rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194191844
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File path: example/image-classification/common/data.py
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@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+ aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+ aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+ aug.add_argument('--brightness', type=float, default=0,
Review comment:
How about a function like the set_aug_level with the defaults set for
resnet, but that function is not automatically called?
My only concern was that we don't have a good source (for users not using
GluonCv, on a good set of starting params). Your point also makes sense, don't
have a strong opinion on this.
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