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{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"id": "c168f24a",
"metadata": {},
"outputs": [],
"source": [
"!pip install -Uqq fastai duckduckgo_search pandas"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c84aa916",
"metadata": {},
"outputs": [],
"source": [
"from duckduckgo_search import ddg_images\n",
"from fastcore.all import *\n",
"from time import sleep\n",
"import pandas as pd\n",
"from io import StringIO\n",
"\n",
"\n",
"def search_images(term, max_images=50):\n",
" print(f\"Searching for '{term}'\")\n",
" return L(ddg_images(term, max_results=max_images)).itemgot('image')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fef32513",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a17948bf",
"metadata": {},
"outputs": [],
"source": [
"searches = 'basketball ball','rugby ball', 'soccer ball', 'golf ball'\n",
"path = Path('model_pics')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a78f7280",
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"\n",
"for o in searches:\n",
" dest = (path/o)\n",
" dest.mkdir(exist_ok=True, parents=True)\n",
" download_images(dest, urls=search_images(f'{o} photo'))\n",
" sleep(10) # Pause between searches to avoid over-loading server"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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