tqdm

imageio

Seaborn

tqdm : Progress bars for the command line or Jupyter notebook

tqdm

from tqdm import tqdm for i in tqdm([a, b, c, d, ..]): ...

41%|███████████████ | 4080/10000 [00:04<00:06, 895.98it/s]

len()

tqdm

tqdm_notebook

tqdm

Install tqdm

tqdm

pip install tqdm pip3 install tqdm conda install tqdm

imageio : Load and save images

imageio

.imread(uri,..)

.imwrite(uri, image,..)

import imageio image = imageio.imread('./cat.png') # You can manipulate the image as a numpy array. image = image[:500] image.imwrite('./half_cat.png', image)

imageio

Install imageio

imageio

pip install imageio pip3 install imageio conda install imageio

Seaborn : Create beautiful graphs and visualizations

Seaborn

Install seaborn

seaborn

pip install seaborn pip3 install seaborn conda install seaborn

Learn how to useto display command line and Jupyter progress bars,to easily load and save images andto create beautiful graphs and visualizations.Import thefunction from the module. Then wrap it around any iterable used in a for loop to create a progress bar.(like a list or a numpy array but unlike a generator) it will also display the progress percentage and estimated time left. You can also usein Jupyter notebook by importing thefunction.also has some more advanced functionality for nested loops, labeled loops and color-coding exit status, all of which you can see in their great documentation Installwith pip (pip3 for Python 3)conda:Import, then useandto read and write images.can also read volumetric and medical data, read frames from a video file, or open an url. It supports a ton of different file formats and parameters and also has a great documentation Installwith pip (pip3 for Python 3)conda:is basically an extension to matplotlib that allows you to use its normal plotting functions but applies really pretty styles to them. It also provides some additional functions not available in matplotlib. Check out their example library and getting started guide Here is the jupyter notebook for the following examples.Installwith pip (pip3 for Python 3)conda: