Earlier　in　2019,　a　novel　coronavirus　pneumonia　outbreak　occurred　in　most　countries　and　regions　of　the　world.　Thus,　judging　whether　individuals　are　wearing　masks　or　not　has　become　an　important　part　of　entrance　inspection　in　many　places.　In　this　paper,　object　detection　in　Google　Cloud　Platform＇s　AutoML　is　used　to　implement　mask　detection.　1,　000　from　these　2,　000　pictures　are　selected　to　refine　the　dataset　for　training,　including　500　faces　with　masks　and　500　faces　without　masks.　After　training,　the　accuracy　achieves　94%　and　the　map　achieves　97.3%,　which　can　meet　the　requirements　of　practical　application.　What＇s　more,　tflite　is　used　to　deploy　the　model　on　the　edge,　to　realize　the　application　of　the　model　in　the　real　scenes.　©　2021　SPIE.