Show match candidates
This commit is contained in:
parent
5b13ca1595
commit
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@ -21,13 +21,20 @@ var loading = document.getElementById("loading");
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var load_text = document.getElementById("load-text");
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var isa_card = document.getElementById("isa-card");
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var detail_card = document.getElementById("detail-card");
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var detail = document.getElementById("detail");
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var detail_image = document.getElementById("detail-image");
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var detail_header = document.getElementById("detail-header");
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var detail_qid;
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var candidates = document.getElementById("candidates");
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var checkbox_list = document.getElementsByClassName("isa-checkbox");
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var nearby_lookup = {};
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var isa_labels = {};
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var items_url = "/api/1/items";
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var osm_objects_url = "/api/1/osm";
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var missing_url = "/api/1/missing";
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var hover_circles = [];
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var selected_circles = [];
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var candidate_outline;
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var isa_count = {};
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@ -267,7 +274,7 @@ function build_item_detail(item, tag_or_key_list) {
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var popup = "<p><strong>Wikidata item</strong><br>";
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popup += `<a href="${wd_url}" target="_blank">${item.label}</a> (${item.qid})`;
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if (item.description) {
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popup += `<br>description: ${item.description}`;
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popup += `<br><strong>description</strong><br>${item.description}`;
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}
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if (item.isa_list && item.isa_list.length) {
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popup += "<br><strong>item type</strong>";
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@ -279,17 +286,14 @@ function build_item_detail(item, tag_or_key_list) {
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}
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if (tag_or_key_list && tag_or_key_list.length) {
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popup += "<br><strong>OSM tags/keys to search for</strong>"
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popup += "<br><strong>OSM tags/keys to search for</strong>";
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for (const v of tag_or_key_list) {
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popup += `<br>${v}`;
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}
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}
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if (item.image_list && item.image_list.length) {
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popup += `<br><img class="w-100" src="/commons/${item.image_list[0]}">`;
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}
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if (item.street_address && item.street_address.length) {
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popup += "<br><strong>street address</strong>"
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popup += "<br><strong>street address</strong>";
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popup += `<br>${item.street_address[0]["text"]}`;
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}
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@ -310,7 +314,7 @@ function mouseover(item) {
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item.markers.forEach((marker) => {
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var coords = marker.getLatLng();
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var circle = L.circle(coords, {radius: 25}).addTo(map);
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var circle = L.circle(coords, { radius: 20 }).addTo(map);
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hover_circles.push(circle);
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});
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}
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@ -336,6 +340,19 @@ function close_item_details() {
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circle.removeFrom(map);
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});
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selected_circles = [];
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detail_header.innerHTML = "";
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detail.innerHTML = "";
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candidates.innerHTML = "";
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detail_qid = undefined;
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detail_image.setAttribute("src", "");
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detail_image.classList.add("d-none");
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if (candidate_outline) {
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candidate_outline.removeFrom(map);
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candidate_outline = undefined;
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}
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}
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function mouse_events(marker, qid) {
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@ -348,6 +365,7 @@ function mouse_events(marker, qid) {
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mouseout(item);
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});
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marker.on("click", function () {
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var wd_item = items[qid].wikidata;
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isa_card.classList.add("visually-hidden");
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detail_card.classList.remove("visually-hidden");
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detail_card.classList.add("bg-highlight");
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@ -355,23 +373,76 @@ function mouse_events(marker, qid) {
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item.markers.forEach((marker) => {
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var coords = marker.getLatLng();
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var circle = L.circle(coords, {radius: 25, color: "orange"}).addTo(map);
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var circle = L.circle(coords, { radius: 20, color: "orange" }).addTo(map);
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selected_circles.push(circle);
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});
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window.setTimeout(function() {
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window.setTimeout(function () {
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detail_card.classList.remove("bg-highlight");
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}, 500);
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detail_qid = qid;
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if (wd_item.image_list && wd_item.image_list.length) {
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detail_image.setAttribute("src", `/commons/${wd_item.image_list[0]}`);
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detail_image.classList.remove("d-none");
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} else {
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detail_image.setAttribute("src", "");
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detail_image.classList.add("d-none");
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}
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var item_label = `${wd_item.label} (${wd_item.qid})`;
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detail_header.innerHTML = "";
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detail_header.append(document.createTextNode(item_label));
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var item_tags_url = `/api/1/item/${qid}/tags`;
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axios.get(item_tags_url).then((response) => {
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var tag_or_key_list = response.data.tag_or_key_list;
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var item_detail = build_item_detail(items[qid].wikidata, tag_or_key_list);
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if (response.data.qid != detail_qid) {
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tag_or_key_list = []; // different QID
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}
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var item_detail = build_item_detail(wd_item, tag_or_key_list);
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detail.innerHTML = item_detail;
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if (tag_or_key_list.length == 0) return;
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var item_osm_candidates_url = `/api/1/item/${qid}/candidates`;
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axios.get(item_osm_candidates_url).then((response) => {
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console.log(response.data);
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var bounds = map.getBounds();
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var params = { bounds: bounds.toBBoxString() };
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axios
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.get(item_osm_candidates_url, { params: params })
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.then((response) => {
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if (response.data.qid != detail_qid) return; // different QID
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var nearby = response.data.nearby;
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if (!nearby.length) return;
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var osm_html = "<strong>Possible OSM matches</strong><br>";
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for (const osm of nearby) {
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var span_id = osm.identifier.replace("/", "_");
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nearby_lookup[span_id] = osm;
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osm_html += `<span class="osm-candidate" id="${span_id}"> ${osm.distance.toFixed(
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1
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)}m ${osm.name || "no name"}</span><br>`;
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}
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candidates.innerHTML = osm_html;
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var span_list = document.getElementsByClassName("osm-candidate");
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for (const osm_span of span_list) {
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osm_span.onmouseover = function (e) {
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osm = nearby_lookup[e.target.id];
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if (candidate_outline !== undefined) {
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candidate_outline.removeFrom(map);
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}
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var mapStyle = { fillOpacity: 0, color: "red" };
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var geojson = L.geoJSON(null, { style: mapStyle });
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geojson.addData(osm.geojson);
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geojson.addTo(map);
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candidate_outline = geojson;
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};
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}
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});
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});
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});
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@ -47,14 +47,22 @@
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<div class="card visually-hidden m-2" id="detail-card">
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<div class="card-body">
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<div class="h5 card-title">item detail
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<button type="button" class="btn-close" id="close-detail"></button>
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<div class="h4 card-title">
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<span id="detail-header">item detail</span>
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<button type="button" class="btn-close float-end" id="close-detail"></button>
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</div>
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<div class="row">
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<div class="col">
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<div id="detail"></div>
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</div>
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<div class="col">
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<div id="candidates"></div>
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</div>
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</div>
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</div>
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<img src="" class="card-img-bottom d-none" id="detail-image">
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</div>
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</div>
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<script>
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var start_lat = {{ lat | tojson }};
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379
web_view.py
379
web_view.py
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@ -327,6 +327,7 @@ def get_and_save_item(qid):
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raise
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item.locations = model.location_objects(coords)
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database.session.add(item)
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database.session.commit()
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return item
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@ -375,23 +376,334 @@ def api_osm_objects():
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return jsonify(success=True, objects=objects, duration=t1)
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skip_isa = {13226383, 16686448, 2221906}
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edu = ['Tag:amenity=college', 'Tag:amenity=university', 'Tag:amenity=school',
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'Tag:office=educational_institution']
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tall = ['Key:height', 'Key:building:levels']
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extra_keys = {
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'Q3914': ['Tag:building=school',
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'Tag:building=college',
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'Tag:amenity=college',
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'Tag:office=educational_institution'], # school
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'Q322563': edu, # vocational school
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'Q383092': edu, # film school
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'Q1021290': edu, # music school
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'Q1244442': edu, # school building
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'Q1469420': edu, # adult education centre
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'Q2143781': edu, # drama school
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'Q2385804': edu, # educational institution
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'Q5167149': edu, # cooking school
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'Q7894959': edu, # University Technical College
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'Q47530379': edu, # agricultural college
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'Q11303': tall, # skyscraper
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'Q18142': tall, # high-rise building
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'Q33673393': tall, # multi-storey building
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'Q641226': ['Tag:leisure=stadium'], # arena
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'Q2301048': ['Tag:aeroway=helipad'], # special airfield
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'Q622425': ['Tag:amenity=pub',
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'Tag:amenity=music_venue'], # nightclub
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'Q187456': ['Tag:amenity=pub',
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'Tag:amenity=nightclub'], # bar
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'Q16917': ['Tag:amenity=clinic',
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'Tag:building=clinic'], # hospital
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'Q330284': ['Tag:amenity=market'], # marketplace
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'Q5307737': ['Tag:amenity=pub',
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'Tag:amenity=bar'], # drinking establishment
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'Q875157': ['Tag:tourism=resort'], # resort
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'Q174782': ['Tag:leisure=park',
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'Tag:highway=pedestrian',
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'Tag:foot=yes',
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'Tag:area=yes',
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'Tag:amenity=market',
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'Tag:leisure=common'], # square
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'Q34627': ['Tag:religion=jewish'], # synagogue
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'Q16970': ['Tag:religion=christian'], # church
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'Q32815': ['Tag:religion=islam'], # mosque
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'Q811979': ['Key:building'], # architectural structure
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'Q11691': ['Key:building'], # stock exchange
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'Q1329623': ['Tag:amenity=arts_centre', # cultural centre
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'Tag:amenity=community_centre'],
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'Q856584': ['Tag:amenity=library'], # library building
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'Q11315': ['Tag:landuse=retail'], # shopping mall
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'Q39658032': ['Tag:landuse=retail'], # open air shopping centre
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'Q277760': ['Tag:historic=folly',
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'Tag:historic=city_gate'], # gatehouse
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'Q180174': ['Tag:historic=folly'], # folly
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'Q15243209': ['Tag:leisure=park',
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'Tag:boundary=national_park'], # historic district
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'Q3010369': ['Tag:historic=monument'], # opening ceremony
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'Q123705': ['Tag:place=suburb'], # neighbourhood
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'Q256020': ['Tag:amenity=pub'], # inn
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'Q41253': ['Tag:amenity=theatre'], # movie theater
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'Q17350442': ['Tag:amenity=theatre'], # venue
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'Q156362': ['Tag:amenity=winery'], # winery
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'Q14092': ['Tag:leisure=fitness_centre',
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'Tag:leisure=sports_centre'], # gymnasium
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'Q27686': ['Tag:tourism=hostel', # hotel
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'Tag:tourism=guest_house',
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'Tag:building=hotel'],
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'Q11707': ['Tag:amenity=cafe', 'Tag:amenity=fast_food',
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'Tag:shop=deli', 'Tag:shop=bakery',
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'Key:cuisine'], # restaurant
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'Q2360219': ['Tag:amenity=embassy'], # permanent mission
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'Q27995042': ['Tag:protection_title=Wilderness Area'], # wilderness area
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'Q838948': ['Tag:historic=memorial',
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'Tag:historic=monument'], # work of art
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'Q23413': ['Tag:place=locality'], # castle
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'Q28045079': ['Tag:historic=archaeological_site',
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'Tag:site_type=fortification',
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'Tag:embankment=yes'], # contour fort
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'Q744099': ['Tag:historic=archaeological_site',
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'Tag:site_type=fortification',
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'Tag:embankment=yes'], # hillfort
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'Q515': ['Tag:border_type=city'], # city
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'Q1254933': ['Tag:amenity=university'], # astronomical observatory
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'Q1976594': ['Tag:landuse=industrial'], # science park
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'Q190928': ['Tag:landuse=industrial'], # shipyard
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'Q4663385': ['Tag:historic=train_station', # former railway station
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'Tag:railway=historic_station'],
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'Q11997323': ['Tag:emergency=lifeboat_station'], # lifeboat station
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'Q16884952': ['Tag:castle_type=stately',
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'Tag:building=country_house'], # country house
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'Q1343246': ['Tag:castle_type=stately',
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'Tag:building=country_house'], # English country house
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'Q4919932': ['Tag:castle_type=stately'], # stately home
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'Q1763828': ['Tag:amenity=community_centre'], # multi-purpose hall
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'Q3469910': ['Tag:amenity=community_centre'], # performing arts center
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'Q57660343': ['Tag:amenity=community_centre'], # performing arts building
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'Q163740': ['Tag:amenity=community_centre', # nonprofit organization
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'Tag:amenity=social_facility',
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'Key:social_facility'],
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'Q41176': ['Key:building:levels'], # building
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'Q44494': ['Tag:historic=mill'], # mill
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'Q56822897': ['Tag:historic=mill'], # mill building
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'Q2175765': ['Tag:public_transport=stop_area'], # tram stop
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'Q179700': ['Tag:memorial=statue', # statue
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'Tag:memorial:type=statue',
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'Tag:historic=memorial'],
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'Q1076486': ['Tag:landuse=recreation_ground'], # sports venue
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'Q988108': ['Tag:amenity=community_centre', # club
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'Tag:community_centre=club_home'],
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'Q55004558': ['Tag:service=yard',
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'Tag:landuse=railway'], # car barn
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'Q19563580': ['Tag:landuse=railway'], # rail yard
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'Q134447': ['Tag:generator:source=nuclear'], # nuclear power plant
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'Q1258086': ['Tag:leisure=park',
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'Tag:boundary=national_park'], # National Historic Site
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'Q32350958': ['Tag:leisure=bingo'], # Bingo hall
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'Q53060': ['Tag:historic=gate', # gate
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'Tag:tourism=attraction'],
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'Q3947': ['Tag:tourism=hotel', # house
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'Tag:building=hotel',
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'Tag:tourism=guest_house'],
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'Q847017': ['Tag:leisure=sports_centre'], # sports club
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'Q820477': ['Tag:landuse=quarry',
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'Tag:gnis:feature_type=Mine'], # mine
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'Q77115': ['Tag:leisure=sports_centre'], # community center
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'Q35535': ['Tag:amenity=police'], # police
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'Q16560': ['Tag:tourism=attraction', # palace
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'Tag:historic=yes'],
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'Q131734': ['Tag:amenity=pub', # brewery
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'Tag:industrial=brewery'],
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'Q828909': ['Tag:landuse=commercial',
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'Tag:landuse=industrial',
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'Tag:historic=dockyard'], # wharf
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'Q10283556': ['Tag:landuse=railway'], # motive power depot
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'Q18674739': ['Tag:leisure=stadium'], # event venue
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'Q20672229': ['Tag:historic=archaeological_site'], # friary
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'Q207694': ['Tag:museum=art'], # art museum
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'Q22698': ['Tag:leisure=dog_park',
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'Tag:amenity=market',
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'Tag:place=square',
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'Tag:leisure=common'], # park
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'Q738570': ['Tag:place=suburb'], # central business district
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'Q1133961': ['Tag:place=suburb'], # commercial district
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'Q935277': ['Tag:gnis:ftype=Playa',
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'Tag:natural=sand'], # salt pan
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'Q14253637': ['Tag:gnis:ftype=Playa',
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'Tag:natural=sand'], # dry lake
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'Q63099748': ['Tag:tourism=hotel', # hotel building
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'Tag:building=hotel',
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'Tag:tourism=guest_house'],
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'Q2997369': ['Tag:leisure=park',
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'Tag:highway=pedestrian',
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'Tag:foot=yes',
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'Tag:area=yes',
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'Tag:amenity=market',
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'Tag:leisure=common'], # plaza
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'Q130003': ['Tag:landuse=winter_sports', # ski resort
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'Tag:site=piste',
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'Tag:leisure=resort',
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'Tag:landuse=recreation_ground'],
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'Q4830453': ['Key:office',
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'Tag:building=office'], # business
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}
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skip_isa = {
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13226383,
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16686448,
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2221906,
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2133296, # space (architecture)
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56052926, # building division
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15989253, # part
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9350592, # telecommunications infrastructure
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121359, # infrastructure
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28877, # goods
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2897903, # goods and services
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2995644, # result
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733541, # consequence
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408386, # inference
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3249551, # process
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20937557, # series
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16887380, # group
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28813620, # set
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99527517, # collection entity
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1150070, # change
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1190554, # occurrence
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26907166, # temporal entity
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2425052, # electrical appliance
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931447, # electrical load
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210729, # electrical element
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3749263, # electrical device
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16798631, # equipment
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66310125, # nonbiological component
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22811462, # type of manufactured good
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21146257, # type
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16889133, # class
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||||
1310239, # component
|
||||
337060, # perceptible object
|
||||
581105, # consumer electronics
|
||||
2858615, # electronic machine
|
||||
1183543, # device
|
||||
39546, # tool
|
||||
35825432, # converter
|
||||
11019, # machine
|
||||
8205328, # artificial physical object
|
||||
223557, # physical object
|
||||
35459920, # three-dimensional object
|
||||
488383, # object
|
||||
35120, # entity
|
||||
1454986, # physical system
|
||||
30060700, # scientific object
|
||||
58778, # system
|
||||
6671777, # structure
|
||||
4406616, # concrete object
|
||||
2555640, # cell (architecture)
|
||||
78642244, # closed space
|
||||
1902617, # verblijfsruimte
|
||||
180516, # room ['Key:room']
|
||||
17334923, # location
|
||||
27096213, # geographic entity
|
||||
58416391, # spatial entity
|
||||
58415929, # spatio-temporal entity
|
||||
811979, # architectural structure
|
||||
811430, # human-made geographic feature
|
||||
35145743, # human-made landform
|
||||
27096235, # artificial geographic entity
|
||||
618123, # geographical feature
|
||||
386724, # work
|
||||
15401930, # product
|
||||
102074988, # artificial physical structure
|
||||
15710813, # physical structure
|
||||
1299240, # interior space
|
||||
4830453, # business
|
||||
3563237, # economic unit
|
||||
2198779, # unit
|
||||
7184903, # abstract object
|
||||
43229, # organization
|
||||
16334295, # group of humans
|
||||
16334298, # group of living things
|
||||
61961344, # group of physical objects
|
||||
98119401, # group or class of physical objects
|
||||
106559804, # person or organization
|
||||
24229398, # agent
|
||||
23958946, # individual entity
|
||||
4830453, # business
|
||||
2695280, # technique
|
||||
21162272, # means
|
||||
4026292, # action
|
||||
1914636, # activity
|
||||
372222, # human-readable medium
|
||||
494756, # data
|
||||
42848, # data
|
||||
1166770, # depiction
|
||||
11024, # communication
|
||||
6031064, # information exchange
|
||||
52948, # interaction
|
||||
23009552, # exchange
|
||||
23009675, # transfer
|
||||
22294683, # biological process involved in intraspecies interaction between organisms
|
||||
628858, # workplace
|
||||
1228250, # line
|
||||
211548, # locus
|
||||
36161, # set
|
||||
864377, # multiset
|
||||
246672, # mathematical object
|
||||
5469988, # formalization
|
||||
4393498, # representation
|
||||
930933, # relation
|
||||
217594, # class
|
||||
294440, # public space
|
||||
7551384, # social space
|
||||
83493482, # thanking
|
||||
83492918, # acknowledgement
|
||||
628523, # message
|
||||
11028, # information
|
||||
189970, # social status
|
||||
11424100, # status
|
||||
4897819, # role
|
||||
1207505, # quality
|
||||
937228, # property
|
||||
11862829, # academic discipline
|
||||
1047113, # specialty
|
||||
9081, # knowledge
|
||||
104127086, # memory
|
||||
12488383, # content
|
||||
2434238, # heritage
|
||||
23893363, # heritage
|
||||
82821, # tradition
|
||||
251777, # custom
|
||||
1299714, # habit
|
||||
36529775, # habit
|
||||
7302601, # recognition
|
||||
}
|
||||
skip_tags = {"Key:addr:street"}
|
||||
|
||||
def get_items(item_ids):
|
||||
items = []
|
||||
for item_id in item_ids:
|
||||
item = model.Item.query.get(item_id)
|
||||
if not item:
|
||||
print(f"get Q{item_id}")
|
||||
if not get_and_save_item(f"Q{item_id}"):
|
||||
continue
|
||||
item = model.Item.query.get(item_id)
|
||||
items.append(item)
|
||||
|
||||
return items
|
||||
|
||||
def get_item_tags(item):
|
||||
isa_items = []
|
||||
isa_list = [v["numeric-id"] for v in item.get_claim("P31")]
|
||||
isa_items = model.Item.query.filter(model.Item.item_id.in_(isa_list)).all()
|
||||
isa_items = get_items(isa_list)
|
||||
|
||||
osm_list = set()
|
||||
seen = set(isa_list) | skip_isa
|
||||
while isa_items:
|
||||
isa = isa_items.pop()
|
||||
if not isa:
|
||||
continue
|
||||
osm = [v for v in isa.get_claim("P1282") if v not in skip_tags]
|
||||
if isa.qid in extra_keys:
|
||||
osm += extra_keys[isa.qid]
|
||||
|
||||
print(isa.qid, isa.label(), osm)
|
||||
osm_list.update(osm)
|
||||
|
||||
subclass_of = [v["numeric-id"] for v in isa.get_claim("P279")]
|
||||
subclass_of = [v["numeric-id"] for v in (isa.get_claim("P279") or []) if v]
|
||||
isa_list = [isa_id for isa_id in subclass_of if isa_id not in seen]
|
||||
seen.update(isa_list)
|
||||
isa_items += model.Item.query.filter(model.Item.item_id.in_(isa_list)).all()
|
||||
isa_items += get_items(isa_list)
|
||||
return sorted(osm_list)
|
||||
|
||||
|
||||
|
|
@ -404,59 +716,80 @@ def api_get_item_tags(item_id):
|
|||
return jsonify(success=True, qid=item.qid, tag_or_key_list=osm_list, duration=t1)
|
||||
|
||||
|
||||
def get_tag_filter(item):
|
||||
osm_list = get_item_tags(item)
|
||||
def get_tag_filter(cls, tag_list):
|
||||
tag_filter = []
|
||||
for tag_or_key in osm_list:
|
||||
for tag_or_key in tag_list:
|
||||
if tag_or_key.startswith("Key:"):
|
||||
tag_filter.append(model.Polygon.tags.has_key(tag_or_key[4:]))
|
||||
tag_filter.append(cls.tags.has_key(tag_or_key[4:]))
|
||||
if tag_or_key.startswith("Tag:"):
|
||||
k, _, v = tag_or_key.partition("=")
|
||||
tag_filter.append(model.Polygon.tags[k] == v)
|
||||
tag_filter.append(cls.tags[k[4:]] == v)
|
||||
|
||||
return or_(*tag_filter)
|
||||
return tag_filter
|
||||
|
||||
def get_nearby(bbox, item, max_distance=200):
|
||||
db_bbox = make_envelope(bbox)
|
||||
|
||||
def get_nearby(item, max_distance=100):
|
||||
osm_objects = {}
|
||||
distances = {}
|
||||
tag_filter = get_tag_filter(item)
|
||||
tag_list = get_item_tags(item)
|
||||
if not tag_list:
|
||||
return []
|
||||
|
||||
for loc in item.locations:
|
||||
lat, lon = loc.get_lat_lon()
|
||||
point = func.ST_SetSRID(func.ST_MakePoint(lon, lat), 4326)
|
||||
for cls in model.Point, model.Line, model.Polygon:
|
||||
tag_filter = get_tag_filter(cls, tag_list)
|
||||
dist = func.ST_Distance(point, cls.way.cast(Geography(srid=4326)))
|
||||
|
||||
dist = func.ST_Distance(point, model.Polygon.way.cast(Geography()))
|
||||
|
||||
q = (model.Polygon.query
|
||||
.add_columns(dist.label('distance'))
|
||||
.filter(dist < max_distance, tag_filter)
|
||||
.order_by(point.distance_centroid(model.Polygon.way))
|
||||
q = (cls.query.add_columns(dist.label('distance'))
|
||||
.filter(
|
||||
func.ST_Intersects(db_bbox, cls.way),
|
||||
func.ST_Area(cls.way) < 20 * func.ST_Area(db_bbox),
|
||||
or_(*tag_filter))
|
||||
.order_by(point.distance_centroid(cls.way))
|
||||
.limit(20))
|
||||
|
||||
# print(q.statement.compile(compile_kwargs={"literal_binds": True}))
|
||||
|
||||
for i, dist in q:
|
||||
if dist > max_distance:
|
||||
continue
|
||||
osm_objects.setdefault(i.identifier, i)
|
||||
if i.identifier not in distances or dist < distances[i.identifier]:
|
||||
distances[i.identifier] = dist
|
||||
|
||||
return [(osm_objects[identifier], dist)
|
||||
nearby = [(osm_objects[identifier], dist)
|
||||
for identifier, dist
|
||||
in sorted(distances.items(), key=lambda i:i[1])]
|
||||
|
||||
return nearby[:10]
|
||||
|
||||
|
||||
@app.route("/api/1/item/Q<int:item_id>/candidates")
|
||||
def api_find_osm_candidates(item_id):
|
||||
bounds = request.args.get("bounds")
|
||||
|
||||
t0 = time()
|
||||
item = model.Item.query.get(item_id)
|
||||
max_distance = 100
|
||||
nearby = []
|
||||
for osm, dist in get_nearby(item, max_distance):
|
||||
for osm, dist in get_nearby(bounds, item):
|
||||
tags = osm.tags
|
||||
name = osm.name or tags.get("addr:housename")
|
||||
if not name and "addr:housenumber" in tags and "addr:street" in tags:
|
||||
name = tags["addr:housenumber"] + " " + tags["addr:street"]
|
||||
|
||||
cur = {
|
||||
"identifier": osm.identifier,
|
||||
"distance": dist,
|
||||
"tags": osm.tags,
|
||||
"area": osm.area,
|
||||
"name": name,
|
||||
"tags": tags,
|
||||
"geojson": osm.geojson(),
|
||||
}
|
||||
if hasattr(osm, 'area'):
|
||||
cur["area"] = osm.area
|
||||
|
||||
nearby.append(cur)
|
||||
|
||||
t1 = time() - t0
|
||||
|
|
|
|||
Loading…
Reference in a new issue