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【feature】 新增webai 接口 例子 测试 review by songym
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‎dist/mapboxgl/iclient-mapboxgl-es6.js

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‎dist/mapboxgl/iclient-mapboxgl-es6.min.js

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‎dist/mapboxgl/iclient-mapboxgl.js

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‎dist/mapboxgl/iclient-mapboxgl.min.js

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‎examples/img/building.png

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‎examples/img/landcover.png

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‎examples/locales/en-US/resources.js

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@@ -87,7 +87,8 @@ window.examplesResources = {
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"vuecomponents_leaflet": "Vue - Leaflet",
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"reactcomponents_mbgl": 'React - MapboxGL',
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"h5components": "H5",
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"template": 'Templates'
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"template": 'Templates',
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"machineLearning": 'Machine Learning'
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},
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"more": {
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"_name": "More>>",
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"title_objectdetection":"Machinelearning Result Overlay(Objectdetection)",
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"title_binaryclassification":"Machinelearning Result Overlay(Binaryclassification)",
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"title_mvt_mapboxgl":"MVT WGS84 (via MapboxGL)",
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"title_binary_classification": "Binary Claasification",
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"title_landcover_classification": "Landcover Claasification",
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"title_object_detection": "Object Detection",
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"text_service_name":"Name",
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"text_service_type":"Type",
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"text_removeResult": "Remove result",
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"text_addPath": "Add path",
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"text_query": "To query",
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"text_analyse": "To anaylse",
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"text_closestFacilitiesService": "Closest Facilities Analysis Service",
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"text_weightField": "Weight field:",
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"text_turnField": "End of the mileage point (Turning field):",

‎examples/locales/zh-CN/resources.js

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"vuecomponents_leaflet": "Vue - Leaflet",
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"reactcomponents_mbgl": 'React - MapboxGL',
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"h5components": "H5",
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"template": '模板'
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"template": '模板',
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"machineLearning": '机器学习'
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}
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},
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"footer": {
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"title_objectdetection":"机器学习结果叠加（目标检测）",
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"title_binaryclassification":"机器学习结果叠加（二元分类）",
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"title_mvt_mapboxgl":"MVT WGS84 (叠加 MapboxGL)",
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"title_binary_classification": "二元分类",
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"title_landcover_classification": "地物分类",
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"title_object_detection": "目标识别",
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"text_service_name":"名称",
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"text_service_type":"类型",
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"text_removeResult": "移除结果",
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"text_addPath": "生成路径",
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"text_query": "查询",
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"text_analyse": "分析",
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"text_closestFacilitiesService": "最近设施分析",
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"text_weightField": "权重字段:",
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"text_turnField": "终止里程点：(转向字段)",

‎examples/mapboxgl/binaryClassification.html

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<!--********************************************************************
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* Copyright© 2000 - 2021 SuperMap Software Co.Ltd. All rights reserved.
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*********************************************************************-->
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<title data-i18n='resources.title_binary_classification'></title>
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<style>
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#predict {
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position: absolute;
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left: 10px;
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top: 10px;
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}
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</style>
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</head>
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<img style="display: none;" class="building" id="tileImg16" src="../img/building.png" alt="">
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<canvas id="data-canvas1" width="640" height="640"></canvas>
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<input type='button' id='predict' class='btn btn-primary' data-i18n="[value]resources.text_analyse"/>
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<script type="text/javascript" include="bootstrap,vue" src="../js/include-web.js"></script>
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<script include="iclient-mapboxgl-vue,mapbox-gl-enhance" src="../../dist/mapboxgl/include-mapboxgl.js"></script>
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<script>
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let img = document.querySelector('#tileImg16');
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let canvas = document.querySelector('#data-canvas1');
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let ctx = canvas.getContext('2d');
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let predictBtn = document.querySelector('#predict');
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ctx.drawImage(img, 0, 0, 640, 640);
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let webMachineLearning = new SuperMap.WebMachineLearning();
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let binaryClassification = new SuperMap.BinaryClassification({ modelUrl: 'http://192.168.11.148:8084/model.json', image: img });
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predictBtn.addEventListener('click', function() {
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webMachineLearning.execute(binaryClassification).then((res) => {
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const { data, width, height } = res;
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const bytes = ctx.getImageData(0, 0, 640, 640);
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for (let i = 0;i < width * height; i++) {
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let j = i * 4;
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let threshold = data[i];
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if (threshold > 0.9) {
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bytes.data[j] = 255;
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bytes.data[j + 1] = 255;
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bytes.data[j + 2] = 0;
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bytes.data[j + 3] = 255;
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}
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}
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ctx.putImageData(bytes, 0, 0);
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});
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});
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</script>
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</body>
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</html>

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