class TestDatasetPascal:
def setup(self):
self.d = Dataset(test_config, 'test_pascal_train')
self.d.load_from_pascal('train')
def test_gt(self):
assert(self.d.num_classes() == 20)
assert('dog' in self.d.classes)
def test_gt_for_class(self):
correct = np.array(
[[48., 240., 148., 132., 11., 0., 1., 0.]])
ans = self.d.get_det_gt_for_class("dog")
print ans
assert np.all(ans.arr == correct)
def test_neg_samples(self):
# unlimited negative examples
indices = self.d.get_neg_samples_for_class(
"dog", with_diff=True, with_trun=True)
correct = np.array([1, 2])
assert(np.all(indices == correct))
# maximum 1 negative example
indices = self.d.get_neg_samples_for_class(
"dog", 1, with_diff=True, with_trun=True)
correct1 = np.array([1])
correct2 = np.array([2])
print(indices)
assert(np.all(indices == correct1) or np.all(indices == correct2))
def test_pos_samples(self):
indices = self.d.get_pos_samples_for_class("dog")
correct = np.array([0])
assert(np.all(indices == correct))
def test_ground_truth_test(self):
d = Dataset(test_config, 'test_pascal_val')
d.load_from_pascal('val')
gt = d.get_det_gt(with_diff=False, with_trun=False)
correct = np.matrix(
[[139., 200., 69., 102., 18., 0., 0., 0.],
[123., 155., 93., 41., 17., 0., 0., 1.],
[239., 156., 69., 50., 8., 0., 0., 1.]])
print(gt)
assert np.all(gt.arr == correct)
def test_get_pos_windows(self):
pass
