I would like to use an IPython notebook as a way to interactively analyze some genome charts I am making with Biopython’s GenomeDiagram module. While there is extensive documentation on how to use matplotlib to get graphs inline in IPython notebook, GenomeDiagram uses the ReportLab toolkit which I don’t think is supported for inline graphing in IPython.

I was thinking, however, that a way around this would be to write out the plot/genome diagram to a file and then open the image inline which would have the same result with something like this:

gd_diagram.write("test.png", "PNG")
display(file="test.png")

However, I can’t figure out how to do this – or know if it’s possible. So does anyone know if images can be opened/displayed in IPython?

Courtesy of this post, you can do the following:

from IPython.display import Image
Image(filename='test.png') 

(official docs)

If you are trying to display an Image in this way inside a loop, then you need to wrap the Image constructor in a display method.

from IPython.display import Image, display

listOfImageNames = ['/path/to/images/1.png',
                    '/path/to/images/2.png']

for imageName in listOfImageNames:
    display(Image(filename=imageName))

Note, until now posted solutions only work for png and jpg!

If you want it even easier without importing further libraries or you want to display an animated or not animated GIF File in your Ipython Notebook. Transform the line where you want to display it to markdown and use this nice short hack!

![alt text](test.gif "Title")

This will import and display a .jpg image in Jupyter (tested with Python 2.7 in Anaconda environment)

from IPython.display import display
from PIL import Image


path="/path/to/image.jpg"
display(Image.open(path))

You may need to install PIL

in Anaconda this is done by typing

conda install pillow

Courtesy of this page, I found this worked when the suggestions above didn’t:

import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
    a = np.uint8(a)
    f = StringIO()
    PIL.Image.fromarray(a).save(f, fmt)
    IPython.display.display(IPython.display.Image(data=f.getvalue()))

You could use in html code in markdown section: example:

 <img src="https://www.tensorflow.org/images/colab_logo_32px.png" />

A cleaner Python3 version that use standard numpy, matplotlib and PIL. Merging the answer for opening from URL.

import matplotlib.pyplot as plt
from PIL import Image
import numpy as np

pil_im = Image.open('image.png') #Take jpg + png
## Uncomment to open from URL
#import requests
#r = requests.get('https://www.vegvesen.no/public/webkamera/kamera?id=131206')
#pil_im = Image.open(BytesIO(r.content))
im_array = np.asarray(pil_im)
plt.imshow(im_array)
plt.show()

If you want to efficiently display big number of images I recommend using IPyPlot package

import ipyplot

ipyplot.plot_images(images_array, max_images=20, img_width=150)

There are some other useful functions in that package where you can display images in interactive tabs (separate tab for each label/class) which is very helpful for all the ML classification tasks.

When using GenomeDiagram with Jupyter (iPython), the easiest way to display images is by converting the GenomeDiagram to a PNG image. This can be wrapped using an IPython.display.Image object to make it display in the notebook.

from Bio.Graphics import GenomeDiagram
from Bio.SeqFeature import SeqFeature, FeatureLocation
from IPython.display import display, Image
gd_diagram = GenomeDiagram.Diagram("Test diagram")
gd_track_for_features = gd_diagram.new_track(1, name="Annotated Features")
gd_feature_set = gd_track_for_features.new_set()
gd_feature_set.add_feature(SeqFeature(FeatureLocation(25, 75), strand=+1))
gd_diagram.draw(format="linear", orientation="landscape", pagesize='A4',
                fragments=1, start=0, end=100)
Image(gd_diagram.write_to_string("PNG"))

[See Notebook]