(카메라 보정) 이미지를 읽도록 내 루프를 만드는 방법은 10 초 동안 만 대기하고 다음 이미지로 이동하지 않을 경우 어떻게합니까?

Question

파이썬에 openCV을 사용하여 카메라를 보정하는 코드를 작성 중입니다. 교정을 위해 30 개의 이미지를 사용하고 있습니다. 아이디어는 루프가 이미지로 시작하고 무언가를 감지하지 못하면 언젠가 기다렸다가 다음 이미지로 이동한다는 것입니다.

내 목표는 (예 : 012 초) 동안 각 이미지에 대해 루프가 대기하도록하고 결과가없는 경우 다음 이미지로 전달합니다.

도움 주셔서 감사합니다.

다음은 코드입니다.

# -*- coding: utf-8 -*- 
import numpy as np 
import cv2 
import glob 
import math 
import pickle 
import matplotlib.pyplot as plt 
import time 

# Calcul de la distance 
def _pdist(p1, p2): 
    """ 
    Distance bwt two points. p1 = (x, y), p2 = (x, y) 
    """ 

    return math.sqrt(math.pow(p1[0] - p2[0], 2) + math.pow(p1[1] - p2[1], 2)) 


print "Initializing" 
# termination criteria 
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001) 

# Définir le nombre de bords qu'on a dans le damier (dans notre cas 13*13) 
n_rows = 13 
n_cols = 13 
n_cols_and_rows = (n_cols, n_rows) 
n_rows_and_cols = (n_rows, n_cols) 

# Prépar les points objet (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0) 
objp = np.zeros((n_rows * n_cols, 3), np.float32) 
objp[:, :2] = np.mgrid[0:n_rows, 0:n_cols].T.reshape(-1, 2) 

# Préparer deux tableaux pour sauvegarder les points objet et points images de totues les images trouvées. 
objpoints = [] # 3d point in real world space 
imgpoints = [] # 2d points in image plane. 

# Les photos du damier qu'on a pris pour le test 

mypath = "/home/stagiaire/Bureau/New_Calibrage/RGB/" 

# mypath="/home/stagiaire/Bureau/DATA_new//Photos_damiers_test/GRE/" 
# mypath="/home/stagiaire/Bureau/DATA_new/Photos_damiers_test/NIR/" 
# mypath="/home/stagiaire/Bureau/DATA_new/Photos_damiers_test/RED/" 
# mypath="/home/stagiaire/Bureau/DATA new/Photos_damiers_test/REG/" 
# mypath="/home/stagiaire/Bureau/DATA_new/Photos_damiers_test/RGB/" 


print "Getting images from " + mypath 
images = glob.glob(mypath + '*.JPG') 
print "images is: " + str(images) 

criteria_calibrator = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001) 
criteria = criteria_calibrator 

for idx, fname in enumerate(images): 
    print "\nImage " + fname 
    if time.sleep(10): 
     break 
    img = cv2.imread(fname) 
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
    # Trouver les bords 
    ret, corners = cv2.findChessboardCorners(gray, n_rows_and_cols, None) 
    # Si trouvés, on ajoute les points obj et les points images 
    if ret == True: 
     print " found " + str(len(corners)) + " corners." 
    objpoints.append(objp) 
    # cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria) didnt work, I couldnt make it work copying the calibrator code 
    imgpoints.append(corners) 

    # Dessiner et afficher les bords sur la photo originale 
    cv2.drawChessboardCorners(img, n_rows_and_cols, corners, ret) 
    cv2.imshow('img', img) 
    cv2.waitKey(500) 

# Afficher combien de points image et points objet on a trouvé 
print "objpoints len: " + str(len(objpoints)) 
print "imgpoints len: " + str(len(imgpoints)) 

# Trouver la matrice de la caméra et l'enregistrer dans le dossier du data (photos du test) 

try: 
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None) 
    datathings = (ret, mtx, dist, rvecs, tvecs) 
    outf = open(mypath + "calibration_return_values_rows_and_cols.pickle", "rb") 
    pickle.dump(datathings, outf) 
    fieldnames = ["ret", "mtx", "dist", "rvecs", "tvecs"] 
    for fieldname, data in zip(fieldnames, datathings): 
     print fieldname + ": " 
     print data 
    print "ret, mtx, dist, rvecs, tvecs:" 
    print (ret, mtx, dist, rvecs, tvecs) 
except: 
    print "Failed getting cv2.calibrateCamera" 
    pass 
# cv2.destroyAllWindows() 


# Calibration 
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None) 

img = cv2.imread('/home/stagiaire/Bureau/New_Calibrage/GRE/IMG_700101_000255_0000_RGB.JPG') 

h, w = img.shape[:2] 
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h)) 

# undistortion 
dst = cv2.undistort(img, mtx, dist, None, newcameramtx) 

# crop l'image 
x, y, w, h = roi 
dst = dst[y:y + h, x:x + w] 
cv2.imwrite('Desktop/imagecalibre.png', dst) 

# Affichage l'image originale au coté de l'image calibrée 
plt.subplot(221), plt.imshow(img), plt.title('image originale') 
plt.subplot(222), plt.imshow(dst), plt.title('image calibree') 
plt.show() 

# Calcul de l'erreur 
mean_error = 0 
for i in xrange(len(objpoints)): 
    imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist) 
    error = cv2.norm(imgpoints[i], imgpoints2, cv2.NORM_L2)/len(imgpoints2) 
    tot_error = error 

print "total error: ", mean_error/len(objpoints) 

가 그리고 이것이 내가 루프를 변경하고자하는 부분이다, 나는 time.sleep()처럼 뭔가를 시도했지만 작동하지 않습니다.

for idx, fname in enumerate(images): 
    print "\nImage " + fname 
    if time.sleep(10): 
     break 
    img = cv2.imread(fname) 
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
    # Trouver les bords 
    ret, corners = cv2.findChessboardCorners(gray, n_rows_and_cols, None) 
    # Si trouvés, on ajoute les points obj et les points images 
    if ret == True: 
     print " found " + str(len(corners)) + " corners." 
    objpoints.append(objp) 
    # cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria) didnt work, I couldnt make it work copying the calibrator code 
    imgpoints.append(corners) 

Answer 1

시도

if time.sleep(10): 
    break 

을 제거하고 여기에 cv2.waitKey

에 대한 링크가의

cv2.waitKey(500) 

에

이

cv2.waitKey(10000) # waits 10 seconds (10000 ms) for a pressed key 

을 변경하려면

--- 편집 ---

어쩌면 당신이이 같은 시도 할 수 있습니다 :

for idx, fname in enumerate(images): 
    print "\nImage " + fname 
    img = cv2.imread(fname) 
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
    # Trouver les bords 
    ret, corners = cv2.findChessboardCorners(gray, n_rows_and_cols, None) 
    # Si trouvés, on ajoute les points obj et les points images 
    if ret == True: 
     print " found " + str(len(corners)) + " corners." 

     objpoints.append(objp) 
     # cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria) didnt work, I couldnt make it work copying the calibrator code 
     imgpoints.append(corners) 

     # Dessiner et afficher les bords sur la photo originale 
     cv2.drawChessboardCorners(img, n_rows_and_cols, corners, ret) 
     cv2.imshow('img', img) 
     cv2.waitKey(0) 

    else: 
     print " no corners found"