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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
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