Pre-quantize the corpus
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@@ -0,0 +1,61 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"from util import load_image_128, quantize_image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Processing ../corpus/iso_ray-09_000.png...\n"
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]
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}
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],
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"source": [
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"corpus_dir = Path('../corpus/')\n",
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"quantized_dir = corpus_dir / 'quantized'\n",
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"\n",
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"for src_path in Path('../corpus/').glob('*.*'):\n",
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" dest_path = quantized_dir / src_path.name\n",
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" if not dest_path.exists():\n",
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" print(f\"Processing {src_path}...\")\n",
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" img = load_image_128(src_path)\n",
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" img = quantize_image(img)\n",
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" img.save(dest_path)\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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