Classifying-Painting-Art-Style-With-Deep-Learning

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Classifying-Painting-Art-Style-With-Deep-Learning

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Classifying painting into art style using transfer learning

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# Classifying Paintings by their Art Styles

![](https://raw.githubusercontent.com/samiramunir/Classifying-Painting-Art-Style-With-Deep-Learning/master/Media/artstyles.png)

Objective: 
	For this project I attempted to use convoluted neural networks and transfer learning to train a model to be able to classify 		a paintings art style. I used a dataset of paintings found on Kaggle. The details can be found at the following link.

https://www.kaggle.com/c/painter-by-numbers/data

Process:

The initial data exploration revealed that not all art styles had enough examples. So I picked  5 art styles that had atleast 1000 samples and that were visually quite different from each other.

![](https://raw.githubusercontent.com/samiramunir/Classifying-Painting-Art-Style-With-Deep-Learning/master/Media/EDA.png)

Engineered a CNN  on top of pretrained model VGG19 at the backend  to train on over 3000 painting images labeled by their art style.

Conducted hyper parameter tuning using Talos.

Final model: VGG19  +  4 Dense Layers (Relu) + final layer (Softmax). Achieved test accuracy of 68%.

![](https://raw.githubusercontent.com/samiramunir/Classifying-Painting-Art-Style-With-Deep-Learning/master/Media/model.png)

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Project Partner [Yi Shuen Lim](https://github.com/yishuen)
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