Create README.md

README.md

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+---
+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 = 'kandinski.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 the production, but for a research and quick prototyping.
+Web-crawled image data might not have balanced amount of drawings that sufficiently represent the artists.
+---
+- 2022-01-18 first created by jaekoo kang