-
-
Save Asadullah-Dal17/e265bafdf1e9eaac5885b1dda8f33077 to your computer and use it in GitHub Desktop.
Aruco marker-based OpenCV distance measurement
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from picamera.array import PiRGBArray | |
from picamera import PiCamera | |
import time | |
import sys | |
import numpy as np | |
sys.path.remove('/opt/ros/kinetic/lib/python2.7/dist-packages') | |
import cv2 | |
import cv2.aruco as aruco | |
import numpy as np | |
import rectangleArea as ra | |
import math | |
# reding calibration matrices | |
calibrationResultPath = "res//" | |
fsContent = cv2.FileStorage(calibrationResultPath + "calibrationValues0.yaml", cv2.FILE_STORAGE_READ) | |
mtxNode = fsContent.getNode('camera_matrix') | |
distNode = fsContent.getNode('dist_coeff') | |
mtx = np.asarray(mtxNode.mat()) | |
distor = np.asarray(distNode.mat()) | |
print("--------------------") | |
print(mtx) | |
print("--------------------") | |
print(distor) | |
print("--------------------") | |
#mtx = np.array([[2.6822003708394282e+03, 0., 1.5588865381021240e+03], [0., 2.6741978758743703e+03, 1.2303469240154550e+03], [0., 0., 1.]]) | |
#distor = np.array([2.0426196677407879e-01, -3.3902097431574091e-01, -4.1813964792274307e-03, -1.0425257413809015e-02, 8.2004709580884308e-02]) | |
# getting ready the aruco dictionary | |
aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250) | |
# opening rpi camera | |
camera = PiCamera() | |
#camera.resolution = (1040, 784) | |
camera.resolution = (1024, 770) | |
camera.framerate = 30 | |
rawCapture = PiRGBArray(camera, size=(1024, 770)) | |
time.sleep(0.1) | |
tvec0 = np.array([[[0.0, 0.0, 0.0]]]) | |
rvecmax = 0.0 | |
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True): | |
image = frame.array | |
cv2.rectangle(image, (0, 0), (200, 200), (220, 240, 230), -1) | |
corners, ids, rejectedImgPoints = aruco.detectMarkers(image, aruco_dict) | |
image = aruco.drawDetectedMarkers(image, corners) # marker körvonalak | |
rvec, tvec ,_ = aruco.estimatePoseSingleMarkers(corners, 0.05, mtx, distor) | |
#rvec = np.array([[[0.0, 0.0, 0.0]]]) | |
if ids is not None: | |
for i in range(0, ids.size): | |
#print(image.dtype) | |
rr, thet = ra.rArea(corners) | |
aruco.drawAxis(image, mtx, distor, rvec[0], tvec[0], 0.06) # np.array([0.0, 0.0, 0.0]) | |
#print(f, "\t", end = " ") | |
#print("%d táv: %.2f" % (i, math.sqrt(rvec[i][0][0]**2 + rvec[i][0][1]**2 + rvec[i][0][2]**2))) | |
#cv2.putText(image, image.shape()) | |
#cv2.putText(image, "%.1f cm" % ((20000 / rr**0.5) * 0.116 - 2.08), (0, 230), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (244, 244, 244)) | |
cv2.putText(image, "%.1f cm -- %.0f deg" % ((tvec[0][0][2] * 100), (rvec[0][0][2] / math.pi * 180)), (0, 230), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (244, 244, 244)) | |
cv2.circle(image, (100, int(rr / 600)), 6, (200, 40, 230), -1) | |
R, _ = cv2.Rodrigues(rvec[0]) | |
cameraPose = -R.T * tvec[0] | |
#print(type(cameraPose)) | |
#print((int)(tvec[0][0][2] * 1000)) | |
#rvec = red, blue, green | |
""" | |
if ((rvec[0][0][1])) > rvecmax: | |
rvecmax = (rvec[0][0][1]); | |
print((int)(rvec[0][0][0] / math.pi * 180), " ", (int)(rvec[0][0][1] / math.pi * 180), " ", (int)(rvec[0][0][2] / math.pi * 180)) | |
#print(rvec.shape) | |
""" | |
cv2.imshow("Frame", image) | |
key = cv2.waitKey(1) & 0xFF | |
rawCapture.truncate(0) | |
if key == ord("q"): | |
break |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment