- Published on
OpenCV 이미지 변환
- Authors
- Name
- Inhwan Cho
Grayscale, GaussianBlur
import cv2
img = cv2.imread('cat_img.jpg')
# 컬러 -> 흑백으로 변환
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# ksize == kernel size이므로 홀수만 사용 가능, sigmaX는 블러 정도라고 생각하면 편하며,
# 보통 -3~3사이의 값을 사용
imgBlur = cv2.GaussianBlur(imgGray, ksize=(7,7),sigmaX=3)
cv2.imshow('output',imgGray)
cv2.imshow('output2',imgBlur)
cv2.waitKey(0)
- 결과 imgGray

- 결과 imgBlur

Canny, Dialation
import cv2
img = cv2.imread('cat_img.jpg')
imgCanny = cv2.Canny(img,100,100)
kernel = np.ones((5,5), np.uint8)
# iterations에 높은 수를 넣으면 윤곽선이 더 커집니다.
imgDialation = cv2.dilate(imgCanny, kernel=kernel,iterations=1)
imgEroded = cv2.erode(imgDialation, kernel=kernel, iterations=1)
cv2.imshow('output3',imgCanny)
cv2.imshow('output4',imgDialation)
cv2.imshow('output5',imgEroded)
cv2.waitKey(0)
- 결과 imgCanny

- 결과 imgDialation

- 결과 imgEroded
