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fanfuhan OpenCV 教學016 ~ opencv-016-圖像ROI與ROI操作(簡單使用HSV產生ROI實作 前後景分離/去背) 資料來源: https://fanfuhan.github.io/ https://fanfuhan.github.io/2019/03/28/opencv-016/ GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV 圖像的ROI(region of interest)是指圖像中感興趣區域、在OpenCV中圖像設置圖像ROI區域，實現只對ROI區域操作。 01.矩形ROI區域提取 02.矩形ROI區域copy ~ 拷貝(複製)原圖的部分內容成為一張新圖 03.不規則ROI區域 ~使用BGR2HSV將綠色背景分離，並取前景，最後合成新圖     – ROI區域mask生成     – 像素位and操作     – 提取到ROI區域     – 加背景or操作     – add 背景與ROI區域 C++ #include #include using namespace std; using namespace cv; /* * ROI及相关操作 */ int main() { Mat src = imread("../images/test.png"); imshow("input", src); int h = src.rows; int w = src.cols; // 获取ROI int cy = h / 2; int cx = w / 2; Rect rect(cx - 100, cy - 100, 200, 200); // 注意：roi 与 src指向同一块内存区域，改变roi,src也会改变 Mat roi = src(rect); imshow("roi", roi); // 人物背景图，换背景 // load image Mat image = imread("../images/boy.jpg"); imshow("input", image); // generate mask Mat hsv, mask, mask_not; cvtColor(image, hsv, COLOR_BGR2HSV); inRange(hsv, Scalar(35, 43, 46), Scalar(99, 255, 255), mask); imshow("mask", mask); // extract person Mat person; bitwise_not(mask, mask_not); imshow("mask_not", mask_not); bitwise_and(image, image, person, mask_not); imshow("person", person); // gengerate background Mat background = Mat::zeros(image.size(), image.type()); background.setTo(Scalar(255, 0 ,0)); imshow("background", background); // combine background + person Mat dst; bitwise_or(person, background, dst, mask); add(dst, person, dst); imshow("dst", dst); waitKey(0); return 0; } Python import cv2 as cv import numpy as np src = cv.imread("D:/javaopencv/dahlia_4.jpg") cv.namedWindow("input", cv.WINDOW_AUTOSIZE) cv.imshow("input", src) h, w = src.shape[:2] # 获取ROI cy = h//2 cx = w//2 roi = src[cy-100:cy+100,cx-100:cx+100,:] cv.imshow("roi", roi) # copy ROI image = np.copy(roi) # modify ROI roi[:, :, 0] = 0 cv.imshow("result", src) # modify copy roi image[:, :, 2] = 0 cv.imshow("result", src) cv.imshow("copy roi", image) # example with ROI - generate mask src2 = cv.imread("D:/javaopencv/tinygreen.png"); cv.imshow("src2", src2) hsv = cv.cvtColor(src2, cv.COLOR_BGR2HSV) mask = cv.inRange(hsv, (35, 43, 46), (99, 255, 255)) # extract person ROI mask = cv.bitwise_not(mask) person = cv.bitwise_and(src2, src2, mask=mask); # generate background result = np.zeros(src2.shape, src2.dtype) result[:,:,0] = 255 # combine background + person mask = cv.bitwise_not(mask) dst = cv.bitwise_or(person, result, mask=mask) dst = cv.add(dst, person) cv.imshow("dst", dst) cv.waitKey(0) cv.destroyAllWindows()