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https://github.com/ramidecodes/image-dataset-augmentator

Image augmentation pipepline for conditional GANs base on Augmentator library
https://github.com/ramidecodes/image-dataset-augmentator

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Image augmentation pipepline for conditional GANs base on Augmentator library

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# image-dataset-augmentatator
Image augmentation pipepline for conditional GANs base on Augmentator library

## Available parameters
* `--input_dir` path to directory containing the images
* `--output_dir` path to directory to save new images
* `--output_format` output image format (JPEG|BMP|PNG|GIF)
* `--output_width` output image width in pixels
* `--output_height` output image height in pixels
* `--resample_filter` filter to use when resampling (BICUBIC|BILINEAR|ANTIALIAS|NEAREST)
* `--sample_count` amount of new images to generate
* `--zoom` zoom in randomly
* `--distortion` distort randomly
* `--output_prefix` prefix used to lable output images 'prefix_00001.jpeg'

## Basic execution
```bash
python3 augmentator.py --input_dir 'path/to/your/images' --output_dir 'path/to/your/augmented/images' --zoom --distortion --output_prefix 'relevantprefix' --sample_count 100
```

This will do random crops and resize the images to 512px also add random zoom and distortion.