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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 |
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