Files
vehicle-classification/notebooks/model-training-v1.ipynb
KeshavAnandCode e2406925da exploring data
2026-03-18 17:12:34 -05:00

77 lines
1.5 KiB
Plaintext

{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "7a37220a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello, World!\n"
]
}
],
"source": [
"print(\"Hello, World!\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d318d1f0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Van: 1111 images\n",
"Taxi: 748 images\n",
"Bicycle: 1618 images\n",
"Bus: 2133 images\n",
"Car: 6781 images\n",
"Motorcycle: 2986 images\n",
"Truck: 2033 images\n",
"NonVehicles: 8968 images\n"
]
}
],
"source": [
"import os\n",
"\n",
"data_dir = '../data/raw/vehicle_classification'\n",
"\n",
"for class_name in os.listdir(data_dir):\n",
" class_path = os.path.join(data_dir, class_name)\n",
" if os.path.isdir(class_path):\n",
" count = len(os.listdir(class_path))\n",
" print(f\"{class_name}: {count} images\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.15"
}
},
"nbformat": 4,
"nbformat_minor": 5
}