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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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