<jupyter_start><jupyter_text>Here I'm going to test the details of the Read_Video.py . Let's test a sample from LLO class of videos :<jupyter_code>y = read_video.read_video('/Users/mojtaba/Desktop/OrNet Project/DAT VIDEOS/LLO/DsRed2-HeLa_2_21_LLO_Cell0.mov')
y2 = np.array(y[1:])
y2.shape

y3 = y2[0,:,:,:]
y3.shape
import matplotlib.pyplot as plt
plt.imshow(y3[1,:,:])

for i in range (0,130,10):
    plt.imshow(y3[i,:,:])
    plt.show()<jupyter_output><empty_output><jupyter_text>Now we test a sample video  from Control movies.<jupyter_code>y = read_video.read_video('/Users/mojtaba/Desktop/OrNet Project/DAT VIDEOS/Control/DsRed2-HeLa_10_26_Cell5.mov')
y2 = np.array(y[1:])
y2.shape
y3 = y2[0,:,:,:]
y3.shape
for i in range (0,130,10):
    plt.imshow(y3[i,:,:])
    plt.show()
y = read_video.read_video('/Users/mojtaba/Desktop/OrNet Project/DAT VIDEOS/Control/DsRed2-HeLa_10_26_Cell0.mov')
yt = y[1]
for i in range (0,130,10):
    plt.imshow(yt[i,:,:])
    plt.show()<jupyter_output>/Users/mojtaba/anaconda3/lib/python3.6/site-packages/skimage/util/dtype.py:122: UserWarning: Possible precision loss when converting from float64 to uint8
  .format(dtypeobj_in, dtypeobj_out))
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