OpenCV Python 고급 활용 강좌 소스 코드 2

 

배열 병합

 

import cv2

src = cv2.imread("Image/tomato.jpg", cv2.IMREAD_COLOR)
hsv = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
h, s, v = cv2.split(hsv)

lower_red = cv2.inRange(hsv, (0, 100, 100), (5, 255, 255))
upper_red = cv2.inRange(hsv, (170, 100, 100), (180, 255, 255))
added_red = cv2.addWeighted(lower_red, 1.0, upper_red, 1.0, 0.0)

red = cv2.bitwise_and(hsv, hsv, mask = added_red)
red = cv2.cvtColor(red, cv2.COLOR_HSV2BGR)

cv2.imshow("red", red)
cv2.waitKey()
cv2.destroyAllWindows()

 

채널 분리 혹은 병합

 

import cv2

src = cv2.imread("Image/tomato.jpg", cv2.IMREAD_COLOR)
b, g, r = cv2.split(src)
inverse = cv2.merge((r, g, b))

cv2.imshow("b", b)
cv2.imshow("g", g)
cv2.imshow("r", r)
cv2.imshow("inverse", inverse)
cv2.waitKey()
cv2.destroyAllWindows()

 

도형 그리기

 

import cv2
import numpy as np

src = np.zeros((768, 1366, 3), dtype=np.uint8)

src = cv2.line(src, (100, 100), (1200, 100), (0, 0, 255), 3, cv2.LINE_AA)
src = cv2.circle(src, (300, 300), 50, (0, 255, 0), cv2.FILLED, cv2.LINE_4)
src = cv2.rectangle(src, (500, 200), (1000, 400), (255, 0, 0), 5, cv2.LINE_8)
src = cv2.ellipse(src, (1200, 300), (100, 50), 0, 90, 180, (255, 255, 0), 2)

pts1 = np.array([[100, 500], [300, 500], [200, 600]])
pts2 = np.array([[600, 500], [800, 500], [700, 600]])
src = cv2.polylines(src, [pts1], True, (0, 255, 255), 2)
src = cv2.fillPoly(src, [pts2], (255, 0, 255), cv2.LINE_AA)

src = cv2.putText(src, "CARELAB", (900, 600), cv2.FONT_HERSHEY_COMPLEX, 2, (255, 255, 255), 3)

cv2.imshow("src", src)
cv2.waitKey()
cv2.destroyAllWindows()

 

기하학적 변환

 

import cv2
import numpy as np

src = cv2.imread("Image/harvest.jpg", cv2.IMREAD_COLOR)
height, width, channel = src.shape

srcPoint = np.array([[300, 200], [400, 200], [500, 500], [200, 500]], dtype=np.float32)
dstPoint = np.array([[0, 0], [width, 0], [width, height], [0, height]], dtype=np.float32)

matrix = cv2.getPerspectiveTransform(srcPoint, dstPoint)
dst = cv2.warpPerspective(src, matrix, (width, height))

cv2.imshow("dst", dst)
cv2.waitKey()
cv2.destroyAllWindows()

 

영상 캡쳐와 녹화

 

import datetime
import cv2

capture = cv2.VideoCapture("/Image/Star.mp4")
fourcc = cv2.VideoWriter_fourcc(*'XVID')
record = False

while True:
    if(capture.get(cv2.CAP_PROP_POS_FRAMES) == capture.get(cv2.CAP_PROP_FRAME_COUNT)):
        capture.open("/Image/Star.mp4")

    ret, frame = capture.read()
    cv2.imshow("VideoFrame", frame)

    now = datetime.datetime.now().strftime("%d_%H-%M-%S")
    key = cv2.waitKey(33)

    if key == 27:
        break
    elif key == 26:
        print("캡쳐")
        cv2.imwrite("D:/" + str(now) + ".png", frame)
    elif key == 24
        print("녹화 시작")
        record = True
        video = cv2.VideoWriter("D:/" + str(now) + ".avi", fourcc, 20.0, (frame.shape[1], frame.shape[0]))
    elif key == 3
        print("녹화 중지")
        record = False
        video.release()
        
    if record == True:
        print("녹화 중..")
        video.write(frame)

capture.release()
cv2.destroyAllWindows()

 

윤곽선 검출

 

import cv2

src = cv2.imread("Image/contours.png", cv2.IMREAD_COLOR)

gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
ret, binary = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
binary = cv2.bitwise_not(binary)

contours, hierarchy = cv2.findContours(binary, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)

for i in range(len(contours)):
    cv2.drawContours(src, [contours[i]], 0, (0, 0, 255), 2)
    cv2.putText(src, str(i), tuple(contours[i][0][0]), cv2.FONT_HERSHEY_COMPLEX, 0.8, (0, 255, 0), 1)
    print(i, hierarchy[0][i])
    cv2.imshow("src", src)
    cv2.waitKey(0)

cv2.destroyAllWindows()

 

 

다각형 근사

 

import cv2

src = cv2.imread("Image/car.png", cv2.IMREAD_COLOR)

gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
ret, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU)
binary = cv2.bitwise_not(binary)

contours, hierarchy = cv2.findContours(binary, cv2.RETR_LIST, cv2.CHAIN_APPROX_TC89_KCOS)

for contour in contours:
    epsilon = cv2.arcLength(contour, True) * 0.02
    approx_poly = cv2.approxPolyDP(contour, epsilon, True)

    for approx in approx_poly:
        cv2.circle(src, tuple(approx[0]), 3, (255, 0, 0), -1)

cv2.imshow("src", src)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

 

코너 검출

 

import cv2

src = cv2.imread("Image/coffee.jpg")
dst = src.copy()

gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
corners = cv2.goodFeaturesToTrack(gray, 100, 0.01, 5, blockSize=3, useHarrisDetector=True, k=0.03)

for i in corners:
    cv2.circle(dst, tuple(i[0]), 3, (0, 0, 255), 2)

cv2.imshow("dst", dst)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

 

블록 껍질

 

import cv2

src = cv2.imread("Image/convex.png")
dst = src.copy()

gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
ret, binary = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY_INV)

contours, hierarchy = cv2.findContours(binary, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)

for i in contours:
    hull = cv2.convexHull(i, clockwise=True)
    cv2.drawContours(dst, [hull], 0, (0, 0, 255), 2)

cv2.imshow("dst", dst)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

모멘트

 

import cv2

src = cv2.imread("Image/convex.png")
dst = src.copy()

gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
ret, binary = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY_INV)

contours, hierarchy = cv2.findContours(binary, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)

for i in contours:
    M = cv2.moments(i)
    cX = int(M['m10'] / M['m00'])
    cY = int(M['m01'] / M['m00'])
    
    cv2.circle(dst, (cX, cY), 3, (255, 0, 0), -1)
    cv2.drawContours(dst, [i], 0, (0, 0, 255), 2)

cv2.imshow("dst", dst)
cv2.waitKey(0)
cv2.destroyAllWindows()