https://github.com/saravanabalagi/imaugtools

Tools used for aspect-ratio-preserving image augmentation, namely translate, rotate, crop WITHOUT stretching or skewing the image, or padding pixels to fill up empty space.
https://github.com/saravanabalagi/imaugtools

image-augmentation image-cropping image-processing image-processing-library image-rotation image-translation

Last synced: 3 months ago
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Tools used for aspect-ratio-preserving image augmentation, namely translate, rotate, crop WITHOUT stretching or skewing the image, or padding pixels to fill up empty space.

• Host: GitHub
• URL: https://github.com/saravanabalagi/imaugtools
• Owner: saravanabalagi
• License: mit
• Created: 2019-10-16T10:51:13.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-06-02T12:24:42.000Z (over 4 years ago)
• Last Synced: 2024-10-04T21:24:12.599Z (3 months ago)
• Topics: image-augmentation, image-cropping, image-processing, image-processing-library, image-rotation, image-translation
• Language: Jupyter Notebook
• Homepage: https://pypi.org/project/imaugtools
• Size: 2.15 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# imaugtools

![](https://img.shields.io/pypi/v/imaugtools)

![](https://img.shields.io/pypi/wheel/imaugtools)

![](https://img.shields.io/pypi/l/imaugtools)

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imaugtools contains tools used for image augmentation: translate, rotate, crop. This library is for you if you do NOT want to stretch or skew, or pad pixels that would make your images look strange when doing any of these operations.

## Installation

To install imaugtools, simply run in your terminal

```sh

pip install imaugtools

```

## Usage

Example image

![example-image](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_small.png)

### Translation

```py

from imaugtools import translate_image

my_image_translated = translate_image(my_image, 0.1, 0.2)

my_image_translated_uncropped = translate_image(my_image, 0.1, 0.2, crop=False)

imshow(my_image_translated, my_image_translated_uncropped, mode='BGR')

```

`imshow` function used here is to simply display the images, you can use it from [imshowtools](https://github.com/saravanabalagi/imshowtools) library.

With and without crop:

![translated-image](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_translated.png)

### Rotation

```py

from imaugtools import rotate_image

my_image_rotated = rotate_image(my_image, 30) # angle in degrees

my_image_rotated_uncropped = rotate_image(my_image, 30, crop=False)

imshow(my_image_rotated, my_image_rotated_uncropped, mode='BGR')

```

With and without crop:

![rotated-image](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_rotated.png)

### Cropping

```py

from imaugtools import center_crop, crop_around_center

my_image_center_cropped = center_crop(my_image, (150, 200))

my_image_cropped_around_center = crop_around_center(my_image, (150, 200))

imshow(my_image_center_cropped, my_image_cropped_around_center, mode='BGR')

```

Aspect ratio preserving center crop and crop around center:

![cropped-image](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_cropped.png)

```py

print(my_image_center_cropped.shape, my_image_cropped_around_center.shape)

# Output: (150, 200, 3) (150, 200, 3)

```

## Advanced Usage

### Strided Translation

Strided translation is one of the powerful image augmentation techniques used in training neural networks.

`tx_max = 1` and `ty_max = 1` is equivalent to a stride of 1 in both directions. After you specify `tx_max`, you can specify `tx` (translation in x-axis) from -`tx_max` to +`tx_max`. The same applies to `ty` and `ty_max`.

```py

my_images_translated = []

for j in range(-1, 2):

    for i in range(-1, 2):

        my_images_translated.append(translate_image(my_image, i, j, tx_max=1, ty_max=1))

imshow(*my_images_translated, mode='BGR')

```

![stride-1-translation](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_stride_1.png)

`tx_max = 0.5` and `ty_max = 0.5` is equivalent to a stride of 0.5 in both directions

```py

my_images_translated = []

for j in range(-2, 3):

    for i in range(-2, 3):

        my_images_translated.append(translate_image(my_image, i/4, j/4, tx_max=0.5, ty_max=0.5))

imshow(*my_images_translated, mode='BGR')

```

![stride-0.5-translation](https://github.com/saravanabalagi/imaugtools/raw/master/example/lenna_stride_0.5.png)

## Contributing

Pull requests are very welcome.

1. Fork the repo

1. Create new branch with feature name as branch name

1. Check if things work with a jupyter notebook

1. Raise a pull request

## Licence

Please see attached [Licence](https://github.com/saravanabalagi/imaugtools/blob/master/LICENSE)