def test_regression__vectorizer_layer_minus_one_behaves_same(self):
# GIVEN a layer to test
layer_under_test = -1
# AND a vectorizer that uses that layer
vec = Vectorizer(layer=layer_under_test, prm_path=default_prm_path, backend='cpu')
# AND an expected output
expected_output = [0.0016, 0.9883, 0.0099, 0.00]
#
# WHEN extracting the attributes from an image
print 'This test has not stalled, it takes 20-40 seconds on an fast-ish computer (%s)' % strftime("%H:%M:%S", gmtime())
actual_output = roundArray(vec.get_attribute_vector(image_loc))
#
# THEN the output is as expected
self.assertEqual(expected_output, actual_output, 'The output %s, does not match the expected output of %s' % (str(actual_output), str(expected_output)))
def test_regression__vectorizer_layer_minus_four_behaves_same(self):
# GIVEN a layer to test
layer_under_test = -4
# AND a vectorizer that uses that layer
vec = Vectorizer(layer=layer_under_test, prm_path=default_prm_path, backend='cpu')
# AND an expected output stored in a file
expected_output_file_path = os.path.expanduser('~')+'/SaturnServer/test_resources/layer4results.txt'
#
# WHEN extracting the attributes from an image
print 'This test has not stalled, it takes 20-40 seconds on an fast-ish computer (%s)' % strftime("%H:%M:%S", gmtime())
actual_output = roundArray(vec.get_attribute_vector(image_loc))
#
# THEN each element of the actual output array must match each element of the expected results
with open(expected_output_file_path, 'r') as expected_output_file:
element_no = 0
for expected_element in expected_output_file:
self.assertEqual(float(expected_element), actual_output[element_no],
'The output (element %d) %s, does not match the expected output of %s'
% (element_no, str(actual_output[element_no]), str(expected_element)))
element_no += 1
class VectorizerTest(unittest.TestCase):
def setUp(self):
self.vec = Vectorizer(layer=-1, backend='gpu', cores=32)
# Generate a list of images
base_image = os.path.expanduser(
'~') + '/SaturnServer/test_resources/map_image'
self.imagenames = []
for i in range(1, self.vec.cores + 1):
self.imagenames.append("{}{}.jpg".format(base_image, i))
def test_32_image_processing(self):
print 'About to vectorize'
res_dict, failed_imgs = self.vec.get_batch_attribute_vectors(
self.imagenames)
print 'done vectorizing, results'
print '-[Passed Images]-----'
for url, vec in res_dict.items():
print "{}- {}".format(url.split("/")[-1], vec)
print '-[Failed Images]-----'
for url, issue in failed_imgs.items():
print "{}- {}".format(url, issue)
print '------'
self.assertEqual(
len(res_dict), len(self.imagenames),
"There number of outputs ({}) should match the number of inputs: {}"
.format(len(res_dict), len(self.imagenames)))
self.assertEqual(len(failed_imgs), 0,
"There should be no failed images")
print 'done vectorizing, results'
print '------'
i = 1
for vec in res_dict.values():
print "map_image{}- {}".format(i, vec)
i += 1
print '------'
def test_NSEW(self):
test_img_locs = [
os.path.expanduser("~") +
"/SaturnServer/test_resources/NSEW_test_img_1.jpg",
os.path.expanduser("~") +
"/SaturnServer/test_resources/NSEW_test_img_2.jpg"
]
for img in test_img_locs:
print os.path.isfile(img)
regular_output = self.vec.get_attribute_vector(test_img_locs[0])
print "regular output: {}".format(regular_output)
NSEW_output, failed_images = self.vec.get_NSEW_batch_attribute_vectors(
test_img_locs)
print "Checking corners of NSEW output are different from regular output, but centre tiles are the same"
corners = ["NE", "NW", "SE", "SW"]
for url in NSEW_output:
img = url.split("#")[0]
coord = url.split("#")[1]
if img == test_img_locs[0]:
if coord not in corners:
self.assertItemsEqual(NSEW_output[url], regular_output)
else:
identicle = True
for i in range(0, len(regular_output)):
self.assertNotEqual(NSEW_output[url][i],
regular_output[i])
elif img == test_img_locs[1]:
if coord == "NW":
self.assertItemsEqual(NSEW_output[url], regular_output)
for i in range(0, len(regular_output)):
self.assertNotEqual(
NSEW_output[url][i],
NSEW_output[test_img_locs[0] + "#NW"][i])
