readme: ---
  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 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
  ```python
  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