📗 -> Lecture Date: Name
🎤 Vocab
Most important Python-Packages:
- Numpy
- Matplot
- Scikit-Image
❗ Unit and Larger Context
A image is stored as a 3D array:
- X and Y coords are 2D
- RGB values are the third D (pause)
Example First Row of Image:
<class 'numpy.ndarray'> (426, 640, 3) 255 0
[[240 239 219]
[240 239 219]
[240 239 219]
...
[228 227 197]
[228 227 196]
[227 226 195]]
Todo
Refresh on Numpy syntax and operations
Remember that images are unsigned integers but whenever you need to process them (e.g. apply a blur filter) you need to convert the images into float data type and preferably in the range 0 to 1. Always remember this to and fro conversion between float and integer. See another example below.
fig, axes = plt.subplots(2,2, figsize=(20, 20))
axes[0][0].imshow(im)
axes[0][1].imshow(im+50)
axes[1][0].imshow(np.clip(im+50, 0, 255))
axes[1][1].imshow(np.clip(im.astype('float')+50, 0, 255).astype('uint8'))
for ax in axes.flatten():
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])
plt.tight_layout()
✒️ -> Scratch Notes
- Log as you go through entry
🧪-> Example
- List examples of where entry contents can fit in a larger context
🔗 -> Related Word
- Link all related words