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---
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language: en
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license: mit
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datasets:
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- web crawled (coming soon)
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---
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# Simple CNN-based Artist Classifier
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This repo contains a simple CNN-based Keras model which classifies images into one of 8 artistic trends.
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See also: `https://huggingface.co/jkang/drawing-artist-classifier`
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- The purpose of this model was for a quick prototyping
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- Data has been web-crawled using `https://github.com/YoongiKim/AutoCrawler`
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- 8 popular artists/painters were chosen:
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- \[TREND\]: \[ID\]
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- cubism: 0,
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- expressionism: 1,
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- fauvisme: 2,
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- graffitiar: 3,
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- impressionism: 4,
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- popart: 5,
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- post_impressionism: 6,
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- surrealism: 7}
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- About 100 representative paintings per artist considering 8 trends were crawled and manually checked
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- Dataset will be shared later
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# How to use
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```python
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import tensorflow as tf
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from huggingface_hub import from_pretrained_keras
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model = from_pretrained_keras("jkang/drawing-artistic-trend-classifier")
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image_file = 'kandinski.jpg'
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img = tf.io.read_file(image_file)
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img = tf.io.decode_jpeg(img, channels=3)
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last_layer_activation, predictions = model(img[tf.newaxis,...])
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```
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# Intended uses & limitations
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You can use this model freely for predicting artists or trends of a given image.
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Please keep in mind that this model is not intended for the production, but for a research and quick prototyping.
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Web-crawled image data might not have balanced amount of drawings that sufficiently represent the artists.
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---
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- 2022-01-18 first created by jaekoo kang
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