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fanfuhan OpenCV 教學078 ~ opencv-078-識別(尋找/標記)與跟踪(鎖定/定位)視頻中的特定顏色對象 資料來源: https://fanfuhan.github.io/ https://fanfuhan.github.io/2019/04/24/opencv-078/ GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV 圖像處理與二值分析的視頻版本，通過讀取視頻每一幀的圖像，然後對圖像二值分析，得到指定的色塊區域，主要步驟如下：     色彩轉換BGR2HSV     inRange提取顏色區域mask     對mask區域進行二值分析得到位置與輪廓信息     繪製外接橢圓與中心位置     顯示結果 其中涉及到的知識點主要包括圖像處理、色彩空間轉換、形態學、輪廓分析等。 C++ #include #include using namespace std; using namespace cv; void process_frame(Mat &image); /* * 识别与跟踪视频中的特定颜色对象 */ int main() { VideoCapture capture("../images/color_object.mp4"); if (!capture.isOpened()) { printf("could not open camera...\n"); return -1; } int fps = capture.get(CAP_PROP_FPS); int width = capture.get(CAP_PROP_FRAME_WIDTH); int height = capture.get(CAP_PROP_FRAME_HEIGHT); int num_of_frames = capture.get(CAP_PROP_FRAME_COUNT); printf("frame width: %d, frame height: %d, FPS : %d \n", width, height, fps); Mat frame; while (true) { bool ret = capture.read(frame); if (!ret) break; imshow("input", frame); char c = waitKey(50); process_frame(frame); imshow("result", frame); if (c == 27) { break; } } waitKey(0); return 0; waitKey(0); return 0; } void process_frame(Mat &image) { Mat hsv, mask; // 转换色彩空间 cvtColor(image, hsv, COLOR_BGR2HSV); // 提取颜色区域mask inRange(hsv, Scalar(0, 43, 46), Scalar(10, 255, 255), mask); Mat se = getStructuringElement(MORPH_RECT, Size(15, 15)); morphologyEx(mask, mask, MORPH_OPEN, se); // 寻找最大轮廓 vector> contours; vector hierarchy; findContours(mask, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE); int index = -1; int max = 0; for (size_t t = 0; t < contours.size(); t++) { double area = contourArea(contours[t]); if (area > max) { max = area; index = t; } } // 绘制外接轮廓 if (index >= 0) { RotatedRect rect = minAreaRect(contours[index]); ellipse(image, rect, Scalar(0, 255, 0), 2); circle(image, rect.center, 2, Scalar(255, 0, 0), 2); } } Python import cv2 as cv import numpy as np capture = cv.VideoCapture("D:/images/video/test.mp4") height = capture.get(cv.CAP_PROP_FRAME_HEIGHT) width = capture.get(cv.CAP_PROP_FRAME_WIDTH) count = capture.get(cv.CAP_PROP_FRAME_COUNT) fps = capture.get(cv.CAP_PROP_FPS) print(height, width, count, fps) def process(image, opt=1): hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV) line = cv.getStructuringElement(cv.MORPH_RECT, (15, 15), (-1, -1)) mask = cv.inRange(hsv, (0, 43, 46), (10, 255, 255)) mask = cv.morphologyEx(mask, cv.MORPH_OPEN, line) # 轮廓提取, 发现最大轮廓 out, contours, hierarchy = cv.findContours(mask, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) index = -1 max = 0 for c in range(len(contours)): area = cv.contourArea(contours[c]) if area > max: max = area index = c # 绘制 if index >= 0: rect = cv.minAreaRect(contours[index]) cv.ellipse(image, rect, (0, 255, 0), 2, 8) cv.circle(image, (np.int32(rect[0][0]), np.int32(rect[0][1])), 2, (255, 0, 0), 2, 8, 0) return image while(True): ret, frame = capture.read() if ret is True: cv.imshow("video-input", frame) result = process(frame) cv.imshow("result", result) c = cv.waitKey(50) print(c) if c == 27: #ESC break else: break cv.waitKey(0) cv.destroyAllWindows()