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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# A scratch pad notebook for testing out ideas"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# import libraries\n",
"import os\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Apricot', 'Apple', 'Asparagus', 'Basil', 'Beans', 'Broad Beans', 'Bush Beans', 'Climbing Beans', 'Beets', 'Borage', 'Broccoli', 'Brussel Sprouts', 'Cabbages', 'Chamomile', 'Carrots', 'Cauliflower', 'Celery', 'Cherry', 'Chervil', 'Chives', 'Coriander', 'Corn', 'Cucumber', 'Dill', 'Eggplant', 'Fennel', 'Marigold', 'Fruit Trees', 'Garlic', 'Gooseberry', 'Grape Vine', 'Grass', 'Horseradish', 'Lavendar', 'Leeks', 'Lemon Balm', 'Lettuce', 'Marjoram', 'Mints', 'Mulberry', 'Mustard', 'Nasturtiums', 'Onions', 'Parsley', 'Parsnip', 'Peas', 'Pennyroyal', 'Potato', 'Pumpkin', 'Radish', 'Raspberry', 'Rosemary', 'Roses', 'Rue', 'Sage', 'Savory', 'Shallots', 'Silverbeet', 'Spinach', 'Squash', 'Strawberries', 'Stinging Nettle', 'Sunflower', 'Tansy', 'Thyme', 'Tomato', 'Yarrow', 'Zucchini']\n"
]
}
],
"source": [
"# make plant_compatibility.csv into a matrix. it currently has indexes as rows and columns for plant names and then compatibility values as the values\n",
"plant_compatibility = pd.read_csv('../data/plant_compatibility.csv', index_col=0)\n",
"\n",
"# fill NaN values with 0\n",
"plant_compatibility = plant_compatibility.fillna(0)\n",
"\n",
"# get list of plants\n",
"plant_list = plant_compatibility.index.tolist()\n",
"print(plant_list)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"https://oaidalleapiprodscus.blob.core.windows.net/private/org-5YS2GMCG8RfgP4OEokQn3hGg/user-6uCRR8MZKqJD3U6peXi7IE82/img-17pR4xJgtkBs5Gx5Kx48xElA.png?st=2023-12-17T18%3A20%3A53Z&se=2023-12-17T20%3A20%3A53Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2023-12-16T19%3A51%3A17Z&ske=2023-12-17T19%3A51%3A17Z&sks=b&skv=2021-08-06&sig=6TrxNFh%2BsgPEMxqnNRc6qYagOGmEWbISLKW3wMKFosw%3D\n",
"https://oaidalleapiprodscus.blob.core.windows.net/private/org-5YS2GMCG8RfgP4OEokQn3hGg/user-6uCRR8MZKqJD3U6peXi7IE82/img-vqmQfv9IUlKzR08WzaniBpzs.png?st=2023-12-17T18%3A21%3A04Z&se=2023-12-17T20%3A21%3A04Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2023-12-17T19%3A11%3A33Z&ske=2023-12-18T19%3A11%3A33Z&sks=b&skv=2021-08-06&sig=dqymS6fNQkfntMPb31owYanMCfHwRcTnHMC7qc1OISI%3D\n"
]
}
],
"source": [
"\n",
"import openai\n",
"import requests\n",
"\n",
"# setup keys and api info\n",
"file_path = '/Users/dheym/Library/CloudStorage/OneDrive-Personal/Documents/side_projects/api_keys/openai_api_keys.txt'\n",
"with open(file_path, 'r') as file:\n",
" OPENAI_API_KEY = file.read()\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY\n",
"\n",
"# setup openai\n",
"openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n",
"\n",
"from openai import OpenAI\n",
"client = OpenAI()\n",
"\n",
"\n",
"\n",
"# call Dalle3 to generate images for each plant and save them in the assets folder. use the filename plant_x.png where x is the index of the plant in the plant_list.\n",
"#for i in range(45,len(plant_list)):\n",
"# edit 46, 48, 49, 51, 52, 53, 54, 55, 63 \n",
"for i in [46, 52]:\n",
"# 46, 48, 49, 51, 52, 53, 54, 55, 63 \n",
" plant_name = plant_list[i]\n",
" response = client.images.generate(\n",
" model=\"dall-e-3\",\n",
" prompt=\"a high quality color pixel image (think videogame) of \" + plant_name + \" (as in produce or the plant) with a solid black background. no other objects in the image.\",\n",
" size=\"1024x1024\",\n",
" quality=\"standard\",\n",
" n=1,\n",
" )\n",
"\n",
" # Get the image URL from the response\n",
" image_url = response.data[0].url\n",
" print(image_url)\n",
" \n",
" # Download the image\n",
" img_data = requests.get(image_url).content\n",
"\n",
" # Save the image in the assets folder with the specified filename\n",
" with open(f'../assets/plant_images/plant_{i}.png', 'wb') as handler:\n",
" handler.write(img_data)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Apricot', 'Apple', 'Asparagus', 'Basil', 'Beans', 'Broad Beans',\n",
" 'Bush Beans', 'Climbing Beans', 'Beets', 'Borage', 'Broccoli',\n",
" 'Brussel Sprouts', 'Cabbages', 'Chamomile', 'Carrots', 'Cauliflower',\n",
" 'Celery', 'Cherry', 'Chervil', 'Chives', 'Coriander', 'Corn',\n",
" 'Cucumber', 'Dill', 'Eggplant', 'Fennel', 'Marigold', 'Fruit Trees',\n",
" 'Garlic', 'Gooseberry', 'Grape Vine', 'Grass', 'Horseradish',\n",
" 'Lavendar', 'Leeks', 'Lemon Balm', 'Lettuce', 'Marjoram', 'Mints',\n",
" 'Mulberry', 'Mustard', 'Nasturtiums', 'Onions', 'Parsley', 'Parsnip',\n",
" 'Peas', 'Pennyroyal', 'Potato', 'Pumpkin', 'Radish', 'Raspberry',\n",
" 'Rosemary', 'Roses', 'Rue', 'Sage', 'Savory', 'Shallots', 'Silverbeet',\n",
" 'Spinach', 'Squash', 'Strawberries', 'Stinging Nettle', 'Sunflower',\n",
" 'Tansy', 'Thyme', 'Tomato', 'Yarrow', 'Zucchini'],\n",
" dtype='object')"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"\n",
"\n",
"plant_compatibility.columns.tolist()\n",
"# call Dalle3 to generate images for each plant and save them in the assets folder. use the filename plant_x.png where x is the index of the plant in the plant_list.\n",
"# for i in range(len(plant_list)):\n",
"\n"
]
}
],
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"language": "python",
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"file_extension": ".py",
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