Matplotlib는 배열의 2D 플롯을 위한 Python의 놀라운 시각화 라이브러리입니다. Matplotlib는 NumPy 어레이를 기반으로 구축되고 더 광범위한 SciPy 스택과 함께 작동하도록 설계된 다중 플랫폼 데이터 시각화 라이브러리입니다.
예
#applying pseudocolor
# importing pyplot and image from matplotlib
import matplotlib.pyplot as plt
import matplotlib.image as img
# reading png image
im = img.imread('imR.png')
# applying pseudocolor
# default value of colormap is used.
lum = im[:, :, 0]
# show image
plt.imshow(lum)
#colorbar
# importing pyplot and image from matplotlib
import matplotlib.pyplot as plt
import matplotlib.image as img
# reading png image
im = img.imread('imR.png')
lum = im[:, :, 0]
# setting colormap as hot
plt.imshow(lum, cmap ='hot')
plt.colorbar()
#interpolation
# importing PIL and matplotlib
from PIL import Image
import matplotlib.pyplot as plt
# reading png image file
img = Image.open('imR.png')
# resizing the image
img.thumbnail((50, 50), Image.ANTIALIAS)
imgplot = plt.imshow(img)
#bicubic value for interpolation
# importing pyplot from matplotlib
import matplotlib.pyplot as plt
# importing image from PIL
from PIL import Image
# reading image
img = Image.open('imR.png')
img.thumbnail((30, 30), Image.ANTIALIAS)
# bicubic used for interpolation
imgplot = plt.imshow(img, interpolation ='bicubic')#sinc value for interpolation
# sinc value for interpolation
# importing PIL and matplotlib
from PIL import Image
import matplotlib.pyplot as plt
# reading image
img = Image.open('imR.png')
img.thumbnail((30, 30), Image.ANTIALIAS)
# sinc used for interpolation
imgplot = plt.imshow(img, interpolation ='sinc')