You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

139 lines
14 KiB
Plaintext

{
"cells": [
{
"cell_type": "markdown",
"id": "66f72396-0cf1-41cf-a486-2930d2ad1652",
"metadata": {},
"source": [
"# ghost_map\n",
"Give a string with the name of the image-file that was annotated with the Annotation Compass; Replace all characters of all annotation-texts with a ghost-glyph and return a string that includes all replaced annotation-texts plus html-tags that place them back into their original position."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "444e0267-c783-4b5a-9546-ad007175b6ea",
"metadata": {},
"outputs": [],
"source": [
"from urllib.request import urlopen\n",
"import json"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9bd8860a-9967-49d5-a74a-b5de669dfe6d",
"metadata": {},
"outputs": [],
"source": [
"def ghost_map(image: str, ghost_glyph: str ) -> str:\n",
" \"\"\"give a string with the name of the image-file that was annotated with the Annotation Compass; Replace all characters of all annotation-texts with a ghost-glyph and return a string that includes all replaced annotation-texts plus html-tags that place them back into their original position.\"\"\" \n",
" \n",
" url = f\"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image={image}\"\n",
" response = urlopen(url)\n",
" data_json = json.loads(response.read())\n",
" \n",
" filtered_map = '<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\">'\n",
" for label in data_json['labels']:\n",
" replaced_text = ''\n",
" for char in label['text']:\n",
" replaced_char = char\n",
" if not char.isspace():\n",
" replaced_char = ghost_glyph\n",
" replaced_text = replaced_text + replaced_char\n",
" html_tag = f'<p class=\"lowlight\" style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">{ replaced_text }</p>'\n",
" filtered_map = filtered_map + html_tag\n",
" return filtered_map"
]
},
{
"cell_type": "markdown",
"id": "1094ed8e-1387-481e-b612-9a8cc81d5c18",
"metadata": {},
"source": [
"This function was built for a project where individuals are invited to add their annotations on a map using the Annotation Compass. Each annotation-label is stored in a json-file and includes the annotation-text itself, but also the name of the image-file as well as the position, size, index, timestamp and userID of the annotation.\n",
"\n",
" Example for a label:\n",
"\n",
" {'image': 'map.jpg',\n",
" 'position': {'x': 12, 'y': 97},\n",
" 'size': {'width': 43, 'height': 18},\n",
" 'text': 'This is a text! Is this a text?',\n",
" 'timestamp': 'Wed, 01 Dec 2021 14:04:00 GMT',\n",
" 'userID': 5766039063}\n",
"\n",
"\n",
"If interested in the traces the annotations leave, ghost_map() can help. The function needs a string with the name of the of the image-file that was annotated with the annotation compass tool as well as a ghost-glyph that will replace all characters of the annotation-texts. The output is a string that includes all replaced annotation-texts plus html-tags that place them back into their original position.\n",
"\n",
"How to get a json-file with annotation-labels?\n",
"\n",
" https://hub.xpub.nl/soupboat/generic-labels/\n",
"The Annotation Compass allows people to uplaod an image and ask others to annotate it. A json-file of the annotations is provided."
]
},
{
"cell_type": "markdown",
"id": "2c3e992a-317b-4433-8c3b-9efcedea575d",
"metadata": {
"tags": []
},
"source": [
"## Examples\n",
"\n",
"In this example, the function replaces all characters of the annotation-texts with a ghost-glyph"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "60d22cde-79da-4dbd-a8a7-7028f785ec93",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\"><p class=\"lowlight\" style=\"left: 63.9896%; top: 34.2958%; position: absolute;\">##### ####### ###### ## ######### #########</p><p class=\"lowlight\" style=\"left: 33.6269%; top: 65.1408%; position: absolute;\">#### ## ## ## #### ## # ## ## # ##### ## #### ## #### ### ### #### ##\\n# ### ## ## ## ####### \\n##### #### ## ### ## ### \\n## ## ###### ######## #### ###</p><p class=\"lowlight\" style=\"left: 92.3483%; top: -0.179426%; position: absolute;\">### ############ ## ######### ####### ########## ###### ####### ## ####### ## ####### ## ############ ####### ### ####### ## #### ####### #### ## ### ####### ## ### \\n#### #### #### ## # ##### ## ##### ########### #### ###### #### ## # #### # ### #### ## ### ################### #####</p><p class=\"lowlight\" style=\"left: 65.3034%; top: 35.4839%; position: absolute;\">####### # #### ####### #### ## #### ####### ####### ## #### ### #### ### ##### ## ## ######### ####### ### ######## ###</p><p class=\"lowlight\" style=\"left: 48.135%; top: 20.4458%; position: absolute;\">##### ####### ## ####### #### #### ##### ## ### ####### ## ### # ##### #### ##### ####### ### ######## ##### ### #### ######## ###</p><p class=\"lowlight\" style=\"left: 76.25%; top: 69.5246%; position: absolute;\"># #### #### ## #### # ##### #### ### ## ###### #### ### ###### #####</p><p class=\"lowlight\" style=\"left: 39.3264%; top: 46.831%; position: absolute;\">##### ####### ######## ## ## ##### ####### #######</p><p class=\"lowlight\" style=\"left: 77.0%; top: 63.7521%; position: absolute;\">##### ####### ######### ########## #####\\n</p><p class=\"lowlight\" style=\"left: 63.7806%; top: 41.0296%; position: absolute;\"># ##### ## ### ##### ###### ## ### ###### ###### ### ##### ### # ####### ## ######### ### # ###### ###### ########## ### ####### ##### ### ### #### ### #### #### ## ## ### ##### #####</p><p class=\"lowlight\" style=\"left: 48.9886%; top: 51.256%; position: absolute;\">## ##### # #### ### ###### ## ### #### ### ########## ##### ####### ## #### #####</p><p class=\"lowlight\" style=\"left: 36.5285%; top: 54.2958%; position: absolute;\">##### ####### ######## ## ### ##### #### ## ##### ######### # ##### ### ##########</p><p class=\"lowlight\" style=\"left: 55.0889%; top: 15.6154%; position: absolute;\">### #### ########## ##### ######## ## ####### ########## #### ### ######## ###### ### # ###### ### ### ###### ## ####### #### ### #### ###### ##### ### ##### #### #### #### ### # ## ### #### ######## ## ### ### #####</p><p class=\"lowlight\" style=\"left: 47.2668%; top: 70.1459%; position: absolute;\">####### ### ## ### ##### ### ####### ### ####### ### ####### #### ### ### #### ### ### ## #### ##### ###### ### # ####### ## #### ## ######## ######## ## ############</p><p class=\"lowlight\" style=\"left: 42.5389%; top: 45.7042%; position: absolute;\">##### ####### #### ## ## #### ####</p><p class=\"lowlight\" style=\"left: 45.2507%; top: 29.3907%; position: absolute;\"># ### ### #### ####### ##### ####### ##### ### ###### ###### ###### ## ## ### ###### ### ## #### #### #### ###### #### ### ########## # ### ### ### ### #####</p><p class=\"lowlight\" style=\"left: 60.774%; top: 59.7488%; position: absolute;\">######## ## ### ######</p><p class=\"lowlight\" style=\"left: 42.0882%; top: 18.8014%; position: absolute;\">## ##### ##### ######## # ### ###### ####### ##### #### #### ######### ####### # #### # ########## #### ### ##### # ###### # ##### ## ## ######## #### #### ####</p><p class=\"lowlight\" style=\"left: 39.1192%; top: 36.2676%; position: absolute;\">##### ####### #### ## #### ####### ## ####</p><p class=\"lowlight\" style=\"left: 43.7995%; top: 27.0609%; position: absolute;\"># ### ### #### ####### ##### ####### ##### ### ###### ###### ###### ## ## ### ###### ### ## #### #### #### ###### #### ### ### ############# # ### ### ### ### #####</p><p class=\"lowlight\" style=\"left: 75.285%; top: 29.2254%; position: absolute;\">### ## ###### ######### #### # ### ### ##### ## ### #### #### ## #### ## #### ## ###
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ghost_map('rejection_map.jpg', '#')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7a8c88f3-2f16-4dce-9e29-547648e251c2",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}