def __init__(self, root_uri, params):
super(MainFlow, self).__init__()
self.params = params
input_images = core.PertResource(self,
'%s/photoid_to_image.pert' %
(root_uri),
check_exists=True,
is_generated=False)
CheckInputPreconditions(input_images.GetUri())
photoids_flow = util.PertDropValueFlow(input_images,
'%s/photoid.pert' % root_uri)
self.photoids = photoids_flow.GetOutput()
# extract features
feature_uri_base = '%s/%s/' % (
root_uri,
iwutil.HashProto(self.params.tuned_feature_extractor_params))
feature_flow = util.ExtractFeaturesFlow(
feature_uri_base, input_images,
self.params.tuned_feature_extractor_params.params)
features = feature_flow.GetOutput()
cbir_params = params.cbir
cbir_uri_base = '%s/cbir/%s/' % (feature_uri_base,
iwutil.HashProto(cbir_params))
cbir_flow = util.CbirMetaFlow(feature_uri_base, features, cbir_params)
cbir_results = cbir_flow.cbir_results
itergraph_uri_base = "%s/itergraph/%s/" % (
cbir_uri_base, iwutil.HashProto(self.params))
build_graph_flow = BuildIterativeGraphFlow(itergraph_uri_base,
features, cbir_results,
self.params)
self.merged_matches = build_graph_flow.merged_matches
return
def __init__(self, base_uri, images, max_batch_size, num_shards_features):
super(CreateAllPairsMatchBatchesFlow, self).__init__()
self.AddInput('images', images)
self.AddOutput(
'unsorted_match_batches',
core.PertResource(self,
'%s/unsorted_match_batches.pert' % (base_uri)))
self.max_batch_size = max_batch_size
self.num_shards_features = num_shards_features
return
def __init__(self, root_uri, matches_root_uri):
super(MainFlow, self).__init__()
tide = core.PertResource(self,
'%s/objectid_to_object.pert' % (root_uri),
check_exists=True,
is_generated=False)
matches = core.PertResource(self,
'%s/merged_matches.pert' %
(matches_root_uri),
check_exists=True,
is_generated=False)
matches_to_ig_flow = util.MatchesToImageGraphFlow(
matches_root_uri, matches, tide)
image_graph = matches_to_ig_flow.GetOutput()
eval1_flow = util.LabelpropEval1Flow(matches_root_uri, image_graph,
tide)
matches_to_irg_flow = util.MatchesToImageRegionGraphFlow(
matches_root_uri, matches, tide)
image_region_graph = matches_to_irg_flow.GetOutput()
eval2_flow = util.LabelpropEval2Flow(matches_root_uri,
image_region_graph, tide)
return
def __init__(self, phase_base_uri, itergraph_params, phase_index,
candidates, prev_state, features):
super(ItergraphMatchBatchPlanningFlow, self).__init__()
self.features = features
self.AddInput('candidates', candidates)
self.AddInput('prev_state', prev_state)
self.AddOutput(
'sorted_match_batches',
core.PertResource(
self, '%s/sorted_match_batches.pert' % (phase_base_uri)))
phase = itergraph_params.phase[phase_index]
self.max_candidates_per_phase = phase.max_match_candidates
self.max_vertex_degree = phase.max_vertex_degree
self.max_batch_size = phase.max_match_batch_size
self.max_replication_factor = phase.max_image_replication_factor
self.match_groups = {}
self.num_replications = {}
return
def __init__(self, root_uri):
super(MainFlow, self).__init__()
feature_type = 'usift'
max_batch_size = 50
matcher_config = image_matcher_config.GetImageMatcherConfig(
feature_type)
num_shards_features = 100
images = core.PertResource(self,
'%s/photoid_to_image.pert' % (root_uri))
CHECK(images.Exists(), 'flow expects input to exist: %s' % images)
#tide = core.PertResource(self, '%s/objectid_to_object.pert' % (root_uri))
#CHECK(tide.Exists(), 'flow expects input to exist: %s' % tide)
# crop out borders
crop_flow = util.CropAndScaleImagesFlow(root_uri, images, 1.0)
# extract features
feature_uri_base = "%s/%s/" % (root_uri, feature_type)
feature_flow = util.ExtractFeaturesFlow(feature_uri_base,
crop_flow.GetOutput(),
feature_type,
num_shards_features)
create_allpairs_metadata_flow = CreateAllPairsMatchBatchesFlow(
feature_uri_base, images, max_batch_size, num_shards_features)
sorted_metadata_flow = util.SortFlow(
create_allpairs_metadata_flow.GetOutput(),
'%s/match_batches.pert' % feature_uri_base, num_shards_features)
# build graph
matching_flow = util.MatchBatchesFlow(feature_uri_base,
feature_flow.GetOutput(),
sorted_metadata_flow.GetOutput(),
matcher_config)
return