def __init__(self, plasm):
ecto.BlackBox.__init__(self, plasm)
self.video_cap = highgui.VideoCapture(video_device=0)
self.fps = highgui.FPSDrawer()
self.rgb2gray = imgproc.cvtColor('rgb -> gray', flag=7)
self.circle_detector = calib.PatternDetector('Dot Detector',
rows=7, cols=3, pattern_type="acircles",
square_size=0.03)
self.circle_drawer = calib.PatternDrawer('Circle Draw',
rows=7, cols=3)
self.circle_display = highgui.imshow('Pattern show',
name='Pattern', waitKey=2, maximize=True)
self.pose_calc = calib.FiducialPoseFinder('Pose Calc')
self.pose_draw = calib.PoseDrawer('Pose Draw')
self.camera_info = calib.CameraIntrinsics('Camera Info', camera_file="camera.yml")
def do_ecto(device_id=0, frame_id='base'):
video_capture = highgui.VideoCapture('Video Camera',
video_device=device_id)
mat2image = ecto_ros.Mat2Image(frame_id=frame_id, encoding='bgr8')
pub_rgb = ImagePub("image pub", topic_name='image')
graph = [
video_capture["image"] >> mat2image["image"],
mat2image["image"] >> pub_rgb["input"]
]
plasm = ecto.Plasm()
plasm.connect(graph)
sched = ecto.schedulers.Threadpool(plasm)
sched.execute()
def make_graph(k, sigma, debug):
video = highgui.VideoCapture(video_device=0)
g = imgproc.GaussianBlur(sigma=sigma)
graph = []
graph += [video['image'] >> g['input']]
for x in range(k):
nextg = imgproc.GaussianBlur(sigma=sigma)
graph += [g['out'] >> nextg['input']]
g = nextg
fps = highgui.FPSDrawer()
graph += [
g['out'] >> fps[:],
fps[:] >> highgui.imshow("megagauss", name="megagauss", waitKey=10)[:]
]
return graph
#!/usr/bin/env python
# add pose estimation
import ecto
from ecto_opencv import highgui, calib, imgproc
plasm = ecto.Plasm()
sched = ecto.schedulers.Singlethreaded(plasm)
video_cap = highgui.VideoCapture(video_device=0)
fps = highgui.FPSDrawer()
rgb2gray = imgproc.cvtColor('rgb -> gray', flag=7)
circle_detector = calib.PatternDetector(rows=7,
cols=3,
pattern_type="acircles",
square_size=0.03)
circle_drawer = calib.PatternDrawer(rows=7, cols=3)
circle_display = highgui.imshow('Pattern show',
name='Pattern',
waitKey=2,
maximize=True)
pose_calc = calib.FiducialPoseFinder('Pose Calc')
pose_draw = calib.PoseDrawer('Pose Draw')
camera_info = calib.CameraIntrinsics('Camera Info', camera_file="camera.yml")
plasm.connect(
#!/usr/bin/env python
# abstract the input.
import ecto
from ecto_opencv import highgui, calib, imgproc, cv_bp as cv
from object_recognition.observations import *
from ecto_object_recognition import capture
plasm = ecto.Plasm()
video_cap = highgui.VideoCapture(video_device=0, width=640, height=480)
camera_intrinsics = calib.CameraIntrinsics(camera_file='camera.yml')
poser = OpposingDotPoseEstimator(rows=5, cols=3,
pattern_type=calib.ASYMMETRIC_CIRCLES_GRID,
square_size=0.04, debug=True
)
bgr2rgb = imgproc.cvtColor('rgb -> bgr', flag=imgproc.RGB2BGR)
rgb2gray = imgproc.cvtColor('rgb -> gray', flag=imgproc.RGB2GRAY)
display = highgui.imshow('Poses', name='Poses')
plasm.connect(
video_cap['image'] >> rgb2gray[:],
rgb2gray[:] >> poser['image'],
video_cap['image'] >> poser['color_image'],
poser['debug_image'] >> display['image'],
camera_intrinsics['K'] >> poser['K']
)
if __name__ == '__main__':
from ecto.opts import doit
