Simple CNN-based Artist Classifier

This repo contains a simple CNN-based Keras model which classifies images into one of 10 selected artists/painters.

• The purpose of this model was for a quick prototyping
• Data has been web-crawled using https://github.com/YoongiKim/AutoCrawler
• 10 popular artists/painters were chosen:
  • [ARTIST]: [ID]
  • claude_monet: 0,
  • henri_matisse: 1,
  • jean_michel_basquiat: 2,
  • keith_haring: 3,
  • pablo_picasso: 4,
  • pierre_augste_renoir: 5,
  • rene_magritte: 6,
  • roy_richtenstein: 7,
  • vincent_van_gogh: 8,
  • wassily_kandinsky: 9
• About 100 representative paintings per artist were crawled and manually checked
• Dataset will be shared later

How to use

import tensorflow as tf
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("jkang/drawing-artist-classifier")

image_file = 'monet.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 production, but for research and quick prototyping. Web-crawled image data might not have a balanced amount of drawings that sufficiently represent the artists.

• 2022-01-18 first created by jaekoo kang