Augment Image Data
Project description
Image-Data-Augmentor
Author : Aditya Mangal
Image-Data-Augmentor Image-Data-Augmentor is a Python module designed to enhance the preprocessing pipeline for machine learning models by providing a robust set of image augmentation techniques.
It focuses on modifying the input image data in various controlled ways, allowing developers and researchers to generate a more diverse dataset, improving the model's ability to generalize and handle unseen data.
Installation
Dependencies
- Python (>= 3.7)
- cv2 (>= 4.5)
- NumPy (>= 1.17)
- glob (>= 0.7)
- future (>= 0.18.2)
- ConcurrentImageRead (>= 0.0.10)
User installation
pip install ImageDataAugmenter
To Do List
- Integrate Data Iterator
- Integrate Parallel Processing Pipeline
- Add yolo and xml boxes augmenter
- Generative Adversarial Networks will be used to generate new samples of images
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file imagedataaugmentor-1.0.0.tar.gz.
File metadata
- Download URL: imagedataaugmentor-1.0.0.tar.gz
- Upload date:
- Size: 6.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ba384c439fb54e1d9005625822648abb3413fc7b22078134f79e673242bcb795
|
|
| MD5 |
ad6b9b571927a616992f69962c4b786c
|
|
| BLAKE2b-256 |
8f357816f5f76d60de2347614058a26be0e1c6d32831666c4e14005618254eb1
|
File details
Details for the file ImageDataAugmentor-1.0.0-py3-none-any.whl.
File metadata
- Download URL: ImageDataAugmentor-1.0.0-py3-none-any.whl
- Upload date:
- Size: 7.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ce1b7afb3535e271c94909f272cf83150e3083be7dd351fe08f21addbd8a50bf
|
|
| MD5 |
a1c7b25645803ef4c63ef1c83bea5803
|
|
| BLAKE2b-256 |
f9b248149cbc7604d6b48b565c468da38e0ba4a61659ec5ca5fb9f4702e12326
|
