def __setstate__(self, state):
(
self.__detector_params,
self.__marker_min_perimeter,
self.__marker_detector_modes,
) = state
params = self.__detector_params.to_dict()
self._detector = pupil_apriltags.Detector(**params)
def __init__(self):
"""Конструктор класса"""
self.tag_detector = apriltag.Detector(
families="tagStandard41h12",
nthreads=1,
quad_decimate=1.0,
quad_sigma=0.0,
refine_edges=1,
decode_sharpening=0.25,
debug=0,
)
self.detect_dict = {1: 0, 2: 0, 3: 0}
def __init__(self,
cameras_dir,
intrinsics,
extrinsics,
cameras=[
"020122061233", "821312060044", "020122061651",
"821312062243"
],
tag_size=0.0585):
self.intrinsics = intrinsics
self.extrinsics = extrinsics
self.cameras_dir = cameras_dir
self.cameras = cameras
self.detector = pupil_apriltags.Detector(families="tag36h11")
self.tag_size = tag_size
def is_april(gray):
results = []
# execute the detector to find the tags (more options exist)
detector = pupil_apriltags.Detector(families="tag36h11")
results = detector.detect(gray,
estimate_tag_pose=False,
camera_params=None,
tag_size=0.17)
#print(results)
print("{} AprilTag(s) detected".format(len(results)))
if results != []:
go_time = 1
else:
go_time = 0
return go_time
def get_xy(gray, image):
# execute the detector to find the tags (more options exist)
detector = pupil_apriltags.Detector(families="tag36h11")
results = detector.detect(gray,
estimate_tag_pose=False,
camera_params=None,
tag_size=0.17)
#print("{} AprilTag(s) detected".format(len(results)))
gold = (0, 215, 255)
cv2.circle(image, (577, 204), 10, gold, 3) #577, 324 (204 for dots)
# loop over the AprilTag detection resultsimage
for r in results:
# extract the bounding box (x, y)-coordinates for the AprilTag
# and convert each of the (x, y)-coordinate pairs to integers
(ptA, ptB, ptC, ptD) = r.corners
ptB = (int(ptB[0]), int(ptB[1]))
ptC = (int(ptC[0]), int(ptC[1]))
ptD = (int(ptD[0]), int(ptD[1]))
ptA = (int(ptA[0]), int(ptA[1]))
# draw the bounding box of the AprilTag detection
cv2.line(image, ptA, ptB, (0, 0, 255), 2)
cv2.line(image, ptB, ptC, (0, 0, 255), 2)
cv2.line(image, ptC, ptD, (0, 0, 255), 2)
cv2.line(image, ptD, ptA, (0, 0, 255), 2)
# draw the center (x, y)-coordinates of the AprilTag
(cX, cY) = (int(r.center[0]), int(r.center[1]))
print(cX, cY)
cv2.circle(image, (cX, cY), 5, (0, 255, 0), -1)
# difference in positon
(diffx, diffy) = (cX - 577, cY - 204) #577, 184
(realposx, realposy) = (cX, cY)
cv2.putText(image, 'Difference in x position: %02.1f' % (diffx),
(30, 580), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 2)
cv2.putText(image, 'Difference in y position: %02.1f' % (diffy),
(30, 610), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 2)
def tag(img_tag):
'''
img type: narry unit 8
'''
img_tag = cv2.cvtColor(img_tag, cv2.COLOR_BGR2GRAY)
tag_detector = apriltag.Detector()
tags = tag_detector.detect(
img_tag) # The image must be a grayscale image of type numpy.uint8
# for tag in img.find_apriltags(fx=f_x, fy=f_y, cx=c_x, cy=c_y): # default family "TAG36H11"
for tag in tags:
cv2.circle(img, tuple(tag.corners[0].astype(int)), 4, (0, 0, 255),
2) # left-top
cv2.circle(img, tuple(tag.corners[1].astype(int)), 4, (0, 0, 255),
2) # right-top
cv2.circle(img, tuple(tag.corners[2].astype(int)), 4, (0, 0, 255),
2) # right-bottom
cv2.circle(img, tuple(tag.corners[3].astype(int)), 4, (0, 0, 255),
2) # left-bottom
def detectTags(board, img, cameraMatrix=None, discoff=None, verbose=0):
"""
检测img中的apriltag，返回一组tag,如果不输入cameraMatrix，tags中不含位姿信息
:param board: apiriltag.board 包含board的一些参数
:param img: 需要检测的图片路径
:param cameraMatrix:相机内参
:return: tags 检测到的tags
"""
# img = cv2.imread(img)
if discoff is not None:
img = cv2.undistort(img, cameraMatrix, discoff)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.convertScaleAbs(gray, alpha=1.5, beta=0)
at_detector = apriltag.Detector(families=board.april_family) # for windows
if cameraMatrix is None:
tags = at_detector.detect(gray)
if verbose == 1:
img = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)
img = apriltag_cali_utils.drawTagAxis(img, tags)
cv2.namedWindow("apriltag", cv2.WINDOW_NORMAL)
cv2.imshow("apriltag", img)
cv2.waitKey(0)
else:
if ~(discoff is None):
gray = cv2.undistort(gray, cameraMatrix, discoff)
camera_param = [cameraMatrix[0, 0], cameraMatrix[1, 1], cameraMatrix[0, 2], cameraMatrix[1, 2]]
tags = at_detector.detect(gray, True, camera_param, board.tag_size)
if verbose == 1:
img = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB)
img = apriltag_cali_utils.drawTagAxis(img, tags, cameraMatrix)
cv2.namedWindow("apriltag", cv2.WINDOW_NORMAL)
cv2.imshow("apriltag", cv2.resize(img,(512,512)))
cv2.waitKey(0)
# for tag in tags:
# print(tag.tag_id)
return tags
import logging
from types import SimpleNamespace
import cv2
import numpy as np
import pupil_apriltags
import file_methods as fm
import video_capture
from methods import normalize
from stdlib_utils import unique
logger = logging.getLogger(__name__)
apriltag_detector = pupil_apriltags.Detector()
def get_markers_data(detection, img_size, timestamp):
return {
"id": detection.tag_id,
# verts: Corners need to be listed counter-clockwise
"verts": detection.corners.tolist(),
"centroid": normalize(detection.center, img_size, flip_y=True),
"timestamp": timestamp,
}
def calc_perimeter(corners):
corners = np.asarray(corners, dtype=np.float32)
return cv2.arcLength(corners, closed=True)
def __setstate__(self, state):
self.__detector_params = state
params = self.__detector_params.to_dict()
self._detector = pupil_apriltags.Detector(**params)
import logging
from types import SimpleNamespace
import cv2
import numpy as np
import pupil_apriltags
import file_methods as fm
import video_capture
from methods import normalize
from stdlib_utils import unique
logger = logging.getLogger(__name__)
apriltag_detector = pupil_apriltags.Detector(nthreads=2)
def get_markers_data(detection, img_size, timestamp):
return {
"id": detection.tag_id,
# verts: Corners need to be listed counter-clockwise
"verts": detection.corners.tolist(),
"centroid": normalize(detection.center, img_size, flip_y=True),
"timestamp": timestamp,
}
def calc_perimeter(corners):
corners = np.asarray(corners, dtype=np.float32)
return cv2.arcLength(corners, closed=True)
#!/usr/bin/env python
# coding: UTF-8
# import apriltag
import pupil_apriltags as apriltag # for windows
import cv2
import numpy as np
import sys
img = cv2.imread("D:/vscodescrip/opencv_learning/tag25h9.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 创建一个apriltag检测器
# at_detector = apriltag.Detector(apriltag.DetectorOptions(families='tag36h11 tag25h9') )
at_detector = apriltag.Detector(families='tag36h11') #for windows
# 进行apriltag检测，得到检测到的apriltag的列表
tags = at_detector.detect(gray)
print("%d apriltags have been detected." % len(tags))
for tag in tags:
cv2.circle(img, tuple(tag.corners[0].astype(int)), 4, (255, 0, 0),
2) # left-top
cv2.circle(img, tuple(tag.corners[1].astype(int)), 4, (255, 0, 0),
2) # right-top
cv2.circle(img, tuple(tag.corners[2].astype(int)), 4, (255, 0, 0),
2) # right-bottom
cv2.circle(img, tuple(tag.corners[3].astype(int)), 4, (255, 0, 0),
2) # left-bottom
cv2.imshow("apriltag_test", img)
cv2.waitKey()
def rescale(frame, percent=60):
scale_percent = 60
width = int(frame.shape[1]*scale_percent/100)
height = int(frame.shape[0]*scale_percent/100)
dim = (width, height)
return cv2.resize(frame,dim, interpolation = cv2.INTER_AREA)
cam = cv2.VideoCapture(0)
#set camera resolution
cam.set(cv2.CAP_PROP_FRAME_WIDTH, 640*2)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 480*2)
print("Current camera resolution: (" + str(cam.get(3)) + "; " + str(cam.get(4)) + ")")
# create AprilTags detector with options
detector = pupil_apriltags.Detector(families="tag36h11")
frame_number=0
# keep looping
results = []
while results == []:
if not cam.isOpened():
cam.open(0)
print('initializing...')
(grabbed, frame) = cam.read()
image = rescale(frame, percent=50)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
def detector():
return pupil_apriltags.Detector()
import pupil_apriltags as apriltag
import cv2
import numpy as np
import time
from pupil_apriltags import Detector
cap = cv2.VideoCapture(1, cv2.CAP_DSHOW)
cv2.namedWindow('camera', cv2.WINDOW_AUTOSIZE)
detector1 = apriltag.Detector(families='tag36h11')
initial_color_done = [0, 0, 0, 0, 0,
0] #white blue green orange red white #確認各顏色為中心之面是否完成掃描
initial_color = [
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0] #white blue green orange red white
,
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]
] #各顏色為中心之面的初始顏色
now_color = [0, 0, 0, 0, 0, 0, 0, 0, 0] #讀取進來之九宮格
top_color = [0, 0, 0, 0, 0, 0, 0, 0, 0]
color_detect_x = [0, 0, 0, 0, 0, 0, 0, 0, 0] #tag之x座標
color_detect_y = [0, 0, 0, 0, 0, 0, 0, 0, 0] #tag之y座標
color_detect_id = [0, 0, 0, 0, 0, 0, 0, 0, 0] #tag之id
def swap_four_element(w, x, y, z):
Copyright 2020 by Magician
'''
import pupil_apriltags as apriltag
import cv2
import numpy as np
import sys
img = cv2.imread("test.jpg")
gray = cv2.cvtColor(
img, cv2.COLOR_BGR2GRAY
) # The image must be a grayscale image of type numpy.uint8
# Build a detector for apriltag
tag_detector = apriltag.Detector()
# Perform apriltag detection to get a list of detected apriltag
tags = tag_detector.detect(gray)
print("%d apriltags have been detected." % len(tags))
for tag in tags:
cv2.circle(img, tuple(tag.corners[0].astype(int)), 4, (0, 0, 255),
2) # left-top
cv2.circle(img, tuple(tag.corners[1].astype(int)), 4, (0, 0, 255),
2) # right-top
cv2.circle(img, tuple(tag.corners[2].astype(int)), 4, (0, 0, 255),
2) # right-bottom
cv2.circle(img, tuple(tag.corners[3].astype(int)), 4, (0, 0, 255),
2) # left-bottom
return class_ids, rules, data
pipeline = (
rs.pipeline()
) # <- Объект pipeline содержит методы для взаимодействия с потоком
config = rs.config() # <- Дополнительный объект для хранения настроек потока
colorizer = rs.colorizer()
config.enable_stream(rs.stream.color, 1280, 720, rs.format.bgr8, 30)
config.enable_stream(rs.stream.depth, 848, 480, rs.format.z16, 30)
profile = pipeline.start(config)
detector = apriltag.Detector(
families="tag36h11",
nthreads=1,
quad_decimate=1.0,
quad_sigma=0.0,
refine_edges=1,
decode_sharpening=0.25,
debug=0,
)
font = cv2.FONT_HERSHEY_COMPLEX
print("START")
intr = profile.get_stream(
rs.stream.color).as_video_stream_profile().get_intrinsics()
depth_intrin = (profile.get_stream(
rs.stream.depth).as_video_stream_profile().get_intrinsics())
fx = float(intr.fx) # Focal length of x
fy = float(intr.fy) # Focal length of y
ppx = float(intr.ppx) # Principle Point Offsey of x (aka. cx)
ppy = float(intr.ppy) # Principle Point Offsey of y (aka. cy)
camera_params = [fx, fy, ppx, ppy]
