def perform_learning(self, options):
""" Perfrom the learning from the dataset. """
# Retreiving the dataset models
print 'Training using a {} classifier.'.format(
options['classifier_type'])
models = {}
for category in self.dataset.keys():
models[category] = []
for google_id in self.dataset[category]:
models[category].append(
SketchupModel.find_google_id(google_id))
# Training
classifier = self.classifiers_available[options['classifier_type']]
self.identifier = Identifier(classifier=classifier)
for category in models.keys():
self.identifier.add_models(models[category], category)
# (x, y, w) = self.identifier._get_example_matrix()
# import matplotlib.pyplot as plt
# import numpy as np
# # w = np.array(w)
# # print y
# # print w
# plt.plot(y, w, 'ro')
# print self.dataset.keys()
# plt.show()
self.identifier.train(options['entropy'])
def test_identification_banana_vs_bowl_vs_food_can(self):
""" Try to identify with 3 categories. """
# Getting the dataset
bowl_ids = ['fa61e604661d4aa66658ecd96794a1cd',
'f74bba9a22e044dea3769fcd5f96f4',
'd2e1dc9ee02834c71621c7edb823fc53']
banana_ids = ['f6e6117261dca163713c042b393cc65b',
'ba0d56295321002718ddbf38fa69c501',
'7d78e217e0ba160fe2b248b8bb97d290']
bowls = []
for bowl_id in bowl_ids:
bowls.append(SketchupModel.find_google_id(bowl_id))
bananas = []
for banana_id in banana_ids:
bananas.append(SketchupModel.find_google_id(banana_id))
# Training
iden = Identifier()
iden.add_models(bananas, 'banana')
iden.add_models(bowls, 'bowl')
iden.train()
# Identification
for i in range(20):
example = Example.get_random(['banana', 'bowl'])
pcd_file = example.pcd_file()
print "Identification of file {}".format(example)
cloud = PointCloud.load_pcd(pcd_file.name)
iden.identify(cloud)
def test_exception_when_no_existing_category(self):
""" Test that if the identifier is empty it throws. """
pointcloud = PointCloud.load_pcd("pointcloud/fixtures/cloud.pcd")
identifier = Identifier()
self.assertRaises(IndexError, identifier.identify, pointcloud)
# training will add a category :
model = SketchupModel()
model.google_id = "test1"
model.mesh = file("sketchup_models/fixtures/mesh_can.tri").read()
identifier.add_models([model], "test_category")
try:
identifier.identify(pointcloud)
except IndexError:
self.fail("identifier.identify() raised IndexError unexpectedly!")
except:
# can raise if Indentification failed
pass
def __init__(self, *args, **kwargs):
""" Overwrite to have a default classifier. """
if 'identifier' not in kwargs:
default = Identifier(classifier=KNeighborsClassifier())
kwargs['identifier'] = default
super(EvaluationSession, self).__init__(*args, **kwargs)
