https://github.com/swhl/image_augmentor
An easy-to-use tool for offline data enhancement of images
https://github.com/swhl/image_augmentor
Last synced: 30 days ago
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An easy-to-use tool for offline data enhancement of images
- Host: GitHub
- URL: https://github.com/swhl/image_augmentor
- Owner: SWHL
- License: apache-2.0
- Created: 2021-08-07T09:26:43.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-11-29T13:08:08.000Z (over 4 years ago)
- Last Synced: 2025-01-25T05:41:27.422Z (over 1 year ago)
- Language: Python
- Size: 8 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Update
### 2021-08-07 update
- Add whl package for easy use
## Note
- **This code has a faster speed with the python-opencv.**
- Modify from https://github.com/codebox/image_augmentor for image augmentation by python-opencv.
## Image Augmentor
This is a simple data augmentation tool for image files, intended for use with machine learning data sets.
The tool scans a directory containing image files, and generates new images by performing a specified set of
augmentation operations on each file that it finds. This process multiplies the number of training examples that can
be used when developing a neural network, and should significantly improve the resulting network's performance,
particularly when the number of training examples is relatively small.
Run the utility from the command-line as follows:
```python
from img_aug_offline import ImgAugOffline
img_auger = ImgAugOffline()
img_auger(r'images', ['fliph', 'flipv'])
```
or
```shell
pip install img_aug_offline-0.1-py3-none-any.whl
img_aug_offline images fliph flipv
```
The `` argument should be the path to a directory containing the image files to be augmented.
The utility will search the directory recursively for files with any of the following extensions:
`jpg, jpeg, bmp, png`.
The `transform` arguments determine what types of augmentation operations will be performed,
using the codes listed in the table below:
|Code|Description|Example Values|
|---|---|------|
|`fliph`|Horizontal Flip|`fliph`|
|`flipv`|Vertical Flip|`flipv`|
|`noise`|Adds random noise to the image|`noise_20`,`noise_50`|
|`rot`|Rotates the image by the specified amount|`rot_90`,`rot_-45`|
|`trans`|Shifts the pixels of the image by the specified amounts in the x and y directions|`trans_20_10`,`trans_-10_0`|
|`zoom`|Zooms into the specified region of the image, performing stretching/shrinking as necessary|`zoom_0_0_20_20`,`zoom_-10_-20_10_10`|
|`blur`|Blurs the image by the specified amount, which is only odd number |`blur_1`,`blur_3`, `blur_5`|
Each transform argument results in one additional output image being generated for each input image.
An argument may consist of one or more augmentation operations. Multiple operations within a single argument
must be separated by commas, and the order in which the operations are performed will match the order in which they
are specified within the argument.
### Examples
Produce 2 output images for each input image, one of which is flipped horizontally, and one of which is flipped vertically:
```shell
python main.py ./images fliph flipv
```
Produce 1 output image for each input image, by first rotating the image by 90° and then flipping it horizontally:
```shell
python main.py ./images rot_90,fliph
```
### Operations
#### Horizontal Flip
Mirrors the image around a vertical line running through its center
```shell
python main.py ./my_images fliph
```
#### Vertical Flip
Mirrors the image around a horizontal line running through its center
```shell
python main.py ./my_images flipv
```
#### Noise
Adds random noise to the image. The amount of noise to be added is specified by a floating-point numeric value that is included
in the transform argument, the numeric value must be greater than 0.
```shell
python main.py ./my_images noise_20 noise_50
```
#### Rotate
Rotates the image. The angle of rotation is specified by an integer value that is included in the transform argument.
```shell
python main.py ./my_images rot_-45 rot_90
```
#### Translate
Performs a translation on the image. The size of the translation in the x and y directions are specified by integer values that
are included in the transform argument
```shell
python main.py ./my_images trans_20_20 trans_0_100
```
#### Zoom/Stretch
Zooms in (or out) to a particular area of the image. The top-left and bottom-right coordinates of the target region are
specified by integer values included in the transform argument. By specifying a target region with an aspect ratio that
differs from that of the source image, stretching transformations can be performed.
```shell
python main.py ./my_images zoom_100_200_600_500 zoom_330_650_600_798
```
#### Blur
Blurs the image by the `cv2.GaussianBlur()` of the opencv. The amount of blurring is specified by a positive and odd value or zeros. Details in [GaussianBlur()](https://docs.opencv.org/master/d4/d86/group__imgproc__filter.html#gaabe8c836e97159a9193fb0b11ac52cf1). See `assets/blur/` for more examples.
```shell
python main.py ./my_images blur_1 blur_3 blur_9 blur_19
```
