#!/usr/bin/env python
import ecto
from ecto_opencv.highgui import imshow
from ecto_opencv.calib import DepthTo3d
from image_pipeline import Rectifier, StereoModelLoader, DepthRegister, CameraModelToCv, CV_INTER_NN
from ecto_openni import OpenNICapture, DEPTH_RGB, DEPTH_IR, RGB, IR, IRGamma, enumerate_devices
from ecto_object_recognition.conversion import MatToPointCloudXYZRGB
from ecto_pcl import PointCloudT2PointCloud, CloudViewer, XYZRGB
openni_reg = True
print enumerate_devices()
capture = OpenNICapture('Camera',
stream_mode=DEPTH_RGB,
registration=openni_reg,
latched=False)
depthTo3d = DepthTo3d('Depth ~> 3d')
to_xyzrgb = MatToPointCloudXYZRGB('OpenCV ~> PCL')
pcl_cloud = PointCloudT2PointCloud('conversion', format=XYZRGB)
cloud_viewer = CloudViewer('Cloud Display')
plasm = ecto.Plasm()
plasm.connect(capture['K'] >> depthTo3d['K'],
capture['image'] >> imshow('Image Display')[:],
capture['depth'] >> depthTo3d['depth'],
depthTo3d['points3d'] >> to_xyzrgb['points'],
capture['image'] >> to_xyzrgb['image'],
to_xyzrgb[:] >> pcl_cloud[:], pcl_cloud[:] >> cloud_viewer[:])
if __name__ == '__main__':
from ecto.opts import doit
#!/usr/bin/env python
import ecto
from ecto_opencv import highgui
from ecto_opencv.highgui import V4LCapture, VideoCapture, imshow, FPSDrawer, NiConverter
from image_pipeline import Rectifier, RectifierNC, StereoModelLoader, DepthRegister
from ecto_openni import OpenNICapture, DEPTH_RGB, DEPTH_IR, RGB, IR, IRGamma
capture = OpenNICapture(stream_mode=IR, registration=False, latched=False)
stereo_model = StereoModelLoader(left_fname='left.yml', right_fname="right.yml", stereo_fname = 'stereo.yml');
rect_depth = Rectifier()
conversion = IRGamma() # scale the IR so that we can visualize it.
plasm = ecto.Plasm()
plasm.connect(
capture['ir'] >> conversion[:],
conversion[:] >> rect_depth['image'],
stereo_model['right_model'] >> rect_depth['camera'],
)
#display stuff
plasm.connect(
rect_depth['image'] >> imshow(name='Rectified IR')['image'],
conversion[:] >> imshow(name='Original IR')['image']
)
if __name__ == '__main__':
from ecto.opts import doit
doit(plasm, description='Capture Kinect IR images and rectify.')
#!/usr/bin/env python
import ecto, ecto_pcl, ecto_openni
from ecto_image_pipeline import conversion
from ecto.opts import run_plasm, scheduler_options
from ecto_openni import OpenNICapture, DEPTH_RGB
capture = OpenNICapture(stream_mode=DEPTH_RGB, registration=True, sync=False)
mat2pcl = conversion.MatToPointCloudXYZRGBOrganized('mat2pcl')
pcl2ecto = ecto_pcl.PointCloudT2PointCloud('pcl2ecto')
viewer = ecto_pcl.CloudViewer("viewer", window_name="Clouds!")
graph = [
capture['image'] >> mat2pcl['image'],
capture['depth'] >> mat2pcl['points'], mat2pcl[:] >> pcl2ecto[:],
pcl2ecto[:] >> viewer[:]
]
plasm = ecto.Plasm()
plasm.connect(graph)
if __name__ == "__main__":
from ecto.opts import doit
doit(plasm, description='Execute test kinect.')
#!/usr/bin/env python
import ecto
from ecto_opencv.highgui import imshow, ImageSaver
from ecto_opencv.calib import PatternDetector, PatternDrawer, CameraCalibrator, ASYMMETRIC_CIRCLES_GRID, CHESSBOARD, GatherPoints
from ecto_opencv.imgproc import cvtColor, RGB2GRAY
from ecto_openni import OpenNICapture, DEPTH_RGB, DEPTH_IR, RGB, IR, IRGamma
from image_pipeline import StereoCalibration, LatchBool
import os
from pattern_helpers import *
create_detector_drawer = create_detector_drawer_chessboard
capture = OpenNICapture(stream_mode=RGB, registration=False, latched=True)
next_mode = IR
conversion = IRGamma() # scale the IR so that we can visualize it.
rgb2gray = cvtColor(flag=RGB2GRAY)
plasm = ecto.Plasm()
plasm.insert(capture)
plasm.connect(
capture['image'] >> rgb2gray[:],
capture['ir'] >> conversion[:],
)
ir_detector, ir_drawer = create_detector_drawer()
rgb_detector, rgb_drawer = create_detector_drawer()
rgb_display = imshow(name="RGB Points", triggers=dict(save=ord('s')))
trigger_latch = LatchBool()
reset_source, reset_sink = ecto.EntangledPair(
value=trigger_latch.inputs.at('reset'),