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 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 = '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