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mixly3/boards/default/micropython_k210_mixgoai/examples/v_Q1PyDqzn1C.mix
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<xml version="Mixly 2.0 Beta11" board="MixGo AI" xmlns="http://www.w3.org/1999/xhtml"><block type="factory_block_notes" id="MR6|kVdI;@K8gV]0L%.6" x="268" y="247"><field name="VALUE">-本地端模型训练</field><next><block type="factory_block_notes" id="V9NMeJSCu8M9eX^}TAAj"><field name="VALUE">1.准备训练物品并录入名称 (理论数量不限,目前只支持英文名)</field><next><block type="factory_block_notes" id="sRV)H/rf:wQ,anSW96?r"><field name="VALUE">2.填写总的训练拍照数量如四个物品每个训练5张总共20并不同角度训练</field><next><block type="factory_block_notes" id="zNlg[@Vhs4_X-M_ApbX="><field name="VALUE">3.保存模型下次直接模型加载,不需要再次训练模型</field><next><block type="factory_block_notes" id="a=(RK_sRK=mB@1x,x.,3"><field name="VALUE">4.运行模型,将返回识别到物品名及置信度</field><next><block type="camera_init" id="xIxN)p5yY9v0={~Y)T=o" inline="true"><value name="key1"><shadow type="mode" id="vyt#cV98tY)c=({mq%t`"><field name="flag">sensor.YUV422</field></shadow></value><value name="key2"><shadow type="size" id="K0y_RHF{.vBVR3;B#6sp"><field 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id="+)!gc)R.v=yV$f9}1,Gf"><field name="VAR">calss</field><field name="TEXT">'name1', 'name2', 'name3', 'name4'</field><next><block type="ailocal_training" id="W40~67KV71D_N9gb%L*b" disabled="true"><value name="calss"><shadow type="factory_block_return" id="@`yXjJj6pT.$IEyn+@Ly"><field name="VALUE">calss</field></shadow></value><value name="sample"><shadow type="math_number" id="|=:bb%#163/03V2.vp?7"><field name="NUM">20</field></shadow></value><value name="save"><shadow type="text" id="#!3pY0w7g4Szs+w86sA."><field name="TEXT">MixPY.ai</field></shadow></value><next><block type="ailocal_loading" id="MP_1kHq+IQK!-[B~AJQ,"><value name="path"><shadow type="text" id="Hzq:Y-gD@+]Zw#{b54):"><field name="TEXT">Cool_AI.ai</field></shadow></value><next><block type="controls_whileUntil" id="gSUbiJ}O([p}eax|VHK:"><field name="MODE">WHILE</field><value name="BOOL"><shadow type="logic_boolean" id="odC#054A+#VN-(DOoQ-,"><field name="BOOL">TRUE</field></shadow></value><statement name="DO"><block 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