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462 lines
17 KiB
JavaScript
462 lines
17 KiB
JavaScript
Blockly.Msg["UGJ_DRAW_GRIDEYEDATA_TITLE"] = "赤外線アレイセンサ画像表示 %1 温度データ %2 温度範囲上限 %3 %4 温度範囲下限 %5 %6";
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Blockly.Msg["UGJ_DRAW_GRIDEYEDATA_TOOLTIP"] = "AMG8833の温度データを、画像としてキャンバスに描画します。「着色」をチェックすると、温度範囲で設定されている色をつけて表示します。";
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Blockly.Msg["UGJ_GRIDEYE_INIT_TITLE"] = "赤外線アレイセンサ(アドレス: %1 )を初期化";
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Blockly.Msg["UGJ_GRIDEYE_INIT_TOOLTIP"] = "赤外線アレイセンサ AMG8833 の使用準備をします。";
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Blockly.Msg["UGJ_GRIDEYE_THERMISTOR_TITLE"] = "赤外線アレイセンサ本体温度";
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Blockly.Msg["UGJ_GRIDEYE_THERMISTOR_TOOLTIP"] = "AMG8833に内蔵されたサーミスタ(温度センサ)の値を取得します。";
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Blockly.Msg["UGJ_GRIDEYE_READ_TITLE"] = "赤外線アレイセンサの値";
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Blockly.Msg["UGJ_GRIDEYE_READ_TOOLTIP"] = "AMG8833から読み取った温度データを、8x8の配列で取得します。";
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Blockly.Msg["UGJ_GRIDEYE_STOP_TITLE"] = "赤外線アレイセンサから切断";
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Blockly.Msg["UGJ_GRIDEYE_STOP_TOOLTIP"] = "センサーとの接続を停止します。";
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Blockly.Msg["UGJ_GRIDEYE_CANVAS_CREATE_TITLE"] = "赤外線アレイセンサデータ表示キャンバスを作成";
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Blockly.Msg["UGJ_GRIDEYE_CANVAS_CREATE_TOOLTIP"] = "ディスプレイエリアにAMG8833データ表示用キャンバスを作成します。";
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Blockly.Msg["UGJ_TEACHABLE_MACHINE_TITLE"] = "TensorFlow.jsによる画像分類器の準備";
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Blockly.Msg["UGJ_TEACHABLE_MACHINE_TOOLTIP"] = "TensorFlow.jsにMobileNet, KNN Classifierを読み込んで、画像認識(分類)を行う準備をします。";
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Blockly.Msg["UGJ_GRIDEYE_PREDICT_CLASS_TITLE"] = "赤外線アレイセンサの画像で推論を行う";
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Blockly.Msg["UGJ_GRIDEYE_PREDICT_CLASS_TOOLTIP"] = "キャンバスに表示されたAMG8833の画像を元に画像分類の推論を行います。推論の結果として定義済みのラベルを返します。";
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Blockly.Msg["UGJ_GRIDEYE_ADD_EXAMPLE_TITLE"] = "赤外線アレイセンサの画像にラベル %1 をつけてデータセットへ追加";
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Blockly.Msg["UGJ_GRIDEYE_ADD_EXAMPLE_TOOLTIP"] = "キャンバスに表示されているAMG8833の画像にラベル(クラス名)をつけてデータセットへ追加します。";
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Blockly.Msg["UGJ_TENSORSET_STRINGIFY_TITLE"] = "学習したクラスデータセットを文字列に変換";
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Blockly.Msg["UGJ_TENSORSET_STRINGIFY_TOOLTIP"] = "学習したクラスデータセットを文字列に変換して保存します。";
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Blockly.Msg["UGJ_TENSORSET_PARSE_TITLE"] = "クラスデータ文字列 %1 を画像分類器にセット";
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Blockly.Msg["UGJ_TENSORSET_PARSE_TOOLTIP"] = "JSONテキストをパースして画像分類器に戻します。";
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/******************* */
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/** Init Grid-Eye ** */
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/******************* */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_init",
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"message0": "%{BKY_UGJ_GRIDEYE_INIT_TITLE}",
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"args0": [
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{
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"type": "field_dropdown",
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"name": "addr",
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"options": [
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[
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"0x68",
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"0x68"
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],
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[
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"0x69",
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"0x69"
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]
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]
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}
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],
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"inputsInline": true,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_GRIDEYE_INIT_TOOLTIP}",
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"helpUrl": "",
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"style": "sensor_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_init'] = function (block, generator) {
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var dropdown_addr = block.getFieldValue('addr');
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Blockly.JavaScript.provideFunction_(
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'require_amg8833', [`const _amg8833 = require('@ocoge/amg8833');`]
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);
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var code = `await _amg8833.init(_rg, ${apptool.i2c_bus}, ${dropdown_addr});\n`;
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return code;//
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};
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/********************** */
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/** Grid-Eye 本体温度 ** */
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/********************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_thermistor",
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"message0": "%{BKY_UGJ_GRIDEYE_THERMISTOR_TITLE}",
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"output": "Number",
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"tooltip": "%{BKY_UGJ_GRIDEYE_THERMISTOR_TOOLTIP}",
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"helpUrl": "",
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"style": "sensor_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_thermistor'] = function (block, generator) {
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var code = `await _amg8833.read_thermistor()`;
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return [code, Blockly.JavaScript.ORDER_NONE];
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};
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/**************************** */
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/** Read Temperature Array ** */
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/**************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_read",
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"message0": "%{BKY_UGJ_GRIDEYE_READ_TITLE}",
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"inputsInline": true,
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"output": "Array",
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"tooltip": "%{BKY_UGJ_GRIDEYE_READ_TOOLTIP}",
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"helpUrl": "",
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"style": "sensor_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_read'] = function (block, generator) {
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var code = 'await _amg8833.read_temp_array()';
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return [code, Blockly.JavaScript.ORDER_ATOMIC];
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};
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/******************* */
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/** Stop Grid-Eye ** */
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/******************* */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_stop",
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"message0": "%{BKY_UGJ_GRIDEYE_STOP_TITLE}",
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"inputsInline": true,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_GRIDEYE_STOP_TOOLTIP}",
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"helpUrl": "",
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"style": "sensor_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_stop'] = function (block, generator) {
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var code = 'await _amg8833.stop();\n';
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return code;
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};
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/***************************** */
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/** GridEye 表示キャンバス作成 ** */
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/***************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_canvas_create",
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"message0": "%{BKY_UGJ_GRIDEYE_CANVAS_CREATE_TITLE}",
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"inputsInline": true,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_GRIDEYE_CANVAS_CREATE_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_canvas_create'] = function (block, generator) {
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var code = `let _grideye_canvas = document.createElement('canvas');
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_grideye_canvas.setAttribute('width', 8);
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_grideye_canvas.setAttribute('height', 8);
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_grideye_canvas.className = 'subdisplay';
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_grideye_canvas.style.width = '160px';
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_grideye_canvas.style.height = '160px';
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_grideye_canvas.id = 'subcanvas';
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document.getElementById('display_area').appendChild(_grideye_canvas);
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_grideye_ctx = _grideye_canvas.getContext('2d', {willReadFrequently: true});
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_grideye_imgData = _grideye_ctx.createImageData(8, 8);
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`;
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return code;
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};
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/********************************************** */
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/** Draw IR Array Data to Image Data ** */
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/********************************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_draw_grideyedata",
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"message0": "%{BKY_UGJ_DRAW_GRIDEYEDATA_TITLE}",
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"args0": [
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{
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"type": "input_dummy"
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},
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{
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"type": "input_value",
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"name": "amg8833data",
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"check": "Array",
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"align": "RIGHT"
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},
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{
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"type": "field_colour",
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"name": "color_high",
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"colour": "#ff0000"
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},
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{
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"type": "input_value",
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"name": "temp_high",
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"check": "Number",
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"align": "RIGHT"
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},
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{
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"type": "field_colour",
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"name": "color_low",
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"colour": "#3333ff"
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},
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{
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"type": "input_value",
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"name": "temp_low",
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"check": "Number",
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"align": "RIGHT"
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}
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],
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"inputsInline": false,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_DRAW_GRIDEYEDATA_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_draw_grideyedata'] = function (block, generator) {
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var value_amg8833data = Blockly.JavaScript.valueToCode(block, 'amg8833data', Blockly.JavaScript.ORDER_ATOMIC);
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var colour_color_high = block.getFieldValue('color_high');
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var value_temp_high = Blockly.JavaScript.valueToCode(block, 'temp_high', Blockly.JavaScript.ORDER_ATOMIC);
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var colour_color_low = block.getFieldValue('color_low');
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var value_temp_low = Blockly.JavaScript.valueToCode(block, 'temp_low', Blockly.JavaScript.ORDER_ATOMIC);
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var functionName = Blockly.JavaScript.provideFunction_(
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'_mapVal',
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['const ' + Blockly.JavaScript.FUNCTION_NAME_PLACEHOLDER_ + ' = (val, inMin, inMax, outMin, outMax) => {',
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`return (val - inMin) * (outMax - outMin) / (inMax - inMin) + outMin;`,
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'}'
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]
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);
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// 温度カラー
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let hr, hg, hb, lr, lg, lb;
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hr = '0x' + colour_color_high.slice(1, 3);
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hg = '0x' + colour_color_high.slice(3, 5);
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hb = '0x' + colour_color_high.slice(5, 7);
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lr = '0x' + colour_color_low.slice(1, 3);
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lg = '0x' + colour_color_low.slice(3, 5);
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lb = '0x' + colour_color_low.slice(5, 7);
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var code = ` const _color_range = [[${lr}, ${hr}], [${lg}, ${hg}], [${lb}, ${hb}]];
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let _grideye_data = ${value_amg8833data};//読み取りブロックを入力に直接接続できるようにする
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for (let raw = 0; raw < _grideye_canvas.height; raw++) {
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for (let col = 0; col < _grideye_canvas.width; col++) {
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for (let rgb = 0; rgb < 3; rgb++) {
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let pixel = ${functionName}(_grideye_data[raw][col], ${value_temp_low}, ${value_temp_high}, _color_range[rgb][0], _color_range[rgb][1]);
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_grideye_imgData.data[((raw * _grideye_canvas.width * 4) + col * 4) + rgb] = pixel;
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}
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_grideye_imgData.data[((raw * _grideye_canvas.width * 4) + col * 4) + 3] = 0xff;
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}
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}
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_grideye_ctx.putImageData(_grideye_imgData, 0, 0);
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`;
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return code;
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};
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/**************************** */
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/** Teachable Machine を開始** */
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/**************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_teachable_machine",
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"message0": "%{BKY_UGJ_TEACHABLE_MACHINE_TITLE}",
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"inputsInline": true,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_TEACHABLE_MACHINE_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_teachable_machine'] = function (block, generator) {
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Blockly.JavaScript.provideFunction_(
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'require_ts', [`const _tf = require('@tensorflow/tfjs-node');`]
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);
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Blockly.JavaScript.provideFunction_(
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'require_mobilenet', [`const _mobilenet = require('@tensorflow-models/mobilenet');`]
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);
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Blockly.JavaScript.provideFunction_(
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'require_knn', [`const _knnClassifier = require('@tensorflow-models/knn-classifier');`]
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);
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var code = ` const _net = await _mobilenet.load({ version: 1, alpha: 0.25 }); // 高速・低精度
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const _classifier = _knnClassifier.create();
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`;
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return code;
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};
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/************************* */
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/** GridEye で推論を行う ** */
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/************************* */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_predict_class",
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"message0": "%{BKY_UGJ_GRIDEYE_PREDICT_CLASS_TITLE}",
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"inputsInline": true,
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"output": "Number",
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"tooltip": "%{BKY_UGJ_GRIDEYE_PREDICT_CLASS_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_predict_class'] = function (block, generator) {
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var functionName = Blockly.JavaScript.provideFunction_( // left output にするための関数化
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'_predictClass',
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[
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`if (_confidence === undefined) var _confidence;`,
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`const ${Blockly.JavaScript.FUNCTION_NAME_PLACEHOLDER_} = async (img, clsfr, mblnet) => {`,
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`if (clsfr.getNumClasses() > 0) {`,
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`const result = await clsfr.predictClass(mblnet.infer(img, 'conv_preds'));`,
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`_confidence = result.confidences[result.label];`,
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`return result.label;`,
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`}`,
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`else return 0;`,
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`}`
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]
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);
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var code = `await ${functionName}(_grideye_canvas, _classifier, _net)`;
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return [code, Blockly.JavaScript.ORDER_NONE];
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};
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/******************************************** */
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/** ラベルをつけて Example をデータセットに追加 ** */
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/******************************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_grideye_add_example",
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"message0": "%{BKY_UGJ_GRIDEYE_ADD_EXAMPLE_TITLE}",
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"args0": [
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{
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"type": "input_value",
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"name": "class_id",
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"check": "Number"
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}
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],
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"inputsInline": true,
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_GRIDEYE_ADD_EXAMPLE_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_grideye_add_example'] = function (block, generator) {
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var value_class_id = Blockly.JavaScript.valueToCode(block, 'class_id', Blockly.JavaScript.ORDER_ATOMIC);
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var code = `_classifier.addExample (_net.infer(_grideye_canvas, true), ${value_class_id});`;
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return code;
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};
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/*************************** */
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/** 学習したクラスを文字列化 ** */
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/*************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_tensorset_stringify",
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"message0": "%{BKY_UGJ_TENSORSET_STRINGIFY_TITLE}",
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"output": null,
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"tooltip": "%{BKY_UGJ_TENSORSET_STRINGIFY_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_tensorset_stringify'] = function (block, generator) {
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var code = `JSON.stringify( Object.entries(_classifier.getClassifierDataset()).map(([label, data])=>[label, Array.from(data.dataSync()), data.shape]) )`;
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return [code, Blockly.JavaScript.ORDER_NONE];
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};
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/***************************************** */
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/** jsonをデータセットに戻して分類器にセット ** */
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/***************************************** */
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_tensorset_parse",
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"message0": "%{BKY_UGJ_TENSORSET_PARSE_TITLE}",
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"args0": [
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{
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"type": "input_value",
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"name": "class_data_json",
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"check": "String"
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}
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],
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"previousStatement": null,
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"nextStatement": null,
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"tooltip": "%{BKY_UGJ_TENSORSET_PARSE_TOOLTIP}",
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"helpUrl": "",
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"style": "multimedia_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_tensorset_parse'] = function (block, generator) {
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var value_class_data_json = Blockly.JavaScript.valueToCode(block, 'class_data_json', Blockly.JavaScript.ORDER_ATOMIC);
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var code = `_classifier.setClassifierDataset( Object.fromEntries( JSON.parse(${value_class_data_json}).map(([label, data, shape])=>[label, _tf.tensor(data, shape)]) ) );`;
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return code;
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};
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// 温度ブロック(ツールボックス上非表示)
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Blockly.defineBlocksWithJsonArray([{
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"type": "ugj_temp",
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"message0": "%1",
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"args0": [
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{
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"type": "field_slider",
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"name": "temp",
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"value": 15,
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"min": 0,
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"max": 40,
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"precision": 1
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}
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],
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"inputsInline": true,
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"output": "Number",
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"tooltip": "",
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"helpUrl": "",
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"style": "math_blocks"
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}]);
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javascript.javascriptGenerator.forBlock['ugj_temp'] = function (block, generator) {
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var number_temp = block.getFieldValue('temp');
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var code = `${number_temp}`;
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return [code, Blockly.JavaScript.ORDER_NONE];
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};
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flyout_contents = flyout_contents.concat([
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{
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"kind": "label",
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"text": "赤外線アレイセンサー(サーマルカメラ)AMG8833",
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"web-line": "4.0",
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"web-line-width": "200"
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},
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{
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"kind": "block",
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"type": "ugj_grideye_init",
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"fields": {
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"addr": "0x69"
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}
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},
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{
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"kind": "block",
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"type": "ugj_grideye_thermistor"
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},
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{
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"kind": "block",
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"type": "ugj_grideye_read"
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},
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{
|
||
"kind": "block",
|
||
"type": "ugj_grideye_stop"
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_grideye_canvas_create"
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_draw_grideyedata",
|
||
"fields": {
|
||
"color_high": "#ff0000",
|
||
"color_low": "#3333ff"
|
||
},
|
||
"inputs": {
|
||
"temp_high": {
|
||
"shadow": {
|
||
"type": "ugj_temp",
|
||
"fields": {
|
||
"temp": "28"
|
||
}
|
||
}
|
||
},
|
||
"temp_low": {
|
||
"shadow": {
|
||
"type": "ugj_temp",
|
||
"fields": {
|
||
"temp": "15"
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_teachable_machine"
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_grideye_predict_class"
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_grideye_add_example",
|
||
"inputs": {
|
||
"class_id": {
|
||
"shadow": {
|
||
"type": "math_number",
|
||
"fields": {
|
||
"NUM": "0"
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_tensorset_stringify"
|
||
},
|
||
{
|
||
"kind": "block",
|
||
"type": "ugj_tensorset_parse"
|
||
}
|
||
]); |