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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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# 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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- 2022-01-18 first created by jaekoo kang |
