replaced cv2.aruco with python bindings for new aruco version
This commit is contained in:
parent
0bc6b68a20
commit
280fb10427
|
|
@ -1,13 +1,16 @@
|
|||
import pyrealsense2 as rs
|
||||
import numpy as np
|
||||
import cv2
|
||||
from cv2 import aruco
|
||||
import os
|
||||
|
||||
from shapely.geometry import LineString
|
||||
from queue import Queue
|
||||
|
||||
class ArucoEstimator:
|
||||
import aruco
|
||||
|
||||
class ArucoEstimator(socketserver.BaseRequestHandler):
|
||||
corner_marker_ids = {
|
||||
'a': 0,
|
||||
'a': 15,
|
||||
'b': 1,
|
||||
'c': 2,
|
||||
'd': 3
|
||||
|
|
@ -59,6 +62,25 @@ class ArucoEstimator:
|
|||
self.cv_camera = cv2.VideoCapture(0)
|
||||
self.pipeline = None
|
||||
|
||||
# create detector and get parameters
|
||||
self.detector = aruco.MarkerDetector()
|
||||
#self.detector.setDictionary('ARUCO_MIP_36h12')
|
||||
#self.detector.setDictionary('ARUCO_MIP_16h3')
|
||||
#self.detector.setDictionary('ARUCO')
|
||||
#self.detector.setDetectionMode(aruco.DM_NORMAL, 0.05)
|
||||
#self.detector.setDetectionMode(aruco.DM_VIDEO_FAST, 0.05)
|
||||
|
||||
self.detector_params = self.detector.getParameters()
|
||||
|
||||
# print detector parameters
|
||||
print("detector params:")
|
||||
for val in dir(self.detector_params):
|
||||
if not val.startswith("__"):
|
||||
print("\t{} : {}".format(val, self.detector_params.__getattribute__(val)))
|
||||
|
||||
self.camparam = aruco.CameraParameters()
|
||||
self.camparam.readFromXMLFile(os.path.join(os.path.dirname(__file__), "dfk72_6mm_param2.yml"))
|
||||
|
||||
def mouse_callback(self, event, px, py, flags, param):
|
||||
if event == 1:
|
||||
if self.all_corners_detected():
|
||||
|
|
@ -107,38 +129,39 @@ class ArucoEstimator:
|
|||
|
||||
gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
|
||||
|
||||
#aruco_dict = aruco.Dictionary_get(aruco.DICT_APRILTAG_16H5)
|
||||
#aruco_dict = aruco.Dictionary_get(aruco.DICT_7X7_50)
|
||||
#aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_50)
|
||||
aruco_dict = aruco.Dictionary_get(aruco.DICT_5X5_1000)
|
||||
#aruco_dict = aruco.Dictionary_get(aruco.DICT_ARUCO_ORIGINAL) # fast
|
||||
parameters = aruco.DetectorParameters_create()
|
||||
corners, ids, rejectedImgPoints = aruco.detectMarkers(gray, aruco_dict, parameters=parameters)
|
||||
frame = aruco.drawDetectedMarkers(color_image.copy(), corners, ids)
|
||||
# run aruco marker detection
|
||||
detected_markers = self.detector.detect(gray)
|
||||
|
||||
if ids is not None:
|
||||
for id, corner in zip(ids, corners):
|
||||
if id in self.corner_marker_ids.values():
|
||||
marker_size = 0.1
|
||||
# extract data for detected markers
|
||||
detected_marker_data = {}
|
||||
for marker in detected_markers:
|
||||
detected_marker_data[marker.id] = {'center': marker.getCenter()}
|
||||
if marker.id > 0:
|
||||
if marker.id in self.corner_marker_ids.values():
|
||||
marker.calculateExtrinsics(0.1, self.camparam)
|
||||
else:
|
||||
marker_size = 0.07
|
||||
corner_pixel_coord = np.mean(corner[0], axis=0)
|
||||
# res = aruco.estimatePoseSingleMarkers(corner, marker_size, self.camera_matrix, self.dist_coeffs)
|
||||
# rvecs = res[0][0][0]
|
||||
# tvecs = res[1][0][0]
|
||||
#
|
||||
# self.update_estimate(id[0], corner_pixel_coord, rvecs, tvecs)
|
||||
marker.calculateExtrinsics(0.07, self.camparam)
|
||||
detected_marker_data[marker.id]['Rvec'] = marker.Rvec
|
||||
detected_marker_data[marker.id]['Tvec'] = marker.Tvec
|
||||
|
||||
frame = self.draw_grid_lines(frame, corners, ids)
|
||||
frame = self.draw_robot_pos(frame, corners, ids)
|
||||
if marker.id > 0: # draw markers onto the image
|
||||
marker.draw(color_image, np.array([255, 255, 255]), 2, True)
|
||||
aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
|
||||
|
||||
# store data
|
||||
for id, data in detected_marker_data.items():
|
||||
self.update_estimate(id, data['center'], data['Rvec'], data['Tvec'])
|
||||
|
||||
# draw grid
|
||||
color_image = self.draw_grid_lines(color_image, detected_marker_data)
|
||||
color_image = self.draw_robot_pos(color_image, detected_marker_data)
|
||||
|
||||
# Show images
|
||||
cv2.imshow('RoboRally', frame)
|
||||
cv2.imshow('RoboRally', color_image)
|
||||
key = cv2.waitKey(1)
|
||||
|
||||
if key > 0:
|
||||
self.event_queue.put(('key', key))
|
||||
print('key = ', key)
|
||||
if key == ord('q'):
|
||||
running = False
|
||||
finally:
|
||||
|
|
@ -147,6 +170,7 @@ class ArucoEstimator:
|
|||
# Stop streaming
|
||||
self.pipeline.stop()
|
||||
|
||||
|
||||
def update_estimate(self, id, pixel_coord, rvec, tvec):
|
||||
# update the marker estimate with new data
|
||||
if id in self.corner_marker_ids.values():
|
||||
|
|
@ -156,8 +180,9 @@ class ArucoEstimator:
|
|||
old_estimate = self.corner_estimates[corner]['real_world_estimate']
|
||||
n_estimates = self.corner_estimates[corner]['n_estimates']
|
||||
|
||||
tvec_proj = tvec[0:2] # projection to get rid of z coordinate
|
||||
tvec_proj = np.array((tvec_proj[0], -tvec_proj[1])) # flip y coordinate
|
||||
x = tvec[0][0]
|
||||
y = -tvec[1][0] # flip y coordinate
|
||||
tvec_proj = np.array([x, y])
|
||||
if old_estimate is not None:
|
||||
new_estimate = (n_estimates * old_estimate + tvec_proj) / (n_estimates + 1) # weighted update
|
||||
else:
|
||||
|
|
@ -169,8 +194,8 @@ class ArucoEstimator:
|
|||
elif id in self.robot_marker_ids:
|
||||
# for robot markers we extract x and y position as well as the angle
|
||||
# here we could also implement a filter
|
||||
x = tvec[0]
|
||||
y = -tvec[1] # flip y coordinate
|
||||
x = tvec[0][0]
|
||||
y = -tvec[1][0] # flip y coordinate
|
||||
|
||||
# compute angle
|
||||
rot_mat, _ = cv2.Rodrigues(rvec)
|
||||
|
|
@ -266,16 +291,12 @@ class ArucoEstimator:
|
|||
thickness=2)
|
||||
return frame
|
||||
|
||||
def draw_grid_lines(self, frame, corners, ids):
|
||||
def draw_grid_lines(self, frame, detected_marker_data):
|
||||
# draws a grid onto the given frame
|
||||
board_corners_pixel_coords = {}
|
||||
for corner, id in self.corner_marker_ids.items():
|
||||
try:
|
||||
ind, _ = np.where(ids == id) # find index
|
||||
ind = ind[0]
|
||||
board_corners_pixel_coords[corner] = tuple(np.mean(corners[ind][0], axis=0))
|
||||
except IndexError:
|
||||
pass
|
||||
if id in detected_marker_data.keys():
|
||||
board_corners_pixel_coords[corner] = tuple(detected_marker_data[id]['center'])
|
||||
|
||||
frame = self.draw_corner_line(frame, 'a', 'b', board_corners_pixel_coords)
|
||||
frame = self.draw_corner_line(frame, 'b', 'c', board_corners_pixel_coords)
|
||||
|
|
@ -318,16 +339,12 @@ class ArucoEstimator:
|
|||
print(f"error: invalid robot id {id}")
|
||||
return None
|
||||
|
||||
def draw_robot_pos(self, frame, corners, ids):
|
||||
def draw_robot_pos(self, frame, detected_marker_data):
|
||||
# draws information about the robot positions onto the given frame
|
||||
robot_corners_pixel_coords = {}
|
||||
for id, estimate in self.robot_marker_estimates.items():
|
||||
try:
|
||||
ind, _ = np.where(ids == id) # find index
|
||||
ind = ind[0]
|
||||
robot_corners_pixel_coords[id] = tuple(np.mean(corners[ind][0], axis=0))
|
||||
except IndexError:
|
||||
pass
|
||||
if id in detected_marker_data.keys():
|
||||
robot_corners_pixel_coords[id] = tuple(detected_marker_data[id]['center'])
|
||||
|
||||
for id, coord in robot_corners_pixel_coords.items():
|
||||
x = self.robot_marker_estimates[id][0]
|
||||
|
|
@ -339,5 +356,4 @@ class ArucoEstimator:
|
|||
|
||||
if __name__ == "__main__":
|
||||
estimator = ArucoEstimator(use_realsense=False)
|
||||
|
||||
estimator.run_tracking()
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user