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---
language: en
license: mit
datasets:
- web crawled (coming soon)
---
# Simple CNN-based Artist Classifier
This repo contains a simple CNN-based Keras model which classifies images into one of 8 artistic trends.
See also: `https://huggingface.co/jkang/drawing-artist-classifier`
- The purpose of this model was for a quick prototyping
- Data has been web-crawled using `https://github.com/YoongiKim/AutoCrawler`
- 8 popular artists/painters were chosen:
- \[TREND\]: \[ID\]
- cubism: 0,
- expressionism: 1,
- fauvisme: 2,
- graffitiar: 3,
- impressionism: 4,
- popart: 5,
- post_impressionism: 6,
- surrealism: 7}
- About 100 representative paintings per artist considering 8 trends were crawled and manually checked
- Dataset will be shared later
# How to use
```python
import tensorflow as tf
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("jkang/drawing-artistic-trend-classifier")
image_file = 'kandinski.jpg'
img = tf.io.read_file(image_file)
img = tf.io.decode_jpeg(img, channels=3)
last_layer_activation, predictions = model(img[tf.newaxis,...])
```
# Intended uses & limitations
You can use this model freely for predicting artists or trends of a given image.
Please keep in mind that this model is not intended for the production, but for a research and quick prototyping.
Web-crawled image data might not have balanced amount of drawings that sufficiently represent the artists.
---
- 2022-01-18 first created by jaekoo kang |