CofeehousePy/deps/scikit-image/doc/examples/data/plot_specific.py

64 lines
1.1 KiB
Python

"""
===============
Specific images
===============
"""
import matplotlib.pyplot as plt
import matplotlib
from skimage import data
matplotlib.rcParams['font.size'] = 18
######################################################################
#
# Stereo images
# =============
fig, axes = plt.subplots(1, 2, figsize=(8, 4))
ax = axes.ravel()
images = data.stereo_motorcycle()
ax[0].imshow(images[0])
ax[1].imshow(images[1])
fig.tight_layout()
plt.show()
######################################################################
#
# PIV images
# =============
fig, axes = plt.subplots(1, 2, figsize=(8, 4))
ax = axes.ravel()
images = data.vortex()
ax[0].imshow(images[0])
ax[1].imshow(images[1])
fig.tight_layout()
plt.show()
######################################################################
#
# Faces and non-faces dataset
# ===========================
#
# A sample of 20 over 200 images is displayed.
fig, axes = plt.subplots(4, 5, figsize=(20, 20))
ax = axes.ravel()
images = data.lfw_subset()
for i in range(20):
ax[i].imshow(images[90+i], cmap=plt.cm.gray)
ax[i].axis('off')
fig.tight_layout()
plt.show()