77 lines
1.5 KiB
Plaintext
77 lines
1.5 KiB
Plaintext
{
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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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"id": "7a37220a",
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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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"Hello, World!\n"
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]
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}
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],
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"source": [
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"print(\"Hello, World!\")"
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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": 2,
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"id": "d318d1f0",
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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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"Van: 1111 images\n",
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"Taxi: 748 images\n",
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"Bicycle: 1618 images\n",
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"Bus: 2133 images\n",
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"Car: 6781 images\n",
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"Motorcycle: 2986 images\n",
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"Truck: 2033 images\n",
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"NonVehicles: 8968 images\n"
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]
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}
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],
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"source": [
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"import os\n",
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"\n",
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"data_dir = '../data/raw/vehicle_classification'\n",
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"\n",
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"for class_name in os.listdir(data_dir):\n",
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" class_path = os.path.join(data_dir, class_name)\n",
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" if os.path.isdir(class_path):\n",
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" count = len(os.listdir(class_path))\n",
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" print(f\"{class_name}: {count} images\")"
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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": "3.11.15"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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