def declare_cells(_p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {}
cells['throttle'] = ecto.TrueEveryN("Throttle", n=1)
cells['mat2image'] = ecto_ros.Mat2Image("Mat2Image")
cells['subscribed_mat2image'] = ecto.If(
"Subscribed Mat2Image",
input_tendril_name="has_subscribers",
cell=cells['mat2image'])
cells['throttled_mat2image'] = ecto.If(
"Throttled Mat2Image",
input_tendril_name="throttle",
cell=cells['subscribed_mat2image'])
cells['publisher'] = ecto_sensor_msgs.Publisher_Image(
"Publisher",
topic_name="/images/candidate_beans",
queue_size=2,
latched=True)
cells['throttled_publisher'] = ecto.If("Throttled Publisher",
input_tendril_name="throttle",
cell=cells['publisher'])
subscribers_input, subscribers_output = \
ecto.EntangledPair(value=cells['throttled_mat2image'].inputs.at('has_subscribers'), source_name="Has Subscribers Input", sink_name="Has Subscribers Output")
cells['subscribers_input'] = subscribers_input
cells['subscribers_output'] = subscribers_output
return cells
def connect_ros_image(self):
frame_id_str = 'camera_optical_frame'
self.image2ros = ecto_ros.Mat2Image(
frame_id=frame_id_str, encoding='bgr8')
self.depth2ros = ecto_ros.Mat2Image(
frame_id=frame_id_str, encoding='16UC1')
self.image_publisher = Publisher_Image(topic_name='/image')
self.depth_publisher = Publisher_Image(topic_name='/depth')
self.graph += [
self.observation_renderer['image'] >> self.image2ros['image'],
self.observation_renderer['depth'] >> self.depth2ros['image'],
self.observation_renderer['depth'] >> self.depth2point_cloud_ros['image'],
self.image2ros['image'] >> self.image_publisher['input'],
self.depth2ros['image'] >> self.depth_publisher['input'],
]
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 configure(self, p, _i, _o):
feature_params = self._parameters.get("feature", False)
if not feature_params:
raise RuntimeError("You must supply feature_descriptor parameters for TOD.")
# merge it with the subtype
feature_descriptor_params = { 'feature': feature_params, 'descriptor': self._parameters.get('descriptor', {}) }
from object_recognition.tod import merge_dict
feature_descriptor_params = merge_dict(feature_descriptor_params, self._submethod)
self.feature_descriptor = FeatureDescriptor(json_params=json_helper.dict_to_cpp_json_str(feature_descriptor_params))
self.descriptor_matcher = tod_detection.DescriptorMatcher("Matcher",
search_json_params=json_helper.dict_to_cpp_json_str(self._parameters['search']),
model_documents=self._model_documents)
self.message_cvt = ecto_ros.Mat2Image()
guess_params = self._parameters['guess'].copy()
guess_params['visualize'] = self._visualize
self.guess_generator = tod_detection.GuessGenerator("Guess Gen", **guess_params)
def do_ecto():
# ecto options
parser = argparse.ArgumentParser(
description='Publish images from directory.')
scheduler_options(parser)
args = parser.parse_args()
#this will read all images in the path
path = '/home/sam/Code/vision/VOCdevkit/VOC2012/JPEGImages'
images = ImageReader(path=os.path.expanduser(path))
mat2image = ecto_ros.Mat2Image(encoding='rgb8')
pub_rgb = ImagePub("image_pub", topic_name='/camera/rgb/image_raw')
display = imshow(name='image', waitKey=5000)
plasm = ecto.Plasm()
plasm.connect(
images['image'] >> mat2image['image'],
images['image'] >> display['image'],
mat2image['image'] >> pub_rgb['input'],
)
ecto.view_plasm(plasm)
run_plasm(args, plasm, locals=vars())
print LinemodDetectionPipeline.type_name()
object_ids = ['whoolite', 'tilex']
model_documents = Models(object_db, object_ids,
LinemodDetectionPipeline.type_name(),
json_helper.dict_to_cpp_json_str({}))
print len(model_documents)
detector = Detector(model_documents=model_documents,
db=object_db,
threshold=90)
#connect up the pose_est
plasm.connect(source['image'] >> detector['image'],
source['depth'] >> detector['depth'])
plasm.connect(source['image'] >> imshow(name='source')[:])
if 0:
import ecto_ros
import ecto_ros.ecto_sensor_msgs
import sys
ecto_ros.init(sys.argv, "image_pub")
mat2image = ecto_ros.Mat2Image(frame_id='base', encoding='bgr8')
pub_rgb = ecto_ros.ecto_sensor_msgs.Publisher_Image(
"image pub", topic_name='linemod_image')
plasm.connect(detector['image'] >> mat2image[:],
mat2image[:] >> pub_rgb[:])
else:
plasm.connect(detector['image'] >> imshow(name='result')[:])
run_plasm(options, plasm, locals=vars())