Style transfer is generating an image with the same "content" as a base image, but with the "style" of a different picture (typically artistic). This code provides a TensorFlow implementation and pretrained models for Artistic Neural Style Transfer, as described in the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge.
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├── #1report - report of the implementation
├── #2nueral_style_transform.ipynb - implentation using pretrainged vgg16 using imagenet
├── #3vgg.ipynb - implentation using vgg16 trained with your dataset
├── README.md
VGG16 is a convolution neural net (CNN ) architecture :
- 2 x convolution layer of 64 channel of 3x3 kernal and same padding
- 1 x maxpool layer of 2x2 pool size and stride 2x2
- 2 x convolution layer of 128 channel of 3x3 kernal and same padding
- 1 x maxpool layer of 2x2 pool size and stride 2x2
- 3 x convolution layer of 256 channel of 3x3 kernal and same padding
- 1 x maxpool layer of 2x2 pool size and stride 2x2
- 3 x convolution layer of 512 channel of 3x3 kernal and same padding
- 1 x maxpool layer of 2x2 pool size and stride 2x2
- 1 x Dense layer of 4096 units
- 1 x Dense layer of 4096 units
- 1 x Dense Softmax layer of 2 units
Dataset it's from kaggle best artwork all time It contain best artwork of all time from famous artists
After 1000 epoch the accuracy reached 70 precent
The next step is that we will implement the algorithm into an api that take capture image of a person and then generate a new style with his/her chosen style and print it. For any information contact [email protected] or [email protected].