[GSoC22] Data Augmentation Module in OpenCV (imgaug)

[ZhaoChuyang]

PR for GSoC'22 project on Efficient Data Augmentation Module in OpenCV for DL Training

I implemented data augmentation methods based on basic image processing and have tested the performance of these already implemented methods in python enviroment. The following table demonstrates the running time (in seconds) comparison between OpenCV-Aug module and torchvision transforms on a subset of ImageNet:

single method:

method	config	dataset	opencv	torchvision
resize	size: (200, 200)	imagenet-320	0.388	1.745
center crop	size: (200, 200)	imagenet-320	0.001	0.017
pad	padding: (100, 100, 100, 100)	imagenet-320	0.141	0.553
random crop	size: (200, 200)	imagenet-320	0.001	0.028
random resized crop	size: (500, 500)	imagenet-320	0.368	3.806
random flip	default	imagenet-320	0.046	0.519

compose multiple methods:

method	config	num_augs	opencv	pytorch
RandomCrop + RandomFlip + Pad	RandomCrop: size(300, 300) Pad: padding(100, 100, 100, 100)	3	0.481	1.240
Resize + Pad + RandomFlip + CenterCrop	Resize: size(400, 400) Pad: padding(100, 100, 100, 100) CenterCrop: size(200, 200)	5	0.636	5.486

Besides augmentation methods for pure images, augmentation methods for detection task and segmentation task is also added, which requires processing the target labels of corresponding tasks.

Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

• [x] I agree to contribute to the project under Apache 2 License.
• [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
• [x] The PR is proposed to the proper branch
• [ ] There is a reference to the original bug report and related work
• [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name.
• [x] The feature is well documented and sample code can be built with the project CMake

[ZhaoChuyang]

Hi @kaingwade, thanks for the advice. I have added the license and add documentation for imgaug module. Junk codes in header files have also been cleaned.

[asenyaev]

Hello @ZhaoChuyang!

I have added support for opencv_test_imgaug in CI. Could you push the latest commit again to re-run CI for this PR?

[ZhaoChuyang]

Hi @asenyaev, I have commited the latest changes.

[asmorkalov]

General notes on test code:

• There is no need to store cropped/flipped/converted images in opencv_extra, if test checks single transformation. It's better to call reference function from OpenCV itself. The test should check new logic, but not OpenCV primitives behavior.
• Do not use ts->set_failed_test_info. It old API. Just GTest EXPECT_XXX and ASSERT_XXX are simpler and it very clean which of condition fails.

[asmorkalov]

@ZhaoChuyang Friendly reminder.

[ZhaoChuyang]

Hi, sorry for the delay, I have been caught up in a DDL. I'll fix them ASAP.

[LaurentBerger]

What's new about this module?