영상처리 Chap01_그림불러오기/화면출력/저장하기

1. Pillow API : https://pillow.readthedocs.io/en/stable/index.html
2. PIL의 Image 사용하여 열기
   
   from PIL import Image import matplotlib.pyplot as plt im = Image.open("./images/whale.jpg") plt.imshow(im)

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   from PIL import Image import matplotlib.pyplot as plt   im = Image.open("./images/whale.jpg")   plt.imshow(im)

   
   
3. Image.convert() 함수를 사용하여 Grayscale로 변환하기
   
   from PIL import Image import matplotlib.pyplot as plt im = Image.open("./images/whale.jpg") im_g = im.convert('L') plt.figure(figsize=(10, 5)) plt.subplot(1,2,1) plt.axis('off') plt.imshow(im) plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray')

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   from PIL import Image import matplotlib.pyplot as plt   im = Image.open("./images/whale.jpg") im_g = im.convert('L')   plt.figure(figsize=(10, 5))   plt.subplot(1,2,1) plt.axis('off') plt.imshow(im)   plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray')

   
   
   1. API 설명 : https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.convert
   2. mode 종류 : 1,  L,  P,  RGB,  RGBA,  CMYK,  YCbCr,  LAB,  HSV,  I,  F
4. Image.resize() 함수를 사용하여 그림 크기 변환하기
   
   from PIL import Image import matplotlib.pyplot as plt im = Image.open('./images/whale.jpg') im_large = im.resize((im.width // 20, im.height // 20), Image.BILINEAR) print((im.width, im.height), (im_large.width, im_large.height)) plt.figure(figsize=(10, 5)) plt.subplot(1, 2, 1); plt.imshow(im) plt.subplot(1, 2, 2); plt.imshow(im_large)

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   from PIL import Image import matplotlib.pyplot as plt   im = Image.open('./images/whale.jpg') im_large = im.resize((im.width // 20, im.height // 20), Image.BILINEAR) print((im.width, im.height), (im_large.width, im_large.height))   plt.figure(figsize=(10, 5)) plt.subplot(1, 2, 1); plt.imshow(im) plt.subplot(1, 2, 2); plt.imshow(im_large)

   
   
   1. API 설명 : https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.resize
   2. Image.resize(size, resample=None, box=None, reducing_gap=None)
   3. size = (width, height)
   4. resample : PIL.Image.NEAREST, PIL.Image.BOX, PIL.Image.BILINEAR, PIL.Image.HAMMING, PIL.Image.BICUBIC, PIL.Image.LANCZOS
5. Image.split() 함수를 사용하여 그림을 채널별로 나누기
   
   from PIL import Image import matplotlib.pyplot as plt im = Image.open('./images/whale.jpg') #open image r, g, b = im.split() # img는 RGB #im2 = im.convert("RGBA") # convert to RGBA #r, g, b, a = im2.split() # img2는 RGBA plt.figure(figsize=(10, 6)) plt.subplot(2, 2, 1); plt.axis('off'); plt.imshow(im) plt.subplot(2, 2, 2); plt.axis('off'); plt.imshow(r, cmap=plt.cm.Reds) plt.subplot(2, 2, 3); plt.axis('off'); plt.imshow(g, cmap=plt.cm.Greens) plt.subplot(2, 2, 4); plt.axis('off'); plt.imshow(b, cmap=plt.cm.Blues)

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   from PIL import Image import matplotlib.pyplot as plt   im = Image.open('./images/whale.jpg') #open image r, g, b = im.split()  # img는 RGB   #im2 = im.convert("RGBA")  # convert to RGBA #r, g, b, a = im2.split()   # img2는 RGBA   plt.figure(figsize=(10, 6))   plt.subplot(2, 2, 1); plt.axis('off'); plt.imshow(im) plt.subplot(2, 2, 2); plt.axis('off'); plt.imshow(r, cmap=plt.cm.Reds) plt.subplot(2, 2, 3); plt.axis('off'); plt.imshow(g, cmap=plt.cm.Greens) plt.subplot(2, 2, 4); plt.axis('off'); plt.imshow(b, cmap=plt.cm.Blues)

   
   
   1. API 설명 : https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.split
   2. 읽어온 그림이 RGB나 HSV와 같이 채널이 3개면 3개값 리턴,
   3. RGBA와 같이 채널이 4개면 4개값 리턴

1. skimage API : https://scikit-image.org/docs/stable/api/api.html
2. PIL의 Image 사용하여 열기
   
   from skimage.io import imread import matplotlib.pyplot as plt im = imread("./images/whale.jpg") plt.imshow(im)

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   from skimage.io import imread import matplotlib.pyplot as plt   im = imread("./images/whale.jpg")   plt.imshow(im)

   
   
   1. API 설명 : https://scikit-image.org/docs/stable/api/skimage.io.html#imread
3. color.rgb2gray() 함수를 사용하여 Grayscale로 변환하기
   
   from skimage.io import imread from skimage.color import rgb2gray import matplotlib.pyplot as plt im = imread("./images/whale.jpg") im_g = rgb2gray(im) plt.figure(figsize=(10, 5)) plt.subplot(1,2,1) plt.axis('off') plt.imshow(im) plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray')

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   from skimage.io import imread from skimage.color import rgb2gray import matplotlib.pyplot as plt   im = imread("./images/whale.jpg")   im_g = rgb2gray(im)   plt.figure(figsize=(10, 5))   plt.subplot(1,2,1) plt.axis('off') plt.imshow(im)   plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray')

   
   
   1. API 설명 : https://scikit-image.org/docs/stable/api/skimage.color.html#rgb2gray
4. transform.resize() 함수를 사용하여 그림 크기 변환하기
   
   from skimage.io import imread from skimage.transform import resize import matplotlib.pyplot as plt im = imread("./images/whale.jpg") im_large = resize(im, (im.shape[0] // 20, im.shape[1] // 20)) print(im.shape, im_large.shape) plt.figure(figsize=(10, 5)) plt.subplot(1, 2, 1); plt.imshow(im) plt.subplot(1, 2, 2); plt.imshow(im_large)

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   from skimage.io import imread from skimage.transform import resize import matplotlib.pyplot as plt   im = imread("./images/whale.jpg")   im_large = resize(im, (im.shape[0] // 20, im.shape[1] // 20)) print(im.shape, im_large.shape)   plt.figure(figsize=(10, 5)) plt.subplot(1, 2, 1); plt.imshow(im) plt.subplot(1, 2, 2); plt.imshow(im_large)

   
   
   1. API 설명 : https://scikit-image.org/docs/stable/api/skimage.transform.html#resize
5. numpy array를 나누어 그림을 채널별로 나누기
   
   from skimage.io import imread import matplotlib.pyplot as plt im = imread("./images/whale.jpg") r, g, b = im[:,:,0], im[:,:,1], im[:,:,2] # img는 RGB #r, g, b = im[:,:,0], im[:,:,1], im[:,:,2], im[:,:,3] # img는 RGBA plt.figure(figsize=(10, 6)) plt.subplot(2, 2, 1); plt.axis('off'); plt.imshow(im) plt.subplot(2, 2, 2); plt.axis('off'); plt.imshow(r, cmap=plt.cm.Reds) plt.subplot(2, 2, 3); plt.axis('off'); plt.imshow(g, cmap=plt.cm.Greens) plt.subplot(2, 2, 4); plt.axis('off'); plt.imshow(b, cmap=plt.cm.Blues)

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   from skimage.io import imread import matplotlib.pyplot as plt   im = imread("./images/whale.jpg") r, g, b = im[:,:,0], im[:,:,1], im[:,:,2]              # img는 RGB #r, g, b = im[:,:,0], im[:,:,1], im[:,:,2], im[:,:,3]  # img는 RGBA   plt.figure(figsize=(10, 6))   plt.subplot(2, 2, 1); plt.axis('off'); plt.imshow(im) plt.subplot(2, 2, 2); plt.axis('off'); plt.imshow(r, cmap=plt.cm.Reds) plt.subplot(2, 2, 3); plt.axis('off'); plt.imshow(g, cmap=plt.cm.Greens) plt.subplot(2, 2, 4); plt.axis('off'); plt.imshow(b, cmap=plt.cm.Blues)

   
   

함수를 사용하지 않고 직접 처리하기

1. RGB 영상을 Grayscale로 변환하기
   
   from skimage.io import imread import matplotlib.pyplot as plt from PIL import Image import numpy as np im = imread("./images/whale.jpg") im_g = im[:,:,0] * 0.299 + im[:,:,1] * 0.587 + im[:,:,2] * 0.114 im_g = np.clip(im_g, 0, 255) plt.figure(figsize=(10, 5)) plt.subplot(1,2,1) plt.axis('off') plt.imshow(im) plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray') print(im.shape, im_g.shape)

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   from skimage.io import imread import matplotlib.pyplot as plt from PIL import Image import numpy as np   im = imread("./images/whale.jpg")   im_g = im[:,:,0] * 0.299 + im[:,:,1] * 0.587 + im[:,:,2] * 0.114 im_g = np.clip(im_g, 0, 255)   plt.figure(figsize=(10, 5))   plt.subplot(1,2,1) plt.axis('off') plt.imshow(im)   plt.subplot(1,2,2) plt.axis('off') plt.imshow(im_g, cmap='gray')   print(im.shape, im_g.shape)