使用opencv做瞳孔识别是十分方便的，它有很多好用的库可以直接使用。 废话不多说，直接上代码。
import cv2 import numpy as np cap = cv2.VideoCapture("eyes.mp4") while (True): ret, frame = cap.read() if ret is False: break roi = frame[100: 500, 157: 800] #利用切片工具，选出感兴趣roi区域 # cv2.imshow("show",roi) rows, cols, _ = roi.shape #保存视频尺寸以备用 gray_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY) #转灰度 gray_roi = cv2.GaussianBlur(gray_roi, (7, 7), 0) #高斯滤波一次 _, threshold = cv2.threshold(gray_roi, 8, 255, cv2.THRESH_BINARY_INV) #二值化，依据需要改变阈值 contours, _ = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #画连通域 contours = sorted(contours, key=lambda x: cv2.contourArea(x), reverse=True) for cnt in contours: (x, y, w, h) = cv2.boundingRect(cnt) #cv2.drawContours(roi, [cnt], -1, (0, 0, 255), 3) cv2.rectangle(roi, (x, y), (x + w, y + h), (255, 0, 0), 2) cv2.line(roi, (x + int(w/2), 0), (x + int(w/2), rows), (0, 255, 0), 2) cv2.line(roi, (0, y + int(h/2)), (cols, y + int(h/2)), (0, 255, 0), 2) break cv2.imshow("Roi", roi) cv2.imshow("Threshold", threshold) key = cv2.waitKey(30) if cv2.waitKey(1) & 0xff == ord('q'): break cap.release() cv2.destroyAllWindows()