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FPN - Add min/max size params for pre-processing. #830

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Mar 12, 2019
Merged

FPN - Add min/max size params for pre-processing. #830

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b1cca53
Add size params for preprocessing.
23pointsNorth Mar 10, 2019
451c216
Update FasterRCNN with default sizes.
23pointsNorth Mar 11, 2019
ea816f8
Add size param and fix comments.
23pointsNorth Mar 12, 2019
b27316c
Add tests for min/max size in prepare.
23pointsNorth Mar 12, 2019
99a0a35
Update size tests
23pointsNorth Mar 12, 2019
f1ad965
Fix size param to be a whole integer of _stride.
23pointsNorth Mar 12, 2019
2f2d262
Fix flake8 errors.
23pointsNorth Mar 12, 2019
98e5058
Add note about size.
23pointsNorth Mar 12, 2019
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41 changes: 29 additions & 12 deletions tests/links_tests/model_tests/fpn_tests/test_faster_rcnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,24 +31,35 @@ def __call__(self, x):

class DummyFasterRCNN(FasterRCNN):

def __init__(self, n_fg_class):
def __init__(self, n_fg_class, min_size, max_size):
extractor = DummyExtractor()
super(DummyFasterRCNN, self).__init__(
extractor=extractor,
rpn=RPN(extractor.scales),
head=Head(n_fg_class + 1, extractor.scales),
min_size=min_size, max_size=max_size,
)


@testing.parameterize(
{'n_fg_class': 1},
{'n_fg_class': 5},
{'n_fg_class': 20},
{'n_fg_class': 1, 'min_size': 200, 'max_size': 400,
'in_shape': (3, 200, 50), 'expected_shape': (3, 400, 100)},
{'n_fg_class': 1, 'min_size': 800, 'max_size': 133,
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133 is typo of 1333?

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Yes, a typo.

'in_shape': (3, 480, 640), 'expected_shape': (3, 800, 1088)},
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prepare can accept a batch of images of different shapes.
How about 'in_sizes': [(480, 640), (320, 320)], 'expected_size': (800, 1088) ? (I omit 3 because it is not parameterized)

{'n_fg_class': 5, 'min_size': 200, 'max_size': 400,
'in_shape': (3, 200, 50), 'expected_shape': (3, 400, 100)},
{'n_fg_class': 5, 'min_size': 800, 'max_size': 133,
'in_shape': (3, 480, 640), 'expected_shape': (3, 800, 1088)},
{'n_fg_class': 20, 'min_size': 200, 'max_size': 400,
'in_shape': (3, 200, 50), 'expected_shape': (3, 400, 100)},
{'n_fg_class': 20, 'min_size': 800, 'max_size': 133,
'in_shape': (3, 480, 640), 'expected_shape': (3, 800, 1088)},
)
class TestFasterRCNN(unittest.TestCase):

def setUp(self):
self.link = DummyFasterRCNN(n_fg_class=self.n_fg_class)
self.link = DummyFasterRCNN(n_fg_class=self.n_fg_class,
min_size=self.min_size, max_size=self.max_size)

def test_use_preset(self):
self.link.nms_thresh = 0
Expand Down Expand Up @@ -117,13 +128,19 @@ def test_predict_gpu(self):
self.link.to_gpu()
assert_is_detection_link(self.link, self.n_fg_class)

def test_prepare(self):
imgs = [
np.random.randint(0, 255, size=(3, 480, 640)).astype(np.float32),
np.random.randint(0, 255, size=(3, 320, 320)).astype(np.float32),
]
x, scales = self.link.prepare(imgs)
self.assertEqual(x.shape, (2, 3, 800, 1088))
def check_prepare(self):
x = _random_array(np, self.in_shape)
out, scales = self.link.prepare(x)
self.assertIsInstance(out, np.ndarray)
self.assertEqual(out.shape, self.expected_shape)

def test_prepare_cpu(self):
self.check_prepare()
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We do not need to make _cpu/_gpu because prepare is not related cupy.


@attr.gpu
def test_prepare_gpu(self):
self.link.to_gpu()
self.check_prepare()


testing.run_module(__name__, __file__)