수수께끼 고양이

6x6x2 입력 import numpy as np np.random.seed(1) image=np.random.randint(5, size=(4,4,2)) print('image_0=\n', image[:,:,0]) print('image_1=\n', image[:,:,1]) filter=np.random.randint(5, size=(3,3,2)) print('filter_0=\n', filter[:,:,0]) print('filter_1=\n', filter[:,:,1]) image_pad=np.pad(image,((1,1),(1,1),(0,0))) print('image_pad_0=\n', image_pad[:,:,0]) print('image_pad_1=\n', image_pad[:,:,1]) c..

3x3x2 입력 이미지 import numpy as np np.random.seed(1) image=np.random.randint(5, size=(3,3,2)) print('image_0=\n', image[:,:,0]) print('image_1=\n', image[:,:,1]) filter=np.random.randint(5, size=(3,3,2)) print('filter_0=\n', filter[:,:,0]) print('filter_1=\n', filter[:,:,1]) image_x_filter=image*filter print('image_x_filter_0=\n', image_x_filter[:,:,0]) print('image_x_filter_1=\n', image_x_filter[:..

1. 1~9 사이의 정수값으로 구성된 3x3 랜덤 필터를 만들어 적용해보시오 import numpy as np import cv2 import matplotlib.pyplot as plt image_color=cv2.imread('../images/cat.jpg') print('image_color.shape =',image_color.shape) image=cv2.cvtColor(image_color,cv2.COLOR_BGR2GRAY) print('image.shape =',image.shape) np.random.seed(1) filter=np.random.randint(1,10, size=(3,3,3))/9 image_pad=np.pad(image,((1,1),(1,1))) print('image_..

선명한 이미지 추출하기 import numpy as np import cv2 import matplotlib.pyplot as plt image_color=cv2.imread('../images/cat.jpg') print('image_color.shape =',image_color.shape) image=cv2.cvtColor(image_color,cv2.COLOR_BGR2GRAY) print('image.shape =',image.shape) filter=np.array([ [-1,-1,-1], [-1,9,-1], [-1,-1,-1] ]) image_pad=np.pad(image,((5,5),(5,5))) print('image_pad.shape =', image_pad.shape) convoluti..

import numpy as np import cv2 import matplotlib.pyplot as plt image_bgr=cv2.imread('../images/cat.jpg') image=cv2.cvtColor(image_bgr,cv2.COLOR_BGR2RGB) print('image.shape =',image.shape) filter=np.array([[ [1,1,1], [1,1,1], [1,1,1] ],[ [1,1,1], [1,1,1], [1,1,1] ],[ [1,1,1], [1,1,1], [1,1,1] ]])/9 image_pad=np.pad(image,((1,1),(1,1),(0,0))) print('image_pad.shape =', image_pad.shape) convolution=..