虹膜识别系统 python实现

先上传效果图

main.py

// An highlighted block

"""
Demonstration of the GazeTracking library.
Check the README.md for complete documentation.
"""
import pandas as pd
import cv2
import dlib
import saccademodel
import fixationmodel
from imutils import resize
import os
from GazeTracking_master.gaze_tracking.gaze_tracking import GazeTracking
import matplotlib.pyplot as plt
from GazeTracking_master.gaze_tracking.FaceAligner import FaceAligner
# import calibration_
import collections
def gaze_():
# calibration_matrix = calibration_.main()
# def gaze_(path, path_csv):
    gaze = GazeTracking()
    webcam = cv2.VideoCapture(0)
    frame_cnt = 0
    Frame = [];
    Gaze = [];
    Left_gaze = [];Right_gaze = []
    calibration_points = [];
    X_gaze = []
    while True:
        # We get a new frame from the webcam
        _, frame = webcam.read()
        if not _:
            print('no frame')
            break
        # We send this frame to GazeTracking to analyze it
        # frame = cv2.rotate(frame, cv2.ROTATE_90_CLOCKWISE)#转化角度90度
        # frame = cv2.resize(src=frame, dsize=(720, 1280))#压缩尺寸
        cv2.imshow('frame',frame)
        _face_detector = dlib.get_frontal_face_detector()
        _predictor = dlib.shape_predictor("C:/Users/zhangjing/Anaconda3/envs/Django_1/GazeTracking_master/gaze_tracking/trained_models/shape_predictor_68_face_landmarks.dat")
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = _face_detector(frame)
        Fa = FaceAligner(_face_detector, _predictor, (0.35, 0.35), desiredFaceWidth=720, desiredFaceHeight=1280)
        aligned_face = Fa.align(frame, gray, faces[0])
        frame = aligned_face

        gaze.refresh(frame)
        frame,left,right = gaze.annotated_frame()
        Left_gaze.append(left);Right_gaze.append(right)

        text = ""

        if gaze.is_blinking():
            text = "Blinking"
        elif gaze.is_right():
            text = "Looking right"
        elif gaze.is_left():
            text = "Looking left"
        elif gaze.is_center():
            text = "Looking center"

        cv2.putText(frame, text, (20, 60), cv2.FONT_HERSHEY_DUPLEX, 1.4, (147, 58, 31), 2)

        left_pupil = gaze.pupil_left_coords()
        right_pupil = gaze.pupil_right_coords()
        cv2.putText(frame, "Left pupil:  " + str(left_pupil), (20, 130), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)
        cv2.putText(frame, "Right pupil: " + str(right_pupil), (20, 165), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)

        if left_pupil == None:
            continue
        left_pupil = list(left_pupil)
        right_pupil = list(right_pupil)
        Gaze.append(left_pupil)
        # point = [left_pupil[0],left_pupil[1], left_pupil[0]*left_pupil[1], 1]
        # calibration_point = np.dot(calibration_matrix[0][0], point)
        # print(calibration_point)
        # calibration_point_1 = np.transpose(calibration_point)
        # print(calibration_point_1)
        # calibration_point_2 = np.asarray(calibration_point_1)
        # print(calibration_point_2)
        # calibration_point = list(calibration_point)
        # calibration_points.append([np.float(calibration_point[0]),abs(np.float(calibration_point[1]))])
        Frame.append(frame_cnt)

        # cv2.moveWindow("trans:" + frame, 1000, 100)
        cv2.imshow('Dome',frame)
        # cv2.imwrite("E:/ffmpeg-latest-win64-static/eye_frame_2/face/"+str(frame_cnt)</