def test_errors_contain_correct_image_numbers(self):
detections = [
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 0], [0, 1]], [[1, 0], [0, 1]]]
}],
[],
[],
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 0], [0, 1]], [[1, 0], [0, 1]]]
}, {
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 2], [2, 1]], [[1, 0], [0, 1]]]
}],
]
sequence_json = self.make_sequence(detections)
seq_gen = submission_loader.read_sequence(sequence_json)
# the first 3 images are fine
for _ in range(3):
next(seq_gen)
img_dets = next(seq_gen)
next(img_dets) # First detection is fine
with self.assertRaises(ValueError) as cm:
next(img_dets) # Second detection, fourth image has a problem
msg = str(cm.exception)
self.assertIn(os.path.basename(sequence_json), msg)
self.assertIn('3', msg)
self.assertIn('1', msg)
def test_errors_if_no_valid_classes(self):
detections = [
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 0], [0, 1]], [[1, 0], [0, 1]]]
}],
[],
[],
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 0], [0, 1]], [[1, 0], [0, 1]]]
}, {
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[1, 2], [2, 1]], [[1, 0], [0, 1]]]
}],
]
patch_classes(detections)
os.makedirs(self.temp_dir, exist_ok=True)
json_file = os.path.join(self.temp_dir, 'test.json')
with open(json_file, 'w') as fp:
json.dump({
'classes': [str(idx) for idx in range(len(class_list.CLASSES))],
'detections': detections
}, fp)
with self.assertRaises(ValueError) as cm:
next(submission_loader.read_sequence(json_file))
msg = str(cm.exception)
self.assertIn('test.json', msg)
def test_inner_generator_returns_detection_instances(self):
detections = [
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}],
[],
[],
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}, {
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}],
]
sequence_json = self.make_sequence(detections)
gen = submission_loader.read_sequence(sequence_json)
seq_dets = list(gen)
self.assertEqual(len(detections), len(seq_dets))
for img_idx in range(len(seq_dets)):
img_dets = list(seq_dets[img_idx])
self.assertEqual(len(detections[img_idx]), len(img_dets))
for det_idx in range(len(img_dets)):
self.assertIsInstance(img_dets[det_idx], data_holders.DetectionInstance)
expected_probs = detections[img_idx][det_idx]['label_probs']
expected_list = np.zeros(len(class_list.CLASSES), dtype=np.float32)
expected_list[0:len(expected_probs)] = expected_probs
self.assertNPEqual(expected_list, img_dets[det_idx].class_list)
def test_returns_generator_of_generators(self):
detections = [
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}],
[],
[],
[{
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}, {
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}],
]
sequence_json = self.make_sequence(detections)
gen = submission_loader.read_sequence(sequence_json)
self.assertIsInstance(gen, types.GeneratorType)
seq_dets = list(gen)
self.assertEqual(len(detections), len(seq_dets))
for img_idx in range(len(seq_dets)):
self.assertIsInstance(seq_dets[img_idx], types.GeneratorType)
img_dets = list(seq_dets[img_idx])
self.assertEqual(len(detections[img_idx]), len(img_dets))
def test_errors_if_detections_missing(self):
os.makedirs(self.temp_dir, exist_ok=True)
json_file = os.path.join(self.temp_dir, 'test.json')
with open(json_file, 'w') as fp:
json.dump({
'classes': class_list.CLASSES,
# 'detections': detections
}, fp)
with self.assertRaises(KeyError) as cm:
next(submission_loader.read_sequence(json_file))
msg = str(cm.exception)
self.assertIn('test.json', msg)
def test_slice_both(self):
det = {
'label_probs': [0.1, 0.2, 0.3, 0.4],
'bbox': [12, 14, 55, 46],
'covars': [[[0, 0], [0, 0]], [[0, 0], [0, 0]]]
}
detections = [
[det for _ in range(1)],
[det for _ in range(3)],
[det for _ in range(5)],
[det for _ in range(7)],
]
sequence_json = self.make_sequence(detections)
gen = submission_loader.read_sequence(sequence_json, start_index=1, end_index=3)
self.assertIsInstance(gen, types.GeneratorType)
seq_dets = list(gen)
self.assertEqual(2, len(seq_dets))
for img_idx in range(2):
self.assertIsInstance(seq_dets[img_idx], types.GeneratorType)
img_dets = list(seq_dets[img_idx])
self.assertEqual(len(detections[img_idx + 1]), len(img_dets))
def test_returns_empty_generator_for_no_images(self):
sequence_json = self.make_sequence([])
gen = submission_loader.read_sequence(sequence_json)
self.assertIsInstance(gen, types.GeneratorType)
dets = list(gen)
self.assertEqual(dets, [])