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imshowtools contains simplified imshow functions to show multiple images and with other options

Project description


This library lets you view images in Jupyter notebooks in a much simpler and intuitive way. Ships with a better 'imshow' function with Multi Images, Smart Wrap and BGR support!.


To install imshowtools, simply do

pip install imshowtools

Quick Plot

Import imshow from imshowtools and use it:

from imshowtools import imshow
import tensorflow as tf
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()

imshow(x_train[0], x_train[1], x_train[2])
imshow(*x_train[:20], cmap='binary')
imshow(*x_train[:100], cmap='binary', size=(10, 10))

You can use any matplotlib compatible cmap


Example ipynb notebook and Python along with test images provided in the example folder.

Get Numpy Image

You can use obtain numpy image in any of ['RGB', 'RGBA', 'ARGB', 'BW', 'L', "BGR", "BGRA", "ABGR"] colorspaces.

image = imshow(*x_train[:100], return_image=True)
image = imshow(*x_train[:100], return_image="RGBA")
image = imshow(*x_train[:100], return_image="RGB")
image = imshow(*x_train[:100], return_image="BW")

# cv2.imwrite("saved_sample.png", image)
# do stuff with 'image' or even
# imshow(image)


(288, 432, 3)
(288, 432, 4)
(288, 432, 3)
(288, 432)

Rows and Columns

imshow(*x_train[:15], cmap='Purples', rows=1)
imshow(*x_train[:24], cmap='Greens', columns=4)


Open CV Images

lenna = cv2.imread('example/lenna.png')
imshow(lenna, mode='BGR')

image = imshow(*[lenna for _ in range(12)], return_image="BW")



If you do not want to use imshow directly in your app (maybe you have another function named imshow), you shall use it like

import imshowtools

or if you like to use a custom namespace

import imshowtools as my_namespace


Pull requests are very welcome.

  1. Fork the repo
  2. Create new branch with feature name as branch name
  3. Check if things work with a jupyter notebook
  4. Raise a pull request


Please see attached Licence

Project details

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