def test_compute_descriptor_dummy_model(self):
# Caffe dummy network interaction test Lenna image)
# Construct network with an empty model just to see that our
# interaction with the Caffe API is successful. We expect a
# zero-valued descriptor vector.
g = CaffeDescriptorGenerator(self.dummy_net_topo_fp,
self.dummy_caffe_model_fp,
self.dummy_img_mean_fp,
return_layer='fc', use_gpu=False)
d = g.compute_descriptor(from_uri(self.lenna_image_fp))
self.assertAlmostEqual(d.vector().sum(), 0., 12)
def test_compute_descriptor_dummy_model(self):
# Caffe dummy network interaction test Lenna image)
# Construct network with an empty model just to see that our
# interaction with the Caffe API is successful. We expect a
# zero-valued descriptor vector.
g = CaffeDescriptorGenerator(self.dummy_net_topo_fp,
self.dummy_caffe_model_fp,
self.dummy_img_mean_fp,
return_layer='fc', use_gpu=False)
d = g.compute_descriptor(from_uri(self.lenna_image_fp))
nose.tools.assert_almost_equal(d.vector().sum(), 0., 12)
def test_compute_descriptor_from_url_hopper_description(self):
# Caffe AlexNet interaction test (Grace Hopper image)
# This is a long test since it has to download data for remote URIs
d = CaffeDescriptorGenerator(
self.alexnet_prototxt_elem,
self.alexnet_caffemodel_elem,
self.image_mean_proto_elem,
return_layer='fc7',
use_gpu=False,
)
hopper_elem = DataFileElement(self.hopper_image_fp, readonly=True)
expected_descr = numpy.load(self.hopper_alexnet_fc7_descr_fp)
descr = d.compute_descriptor(hopper_elem).vector()
numpy.testing.assert_allclose(descr, expected_descr, atol=1e-4)
def test_compute_descriptor_dummy_model(self):
# Caffe dummy network interaction test Lenna image)
# Construct network with an empty model just to see that our
# interaction with the Caffe API is successful. We expect a
# zero-valued descriptor vector.
g = CaffeDescriptorGenerator(self.dummy_net_topo_elem,
self.dummy_caffe_model_elem,
self.dummy_img_mean_elem,
return_layer='fc',
use_gpu=False)
d = g.compute_descriptor(
DataFileElement(self.hopper_image_fp, readonly=True))
self.assertAlmostEqual(d.vector().sum(), 0., 12)
def test_compute_descriptor_from_url_lenna_description(self):
# Caffe AlexNet interaction test (Lenna image)
# This is a long test since it has to download data for remote URIs
d = CaffeDescriptorGenerator(
self.www_uri_alexnet_prototxt,
self.www_uri_alexnet_caffemodel,
self.www_uri_image_mean_proto,
return_layer='fc7',
use_gpu=False,
)
lenna_elem = from_uri(self.lenna_image_fp)
expected_descr = numpy.load(self.lenna_alexnet_fc7_descr_fp)
descr = d.compute_descriptor(lenna_elem).vector()
numpy.testing.assert_allclose(descr, expected_descr, atol=1e-5)
def test_compute_descriptor_from_url_lenna_description(self):
# Caffe AlexNet interaction test (Lenna image)
# This is a long test since it has to download data for remote URIs
d = CaffeDescriptorGenerator(
self.www_uri_alexnet_prototxt,
self.www_uri_alexnet_caffemodel,
self.www_uri_image_mean_proto,
return_layer='fc7',
use_gpu=False,
)
lenna_elem = from_uri(self.lenna_image_fp)
expected_descr = numpy.load(self.lenna_alexnet_fc7_descr_fp)
descr = d.compute_descriptor(lenna_elem).vector()
numpy.testing.assert_allclose(descr, expected_descr, atol=1e-5)
"""
Test computing a descriptor on something.
"""
from smqtk.algorithms.descriptor_generator.caffe_descriptor import CaffeDescriptorGenerator
from smqtk.representation.data_element.file_element import DataFileElement
e = DataFileElement("/usr/local/lib/python2.7/dist-packages/smqtk/tests/data/"
"Lenna.png")
gen = CaffeDescriptorGenerator(
"/home/smqtk/caffe/msra_resnet/ResNet-50-deploy.prototxt",
"/home/smqtk/caffe/msra_resnet/ResNet-50-model.caffemodel",
"/home/smqtk/caffe/msra_resnet/ResNet_mean.binaryproto",
return_layer="pool5",
use_gpu=False,
load_truncated_images=True)
# Uses default DescriptorMemoryElement factory.
d = gen.compute_descriptor(e)
assert d.vector() is not None
"""
Test computing a descriptor on something.
"""
from smqtk.algorithms.descriptor_generator.caffe_descriptor import CaffeDescriptorGenerator
from smqtk.representation.data_element.file_element import DataFileElement
e = DataFileElement("/usr/local/lib/python2.7/dist-packages/smqtk/tests/data/"
"Lenna.png")
gen = CaffeDescriptorGenerator(
"/home/smqtk/caffe/msra_resnet/ResNet-50-deploy.prototxt",
"/home/smqtk/caffe/msra_resnet/ResNet-50-model.caffemodel",
"/home/smqtk/caffe/msra_resnet/ResNet_mean.binaryproto",
return_layer="pool5",
use_gpu=False, load_truncated_images=True
)
# Uses default DescriptorMemoryElement factory.
d = gen.compute_descriptor(e)
assert d.vector() is not None