https://github.com/yeonghyeon/dcraw
DCRAW: Deep Convolutional Recurrent Attentive Writer
https://github.com/yeonghyeon/dcraw
Last synced: 3 months ago
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DCRAW: Deep Convolutional Recurrent Attentive Writer
- Host: GitHub
- URL: https://github.com/yeonghyeon/dcraw
- Owner: YeongHyeon
- License: mit
- Created: 2019-04-25T06:45:49.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-05-24T06:34:19.000Z (over 6 years ago)
- Last Synced: 2025-02-26T05:32:53.505Z (7 months ago)
- Language: Python
- Homepage:
- Size: 4.03 MB
- Stars: 4
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DCRAW: Deep Convolutional Recurrent Attentive Writer
Implementation of DRAW based Auto-Encoder.
First of all, feature maps are extracted from Deep Convolutional Neural Network (DCNN).
Then, encoding and decoding are recurrently conducted by DRAW.
Code after decoding is used to reconstruct original image.
(When the purpose is not reconstructing of original image, it is possible to set the other target image.)
## Requirements
* Python 3.5.2
* Tensorflow 1.4.0
* Numpy 1.13.3
* Scipy 1.2.0
* Matplotlib 3.0.2
## Usage
Just run the following command in the terminal.
```
$ python run.py // with default options
$ python run.py --attention True // for using attentive read and write.
$ python run.py --help // for confirming the option
```
## Architecture
Whole architecture of the DCRAW.
Architecture of the DRAW.
## Results
Following figures are sequentially generated by DCRAW for each epoch.
### Without attention
Epoch 0
Epoch 500
Epoch 1000
### With attention
Epoch 0
Epoch 500
Epoch 1000
## Reference
* [DRAW: Deep Recurrent Attentive Writer](https://arxiv.org/abs/1502.04623)
* [Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction](https://link.springer.com/chapter/10.1007/978-3-642-21735-7_7)
* [An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition](https://ieeexplore.ieee.org/abstract/document/7801919)
## Author
YeongHyeon Park