def declare_cells(p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {'args': ecto.Constant(value=p.args),
'dataset': ODMLoadDatasetCell(force_focal=p.args.force_focal,
force_ccd=p.args.force_ccd),
'resize': ODMResizeCell(resize_to=p.args.resize_to),
'opensfm': ODMOpenSfMCell(use_exif_size=False,
feature_process_size=p.args.resize_to,
feature_min_frames=p.args.min_num_features,
processes=context.num_cores,
matching_gps_neighbors=p.args.matcher_neighbors,
matching_gps_distance=p.args.matcher_distance),
'cmvs': ODMCmvsCell(max_images=p.args.cmvs_maxImages),
'pmvs': ODMPmvsCell(level=p.args.pmvs_level,
csize=p.args.pmvs_csize,
thresh=p.args.pmvs_threshold,
wsize=p.args.pmvs_wsize,
min_imgs=p.args.pmvs_minImageNum,
cores=p.args.pmvs_num_cores),
'meshing': ODMeshingCell(max_vertex=p.args.odm_meshing_maxVertexCount,
oct_tree=p.args.odm_meshing_octreeDepth,
samples=p.args.odm_meshing_samplesPerNode,
solver=p.args.odm_meshing_solverDivide),
'texturing': ODMMvsTexCell(data_term=p.args.mvs_texturing_dataTerm,
outlier_rem_type=p.args.mvs_texturing_outlierRemovalType,
skip_vis_test=p.args.mvs_texturing_skipGeometricVisibilityTest,
skip_glob_seam_leveling=p.args.mvs_texturing_skipGlobalSeamLeveling,
skip_loc_seam_leveling=p.args.mvs_texturing_skipLocalSeamLeveling,
skip_hole_fill=p.args.mvs_texturing_skipHoleFilling,
keep_unseen_faces=p.args.mvs_texturing_keepUnseenFaces),
# Old odm_texturing
# 'texturing': ODMTexturingCell(resize=p.args['resize_to'],
# resolution=p.args['odm_texturing_textureResolution'],
'georeferencing': ODMGeoreferencingCell(img_size=p.args.resize_to,
gcp_file=p.args.odm_georeferencing_gcpFile,
use_gcp=p.args.odm_georeferencing_useGcp),
'orthophoto': ODMOrthoPhotoCell(resolution=p.args.odm_orthophoto_resolution)
}
return cells
def test_constant():
print "test running.."
plasm = ecto.Plasm()
c = ecto.Constant(value=0.50505)
m = ecto_test.Multiply(factor=3.3335)
passthrough = ecto_test.PassthroughAny()
print passthrough.__doc__
print ">>>>DOC>>>>", c.__doc__
pr = ecto_test.Printer()
p = ecto.Plasm()
plasm.connect(c[:] >> m[:], m[:] >> passthrough[:],
passthrough[:] >> pr[:])
plasm.execute()
assert m.outputs.out == (0.50505 * 3.3335)
plasm.execute()
assert m.outputs.out == (0.50505 * 3.3335)
def declare_cells(p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {'args': ecto.Constant(value=p.args),
'dataset': ODMLoadDatasetCell(force_focal=p.args.force_focal,
force_ccd=p.args.force_ccd),
'resize': ODMResizeCell(resize_to=p.args.resize_to),
'opensfm': ODMOpenSfMCell(use_exif_size=False,
feature_process_size=p.args.resize_to,
feature_min_frames=p.args.min_num_features,
processes=context.num_cores,
matching_gps_neighbors=p.args.matcher_neighbors,
matching_gps_distance=p.args.matcher_distance),
'cmvs': ODMCmvsCell(max_images=p.args.cmvs_maxImages),
'pmvs': ODMPmvsCell(level=p.args.pmvs_level,
csize=p.args.pmvs_csize,
thresh=p.args.pmvs_threshold,
wsize=p.args.pmvs_wsize,
min_imgs=p.args.pmvs_minImageNum,
cores=p.args.pmvs_num_cores),
'meshing': ODMeshingCell(max_vertex=p.args.odm_meshing_maxVertexCount,
oct_tree=p.args.odm_meshing_octreeDepth,
samples=p.args.odm_meshing_samplesPerNode,
solver=p.args.odm_meshing_solverDivide),
'texturing': ODMTexturingCell(resize=p.args.resize_to,
resolution=p.args.odm_texturing_textureResolution,
size=p.args.odm_texturing_textureWithSize),
'georeferencing': ODMGeoreferencingCell(img_size=p.args.resize_to,
gcp_file=p.args.odm_georeferencing_gcpFile,
use_gcp=p.args.odm_georeferencing_useGcp),
'orthophoto': ODMOrthoPhotoCell(resolution=p.args.odm_orthophoto_resolution)
}
return cells
def declare_cells(p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {
'args':
ecto.Constant(value=p.args),
'dataset':
ODMLoadDatasetCell(verbose=p.args.verbose, proj=p.args.proj),
'opensfm':
ODMOpenSfMCell(
use_exif_size=False,
feature_process_size=p.args.resize_to,
feature_min_frames=p.args.min_num_features,
processes=p.args.max_concurrency,
matching_gps_neighbors=p.args.matcher_neighbors,
matching_gps_distance=p.args.matcher_distance,
hybrid_bundle_adjustment=p.args.use_hybrid_bundle_adjustment),
'slam':
ODMSlamCell(),
'smvs':
ODMSmvsCell(alpha=p.args.smvs_alpha,
max_pixels=p.args.depthmap_resolution *
p.args.depthmap_resolution,
threads=p.args.max_concurrency,
output_scale=p.args.smvs_output_scale,
shading=p.args.smvs_enable_shading,
gamma_srgb=p.args.smvs_gamma_srgb,
verbose=p.args.verbose),
'meshing':
ODMeshingCell(max_vertex=p.args.mesh_size,
oct_tree=p.args.mesh_octree_depth,
samples=p.args.mesh_samples,
point_weight=p.args.mesh_point_weight,
max_concurrency=p.args.max_concurrency,
verbose=p.args.verbose),
'texturing':
ODMMvsTexCell(
data_term=p.args.texturing_data_term,
outlier_rem_type=p.args.texturing_outlier_removal_type,
skip_vis_test=p.args.texturing_skip_visibility_test,
skip_glob_seam_leveling=p.args.
texturing_skip_global_seam_leveling,
skip_loc_seam_leveling=p.args.
texturing_skip_local_seam_leveling,
skip_hole_fill=p.args.texturing_skip_hole_filling,
keep_unseen_faces=p.args.texturing_keep_unseen_faces,
tone_mapping=p.args.texturing_tone_mapping),
'georeferencing':
ODMGeoreferencingCell(gcp_file=p.args.gcp,
use_exif=p.args.use_exif,
verbose=p.args.verbose),
'dem':
ODMDEMCell(max_concurrency=p.args.max_concurrency,
verbose=p.args.verbose),
'orthophoto':
ODMOrthoPhotoCell(resolution=p.args.orthophoto_resolution,
no_tiled=p.args.orthophoto_no_tiled,
compress=p.args.orthophoto_compression,
bigtiff=p.args.orthophoto_bigtiff,
build_overviews=p.args.build_overviews,
max_concurrency=p.args.max_concurrency,
verbose=p.args.verbose)
}
return cells
def declare_cells(p):
"""
Implement the virtual function from the base class
Only cells from which something is forwarded have to be declared
"""
cells = {
'args':
ecto.Constant(value=p.args),
'dataset':
ODMLoadDatasetCell(force_focal=p.args.force_focal,
force_ccd=p.args.force_ccd),
'opensfm':
ODMOpenSfMCell(use_exif_size=False,
feature_process_size=p.args.resize_to,
feature_min_frames=p.args.min_num_features,
processes=p.args.opensfm_processes,
matching_gps_neighbors=p.args.matcher_neighbors,
matching_gps_distance=p.args.matcher_distance,
fixed_camera_params=p.args.use_fixed_camera_params),
'slam':
ODMSlamCell(),
'cmvs':
ODMCmvsCell(max_images=p.args.cmvs_maxImages),
'pmvs':
ODMPmvsCell(level=p.args.pmvs_level,
csize=p.args.pmvs_csize,
thresh=p.args.pmvs_threshold,
wsize=p.args.pmvs_wsize,
min_imgs=p.args.pmvs_min_images,
cores=p.args.pmvs_num_cores),
'meshing':
ODMeshingCell(max_vertex=p.args.mesh_size,
oct_tree=p.args.mesh_octree_depth,
samples=p.args.mesh_samples,
solver=p.args.mesh_solver_divide,
remove_outliers=p.args.mesh_remove_outliers,
wlop_iterations=p.args.mesh_wlop_iterations,
verbose=p.args.verbose),
'texturing':
ODMMvsTexCell(
data_term=p.args.texturing_data_term,
outlier_rem_type=p.args.texturing_outlier_removal_type,
skip_vis_test=p.args.texturing_skip_visibility_test,
skip_glob_seam_leveling=p.args.
texturing_skip_global_seam_leveling,
skip_loc_seam_leveling=p.args.
texturing_skip_local_seam_leveling,
skip_hole_fill=p.args.texturing_skip_hole_filling,
keep_unseen_faces=p.args.texturing_keep_unseen_faces,
tone_mapping=p.args.texturing_tone_mapping),
'georeferencing':
ODMGeoreferencingCell(gcp_file=p.args.gcp,
use_exif=p.args.use_exif,
verbose=p.args.verbose),
'dem':
ODMDEMCell(verbose=p.args.verbose),
'orthophoto':
ODMOrthoPhotoCell(resolution=p.args.orthophoto_resolution,
t_srs=p.args.orthophoto_target_srs,
no_tiled=p.args.orthophoto_no_tiled,
compress=p.args.orthophoto_compression,
bigtiff=p.args.orthophoto_bigtiff,
build_overviews=p.args.build_overviews,
verbose=p.args.verbose)
}
return cells
if __name__ == '__main__':
import ecto.ecto_test as ecto_test
import yaml
import argparse
parser = argparse.ArgumentParser(description='My awesome program thing.')
parser.add_argument('-i,--input',
metavar='IMAGE_FILE',
dest='imagefile',
type=str,
default='',
help='an image file to load.')
scheduler_options(parser, default_niter=2)
multiply_factory = cell_options(parser, ecto_test.Multiply, prefix='mult')
const_factory = cell_options(parser,
ecto.Constant(value=0.50505),
prefix='const')
#parser.print_help()
options = parser.parse_args()
c = const_factory(options)
m = multiply_factory(options)
cyaml = CellYamlFactory(c, 'const')
print cyaml.dump()
c = cyaml.load(yaml.load(cyaml.dump()))
pr = ecto_test.Printer()
plasm = ecto.Plasm()
plasm.connect(c[:] >> m[:], m[:] >> pr[:])
run_plasm(options, plasm, locals=vars())
options = parser.parse_args(args=args)
run_plasm(options, plasm, locals)
if __name__ == '__main__':
import ecto_test
import yaml
import argparse
parser = argparse.ArgumentParser(description='My awesome program thing.')
parser.add_argument('-i,--input', metavar='IMAGE_FILE', dest='imagefile',
type=str, default='', help='an image file to load.')
group = parser.add_argument_group('ecto scheduler options')
scheduler_options(group, default_niter=2)
multiply_factory = cell_options(parser, ecto_test.Multiply, prefix='mult')
const_factory = cell_options(parser, ecto.Constant(value=0.50505), prefix='const')
#parser.print_help()
options = parser.parse_args()
c = const_factory(options)
m = multiply_factory(options)
cyaml = CellYamlFactory(c, 'const')
print cyaml.dump()
c = cyaml.load(yaml.load(cyaml.dump()))
pr = ecto_test.Printer()
plasm = ecto.Plasm()
plasm.connect(c[:] >> m[:],
m[:] >> pr[:]
)
self.object_id_index += 1
return 0
parser = argparse.ArgumentParser(
description='Generate training data by 3d rendering.')
test_cell = TestCell()
trainer = ecto_yolo.Trainer()
training_image_saver = ecto_yolo.TrainingImageSaver()
observation_renderer = ecto_yolo.ObservationRenderer()
json_db_str = '{"type": "CouchDB", "root": "http://localhost:5984", "collection": "object_recognition"}'
json_db = ecto.Constant(value=json_db_str)
object_id_str = '4680aac58c1d263b9449d57bd2000f27'
object_id = ecto.Constant(value=object_id_str)
frame_id_str = 'camera_optical_frame'
frame_id = ecto.Constant(value=frame_id_str)
ImageBagger = ecto_sensor_msgs.Bagger_Image
CameraInfoBagger = ecto_sensor_msgs.Bagger_CameraInfo
image_ci = ecto_ros.CameraInfo2Cv('camera_info -> cv::Mat')
image = ecto_ros.Image2Mat()
depth = ecto_ros.Image2Mat()
bag = "/home/sam/rosbags/sigverse/no_objects.bag"
