides a range of example images <standardimages>
, which can be used by using a URI like 'imageio:chelsea.png'
. The images are automatically downloaded if not already present on your system. Therefore most examples below should just work.
Probably the most important thing you ever need.
import imageio
im = imageio.imread('imageio:chelsea.png')
print(im.shape)
Imageio can read from filenames, file objects, http, zipfiles and bytes.
import imageio
import visvis as vv
im = imageio.imread('http://upload.wikimedia.org/wikipedia/commons/d/de/Wikipedia_Logo_1.0.png')
vv.imshow(im)
Note: reading from HTTP and zipfiles works for many formats including png and jpeg, but may not work for all formats (some plugins "seek" the file object, which HTTP/zip streams do not support). In such a case one can download/extract the file first. For HTTP one can use something like imageio.imread(imageio.core.urlopen(url).read(), '.gif')
.
import imageio
reader = imageio.get_reader('imageio:cockatoo.mp4')
for i, im in enumerate(reader):
print('Mean of frame %i is %1.1f' % (i, im.mean()))
(Screenshots are supported on Windows and OS X, clipboard on Windows only.)
import imageio
im_screen = imageio.imread('<screen>')
im_clipboard = imageio.imread('<clipboard>')
Use the special <video0>
uri to read frames from your webcam (via the ffmpeg plugin). You can replace the zero with another index in case you have multiple cameras attached.
import imageio
import visvis as vv
reader = imageio.get_reader('<video0>')
t = vv.imshow(reader.get_next_data(), clim=(0, 255))
for im in reader:
vv.processEvents()
t.SetData(im)
Here we take a movie and convert it to gray colors. Of course, you can apply any kind of (image) processing to the image here ...
import imageio
reader = imageio.get_reader('imageio:cockatoo.mp4')
fps = reader.get_meta_data()['fps']
writer = imageio.get_writer('~/cockatoo_gray.mp4', fps=fps)
for im in reader:
writer.append_data(im[:, :, 1])
writer.close()
import imageio
dirname = 'path/to/dicom/files'
# Read as loose images
ims = imageio.mimread(dirname, 'DICOM')
# Read as volume
vol = imageio.volread(dirname, 'DICOM')
# Read multiple volumes (multiple DICOM series)
vols = imageio.mvolread(dirname, 'DICOM')
import imageio
import visvis as vv
vol = imageio.volread('imageio:stent.npz')
vv.volshow(vol)