https://github.com/dataplayer12/hey-daug
A light weight data augmentation tool for training CNNs and Viola Jones detectors
https://github.com/dataplayer12/hey-daug
computer-vision convolutional-neural-networks data-augmentation haar-cascade viola-jones
Last synced: 11 months ago
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A light weight data augmentation tool for training CNNs and Viola Jones detectors
- Host: GitHub
- URL: https://github.com/dataplayer12/hey-daug
- Owner: dataplayer12
- License: mit
- Created: 2018-04-04T12:25:19.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-04-05T04:15:45.000Z (almost 8 years ago)
- Last Synced: 2025-01-22T23:26:35.094Z (about 1 year ago)
- Topics: computer-vision, convolutional-neural-networks, data-augmentation, haar-cascade, viola-jones
- Language: Python
- Homepage:
- Size: 7.81 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# hey-daug
A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six times. Use with care.
Steps for use:
1. Set the parameters for images in constants.py
2. Use data augmentation in your code:
```python
import data_utils as daug
folders=[folder1, folder2] #list of folder paths where training images are saved, ex. ['./pos' , './neg']
daug.augment_and_save(folders)
```
If you would like to remove augmented images and keep originals, use:
```python
du.remove_augmented_data(folders)
```