Run all the cells below to make sure everything is working and ready to go. All cells should run without error.

Test Matplotlib and Plotting



In [1]:

    
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
%matplotlib inline



In [2]:

    
img = mpimg.imread('test.jpg')
plt.imshow(img)









    Out[2]:





<matplotlib.image.AxesImage at 0x11201a208>

Test OpenCV



In [3]:

    
import cv2



In [4]:

    
# convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
plt.imshow(gray, cmap='Greys_r')









    Out[4]:





<matplotlib.image.AxesImage at 0x11af2a860>

Test TensorFlow



In [5]:

    
import tensorflow as tf



In [6]:

    
with tf.Session() as sess:
    a = tf.constant(1)
    b = tf.constant(2)
    c = a + b
    # Should be 3
    print("1 + 2 = {}".format(sess.run(c)))

Test Moviepy



In [8]:

    
# Import everything needed to edit/save/watch video clips
from moviepy.editor import VideoFileClip
from IPython.display import HTML

Create a new video with moviepy by processing each frame to YUV color space.



In [9]:

    
new_clip_output = 'test_output.mp4'
test_clip = VideoFileClip("test.mp4")
new_clip = test_clip.fl_image(lambda x: cv2.cvtColor(x, cv2.COLOR_RGB2YUV)) #NOTE: this function expects color images!!
%time new_clip.write_videofile(new_clip_output, audio=False)









    



[MoviePy] >>>> Building video test_output.mp4
[MoviePy] Writing video test_output.mp4






    



100%|██████████| 251/251 [00:05<00:00, 44.14it/s]






    



[MoviePy] Done.
[MoviePy] >>>> Video ready: test_output.mp4 

CPU times: user 2.33 s, sys: 418 ms, total: 2.75 s
Wall time: 6.88 s



In [10]:

    
HTML("""
<video width="640" height="300" controls>
  <source src="{0}" type="video/mp4">
</video>
""".format(new_clip_output))









    Out[10]:



In [ ]: