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Support resize data augmentation according to original image size #291

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Dec 15, 2020
Merged

Support resize data augmentation according to original image size #291

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b9915ee
Support resize data augmentation according to original image size (im…
Junjun2016 Dec 8, 2020
dbe721c
fix docstring
Junjun2016 Dec 8, 2020
09e84e0
fix bug
Junjun2016 Dec 8, 2020
6241bcb
add unittest
Junjun2016 Dec 8, 2020
ed42fe9
img_scale=None in TTA
Junjun2016 Dec 9, 2020
f856dfa
fix bug
Junjun2016 Dec 9, 2020
010d7e0
add unittest
Junjun2016 Dec 10, 2020
a4f429b
fix typos
Junjun2016 Dec 13, 2020
3ab955e
fix bug
Junjun2016 Dec 14, 2020
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13 changes: 9 additions & 4 deletions mmseg/datasets/pipelines/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,8 @@ class Resize(object):
(multi-scale). There are 3 multiscale modes:
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- ``ratio_range is not None``: randomly sample a ratio from the ratio range
and multiply it with the image scale.
and multiply it with the image scale. When img_scale is None, img_scale is
the shape of image in results (img_scale = results['img'].shape[:2]).
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Suggested change
and multiply it with the image scale. When img_scale is None, img_scale is
the shape of image in results (img_scale = results['img'].shape[:2]).
and multiply it with the image scale. When img_scale is None, the image is resized based on the original size.


- ``ratio_range is None and multiscale_mode == "range"``: randomly sample a
scale from the a range.
Expand Down Expand Up @@ -50,7 +51,7 @@ def __init__(self,

if ratio_range is not None:
# mode 1: given a scale and a range of image ratio
assert len(self.img_scale) == 1
assert self.img_scale is None or len(self.img_scale) == 1
else:
# mode 2: given multiple scales or a range of scales
assert multiscale_mode in ['value', 'range']
Expand Down Expand Up @@ -150,8 +151,12 @@ def _random_scale(self, results):
"""

if self.ratio_range is not None:
scale, scale_idx = self.random_sample_ratio(
self.img_scale[0], self.ratio_range)
if self.img_scale is None:
scale, scale_idx = self.random_sample_ratio(
results['img'].shape[:2], self.ratio_range)
else:
scale, scale_idx = self.random_sample_ratio(
self.img_scale[0], self.ratio_range)
elif len(self.img_scale) == 1:
scale, scale_idx = self.img_scale[0], 0
elif self.multiscale_mode == 'range':
Expand Down
10 changes: 10 additions & 0 deletions tests/test_data/test_transform.py
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Expand Up @@ -38,6 +38,7 @@ def test_resize():
resize_module = build_from_cfg(transform, PIPELINES)

results = dict()
# (288, 512, 3)
img = mmcv.imread(
osp.join(osp.dirname(__file__), '../data/color.jpg'), 'color')
results['img'] = img
Expand Down Expand Up @@ -92,6 +93,15 @@ def test_resize():
resized_results = resize_module(results.copy())
assert max(resized_results['img_shape'][:2]) <= 1333 * 1.1

# test img_scale=None and ratio_range is tuple.
# img shape: (288, 512, 3)
transform = dict(
type='Resize', img_scale=None, ratio_range=(0.5, 2.0), keep_ratio=True)
resize_module = build_from_cfg(transform, PIPELINES)
resized_results = resize_module(results.copy())
assert int(288 * 0.5) <= resized_results['img_shape'][0] <= 288 * 2.0
assert int(512 * 0.5) <= resized_results['img_shape'][1] <= 512 * 2.0


def test_flip():
# test assertion for invalid prob
Expand Down