Question

我正在尝试使用OpenCV跟踪瞳孔，假设瞳孔始终是黑色的，但是我要经历的最大挑战是对瞳孔的反射，有没有办法我可以通过改变瞳孔的眩光颜色周围可见的瞳孔颜色是什么？

请在下面找到代码块

from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2
from matplotlib import pyplot as plt
import sys
import os
import time
import math

ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
    help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
    help="path to input image")
args = vars(ap.parse_args())

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

image = cv2.imread(args["image"])
image = imutils.resize(image, width=1080)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

rects = detector(gray, 1)

for (i, rect) in enumerate(rects):
    shape = predictor(gray, rect)
    shape = face_utils.shape_to_np(shape)
    for (name, (i, j)) in face_utils.FACIAL_LANDMARKS_IDXS.items():
        if(name == "left_eye"):
            listval = shape[i:j].tolist()
            del listval[3]
            del listval[0]
            (x, y, w, h) = cv2.boundingRect(np.array([listval]))
            roi = image[y:y + h, x:x + w]
            roi = imutils.resize(roi, width=250, inter=cv2.INTER_CUBIC)
            grey = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
            imgHSV = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
            _, img1 = cv2.threshold(grey, 26 , 255, cv2.THRESH_BINARY)
            cv2.imshow("ROI_1", roi)
            img1 = cv2.erode(img1, None, iterations=2) #1
            img1 = cv2.dilate(img1, None, iterations=4) #2
            img1 = cv2.medianBlur(img1, 5) #3
            contours, hierarchy = cv2.findContours(img1, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
            drawing = np.copy(roi)
            cv2.drawContours(drawing, contours, -1, (255, 0, 0), 2)
            for contour in contours:
                contour = cv2.convexHull(contour)
                area = cv2.contourArea(contour)
                circumference = cv2.arcLength(contour,True)
                circularity = circumference ** 2 / (4*math.pi*area)
                print(circularity)
                print(area)
                if area > 200 or circularity > 1.5:
                    continue
                
                bounding_box = cv2.boundingRect(contour)

                extend = area / (bounding_box[2] * bounding_box[3])

                if extend > 0.8:
                    continue

                m = cv2.moments(contour)
                if m['m00'] != 0:
                    center = (int(m['m10'] / m['m00']), int(m['m01'] / m['m00']))
                    cv2.circle(drawing, center, 3, (0, 255, 0), -1)

                try:
                    ellipse = cv2.fitEllipse(contour)
                    cv2.ellipse(drawing, box=ellipse, color=(0, 255, 0))
                except:
                    pass

            cv2.putText(drawing, str(area),(10,20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (155,255,0))
            cv2.imshow("Drawing", drawing)
            cv2.waitKey(0)

Answer 1

Glares通常具有大约180的像素值。您可以检查180的像素值，然后会有一个像素簇，其值的范围从180到185或190。将群集的像素值更改为接近的像素值

OpenCV学生反射/眩光消除

1 个答案: