MVDatagen
The tool aims to facilitate generation of image based datasets for machine vision projects.
The project solves two problems:
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marking of existing images
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generating new marked images via transformations like perspective transformations, adding blur, noise etc. This can enlarge your dataset and make your learning algorithms more accurate and robust.
Compilation
The project uses OpenCV for image IO and geometry transformations.
Project can be compiled using the supplied Makefile. Modify it to suit your needs.
Usage
Once compiled the tool can be used in the following way
./MVDatagen -e <existing_dataset_folder> -g <generated_dataset_folder> <additional_options>
For the first use, locate the folder with your images and decide where you want your generated images to be placed. Then use:
./MVDatagen -e <existingImagesFolder> -g <generatedImagesFolder>
This will place the generated images in <generatedImagesFolder>, and also create two files:
<existingImagesFolder>/dataset.txt and <generatedImagesFolder>/dataset.txt. These contain dataset information.
If MVDatagen finds the existing file <existingImages>/dataset.txt, the marking process will be skipped, and you will see the appropriate message. That file will then serve as the basis for generation process.
Additional options are:
-n(value) (e.g. -n10) - creates 10 noised images for each original image. Default is 5. Must be greater than 0.
-v(value) (e.g. -v6) - variance of noise. Default is 10.
-p(value) (e.g. -p8) - creates 8 perspective transformed images for each original image. Default is 10.
-s(value) (e.g. -s5) - variance of perspective. Default is 10.
-b(value) (e.g. -b6) - creates 6 blurred images for each original image. Default is 5.
-r(value) (e.g. -r3) - radius of blur. Default is 3.
-f(value) (e.g. -f1) - Generate flipped image. Default is 1 (true).