Robert W. Rose

In no particular order:

• Template metaprogramming is still evil, and C++11/14 hasn’t fixed anything about it. People argue metaprogramming enables “clean, elegant code,” as if a home built on a garbage dump won’t smell like garbage. If anyone else needs to repair or extend the foundation of your home they’ll need to parse through your garbage pile to make changes. Template metaprogramming as a rule should simply never be done outside low-level libraries.
• auto is too easy to abuse. Oh but, “the IDE makes auto easier to read!” Go back to Java. auto does have a few good uses, clang-tidy provides excellent guidance on where its effective, its guidance should be followed.
• Large lambdas harm readability. They make the control flow of the program harder to parse and discourage self documenting code. Lambdas should be limited to 2-3 statements. And please, if you write a lambda, mean it: don’t write a lambda where you could have just as easily written a standalone function.

You can rip a sequence of images into an mp4 and display it inline in an ipython notebook using a function like this:

import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import display, HTML
def plot_movie_mp4(image_array):
dpi = 72.0
xpixels, ypixels = image_array[0].shape[0], image_array[0].shape[1]
fig = plt.figure(figsize=(ypixels/dpi, xpixels/dpi), dpi=dpi)
im = plt.figimage(image_array[0])
def animate(i):
im.set_array(image_array[i])
return (im,)
anim = animation.FuncAnimation(fig, animate, frames=len(image_array))
display(HTML(anim.to_html5_video()))

However there’s a disadvantage with this method: You have no control over the encoding settings so you’re likely to get a video with a lot of artifacts.

If you would like a video without artifacts, check out JSAnimation. This sends the sequence of images to the browser along with some javascript to play through them. This looks much better and is much easier to control than an html5 video control:

from JSAnimation import IPython_display
def plot_movie_js(image_array):
dpi = 72.0
xpixels, ypixels = image_array[0].shape[0], image_array[0].shape[1]
fig = plt.figure(figsize=(ypixels/dpi, xpixels/dpi), dpi=dpi)
im = plt.figimage(image_array[0])
def animate(i):
im.set_array(image_array[i])
return (im,)
anim = animation.FuncAnimation(fig, animate, frames=len(image_array))
display(IPython_display.display_animation(anim))

16.04 uses gcc 5.4 by default. You’ll need to install gcc 4.9 and configure OpenCV to use 4.9 instead:

sudo apt-get install g++-4.9
cmake -DCMAKE_C_COMPILER=/usr/bin/gcc-4.9 -DCMAKE_CXX_COMPILER=/usr/bin/g++-4.9 .

If you have CUDA installed you may want to disable compiling the CUDA libraries as well, or else suffer another hour+ of compilation time. Add -DWITH_CUDA=OFF to disable CUDA.