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318 lines
12 KiB
Plaintext
318 lines
12 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": "aecab081-a69a-4e38-9a30-cfc95661e56b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from urllib.request import urlopen\n",
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"import json"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9538705e-e51e-49da-b4fe-e6c4c6f6c435",
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"metadata": {},
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"source": [
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"Area Map:\n",
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"Give a string with the name of the image-file that was annotated with the Annotation Compass; Select a specific area of the image, return a list of all labels in that specific area."
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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": "13246f4a-81ac-4b68-b974-ae04064d10cc",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# (combined with html_tag_list)\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def area_map_list(labels: list, left: int, right: int, top: int, bottom: int ) -> list: \n",
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" \n",
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" filtered_map = []\n",
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" for label in labels:\n",
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" if left <= (label['position']['x']) <= right and top <= (label['position']['y']) <= bottom:\n",
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" filtered_map.append(label)\n",
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" \n",
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" return filtered_map\n",
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"\n",
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"#area_map_list(data_json['labels'], 0, 10, 30, 70)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "34b43aae-0830-47ca-86c9-5827bfa44cef",
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"metadata": {},
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"source": [
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"Ghost Map:\n",
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"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."
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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": 4,
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"id": "dcbe893c-d00a-4933-9a18-8216a5f7459a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# this function links to jian.css\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def ghost_map_list(labels: list, ghost_glyph: str ) -> str:\n",
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" \n",
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" filtered_map = '<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\">'\n",
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" for label in labels:\n",
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" replaced_text = ''\n",
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" for char in label['text']:\n",
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" replaced_char = char\n",
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" if not char.isspace():\n",
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" replaced_char = ghost_glyph\n",
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" replaced_text = replaced_text + replaced_char\n",
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" html_tag = f'<p class=\"ghost\" style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">{ replaced_text }</p>'\n",
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" filtered_map = filtered_map + html_tag\n",
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" return filtered_map\n",
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"\n",
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"#ghost_map_list(data_json['labels'], '.')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "863a6716-d9e4-413f-a597-a16cc0f04d6d",
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"metadata": {},
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"source": [
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"Highlight Map:\n",
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"Give a string with the name of the image-file that was annotated with the Annotation Compass; Give a target-word; Return a string that includes all annotation-texts plus html-tags that place them back into their original position while highlighting the annotation-texts that include the target."
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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": 5,
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"id": "18cfc4fa-4039-49fe-8b29-5bbec0e89b6f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# this function links to jian.css\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def highlight_map_list(labels: list, target: str ) -> str:\n",
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"\n",
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" filtered_map = '<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\">'\n",
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" for label in labels:\n",
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" if target in label['text']:\n",
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" highlight_tag = f'<p class=\"highlight\" style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">{ label[\"text\"] }</p>'\n",
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" filtered_map = filtered_map + highlight_tag\n",
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" else:\n",
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" html_tag = f'<p class=\"lowlight\" style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">{ label[\"text\"] }</p>'\n",
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" filtered_map = filtered_map + html_tag\n",
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" \n",
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" return filtered_map\n",
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"\n",
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"#highlight_map_list(data_json['labels'], 'tunnel')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9c41f5fd-1071-43b3-88bc-41a8e5907fdb",
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"metadata": {},
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"source": [
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"html-tag:\n",
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"Give a string with the name of the image-file that was annotated with the Annotation Compass; Return a string that can include the position, text, timestamp and/or userID of all labels plus html-tags that place them back into their original position."
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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": 6,
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"id": "a7ee1bdf-a356-4a66-aa01-ef1dad8738ca",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# this function links to jian.css\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def html_tag_list(labels: list, position: bool, text: bool, timestamp: bool, userID: bool ) -> str: \n",
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" \n",
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" html_tags = '<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\">'\n",
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" for label in labels:\n",
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" html_tags = html_tags + f'<p style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">'\n",
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" if position == True:\n",
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" html_position = f'{ label[\"position\"] } '\n",
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" html_tags = html_tags + html_position\n",
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" if text == True:\n",
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" html_text = f'{ label[\"text\"] } '\n",
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" html_tags = html_tags + html_text\n",
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" if timestamp == True:\n",
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" html_timestamp = f'{ label[\"timestamp\"] } '\n",
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" html_tags = html_tags + html_timestamp\n",
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" if userID == True:\n",
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" html_userID = f'{ label[\"userID\"] } '\n",
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" html_tags = html_tags + html_userID\n",
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" html_tags = html_tags + '</p>'\n",
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" \n",
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" return html_tags\n",
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"\n",
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"#html_tag_list(data_json['labels'], True, False, False, False)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d05dd98e-0cdb-4a50-839a-7a67cdc22010",
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"metadata": {},
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"source": [
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"Individual Map:\n",
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"give a string with the name of the image-file that was annotated with the Annotation Compass; Select one or more specific targets and return a list of all labels that include these targetsselect one or more specific users and return a list of all labels from these users."
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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": 9,
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"id": "e8d7824d-4523-46f7-b89f-0e8f2d98e564",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# hei kamo! is it already in the flask? should be?\n",
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"# (combined with html_tag_list)\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def individual_map_list(labels: list, users: list ) -> list: \n",
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" \n",
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" filtered_map = []\n",
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" for label in labels:\n",
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" for user in users:\n",
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" if label['userID'] == user:\n",
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" filtered_map.append(label)\n",
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" return filtered_map\n",
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"\n",
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"#individual_map_list(data_json['labels'], ['5058763759', '5941298752'])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0f3febed-e702-4585-a7a1-e62d1a16d1c0",
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"metadata": {},
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"source": [
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"Target Map:\n",
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"Give a string with the name of the image-file that was annotated with the Annotation Compass; Select one or more specific targets and return a list of all labels that include these targets"
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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": 7,
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"id": "9d263750-bab0-4989-9074-a58eba21b2c5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# (combined with html_tag_list)\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def target_map_list(labels: list, targets: list ) -> list: \n",
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" \n",
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" filter_map = []\n",
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" for label in labels:\n",
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" for target in targets:\n",
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" if target in label['text']:\n",
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" filter_map.append(label)\n",
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" return filter_map\n",
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"\n",
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"#target_map_list(data_json['labels'], ['tunnel', 'happy'])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a8e5a256-b9e6-4f0f-b395-690c36d88a7e",
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"metadata": {},
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"source": [
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"Vernacular Map:\n",
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"Give a string with the name of the image-file that was annotated with the Annotation Compass; Return a string that includes all annotation-texts plus html-tags that place them back into their original position."
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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": 8,
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"id": "d78dca69-5f1e-408d-85b5-6cc594f2f875",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function for the project!\n",
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"# please, kamo, put it in the flask app! thxxxx\n",
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"# this function links to jian.css\n",
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"\n",
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"url = \"https://hub.xpub.nl/soupboat/generic-labels/get-labels/?image=rejection_map.jpg/\"\n",
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"response = urlopen(url)\n",
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"data_json = json.loads(response.read()) \n",
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"\n",
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"def vernacular_map_list(labels: list) -> str: \n",
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"\n",
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" filtered_map = '<link rel=\"stylesheet\" href=\"/soupboat/si16-app/static/css/jian.css\">'\n",
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" for label in labels:\n",
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" html_tag = f'<p style=\"left: {label[\"position\"][\"x\"]}%; top: {label[\"position\"][\"y\"]}%; position: absolute;\">{ label[\"text\"] }</p>'\n",
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" filtered_map = filtered_map + html_tag\n",
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" \n",
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" return filtered_map\n",
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"\n",
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"#vernacular_map_list(data_json['labels'])"
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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": null,
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"id": "6a207852-701e-48ef-8469-96c245aea6a4",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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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": "3.7.3"
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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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