https://github.com/phanakata/art_identification_using_cnn
Python package to indentify art painting with convolutional neural networks
https://github.com/phanakata/art_identification_using_cnn
convolutional-neural-networks indentifying-arts tensorflow tensorflow-models
Last synced: 3 months ago
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Python package to indentify art painting with convolutional neural networks
- Host: GitHub
- URL: https://github.com/phanakata/art_identification_using_cnn
- Owner: phanakata
- Created: 2018-12-11T17:43:08.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-12-18T18:27:49.000Z (over 7 years ago)
- Last Synced: 2025-07-19T17:33:16.848Z (12 months ago)
- Topics: convolutional-neural-networks, indentifying-arts, tensorflow, tensorflow-models
- Language: Jupyter Notebook
- Homepage:
- Size: 29.9 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# art_identifcation_using_CNN
Codes for identifying arts using convolutional neural networks (CNN). In this package we provide codes for preprocessing purposes such as, resizing images and relabeling data, and CNN models implemented in TensorFlow.
## Data
We used art paintings provided Painter by Numbers competionKaggle competion https://www.kaggle.com/c/painter-by-numbers/data.
## General usage
1. The helper functions can be found in `tools/`
2. A simple jupyter notebook to preprocess images and generate binary numpy files is avalaible in `data/convert_images_to_numpy.ipynb`
3. A simple jupyter notebook to perform classification with TensorFlow is avalaible in `models/CNN_VGGNet_for_classification.ipynb`
This package is still under development and more features will be added.
## Authors:
Paul Hanakata, Owen Howell, Varun Ursekar