使用相機拍照實現(xiàn)圖像識別

首先需要下載節(jié)點 node-red-contrib-tfjs-coco-ssd，下載不上的朋友可以根據(jù)【Node-Red】最新版coco-ssd 1.0.6安裝方法（windows）文章進行安裝。

1、智能識別圖片

使用本地文件的形式對圖像進行識別

• 時間戳（inject）：作為觸發(fā)點節(jié)點
• 文件路徑（file in）：寫入需要識別的圖像路徑，例如：D:\node-redPicture\123.jpeg，在輸出中選擇buffer流
• tf coco ssd：此節(jié)點中，Threshold為分數(shù)閾值（0-1），也可通過傳參msg.scoreThreshold 進行修改；
  Model Url為地址，盡量不要改動，修改為連接不成功的地址后node-red后臺會崩潰；
  Passthru：可以選擇圖片顯示模式；
  Box colour：當(dāng)Passthru中選擇為做過標(biāo)注的圖片，那就需要對標(biāo)注顏色做設(shè)定
  
• msg：在msg節(jié)點中設(shè)置為與調(diào)試輸出相同來查看完整輸出信息
  payload為數(shù)組格式，當(dāng)識別物體為多種時，都可以顯示在數(shù)組中，在數(shù)組中還顯示了標(biāo)注框位置、類型、打分
  image為buffer類型的數(shù)組存放圖片內(nèi)容
  classes為識別類型及數(shù)量
  

2、將識別信息顯示在UI界面

根據(jù)如上輸出的msg，將classes和image 進行輸出。

• base64：需要下載新的節(jié)點node-red-node-base64，并將屬性改為image，實現(xiàn)對msg.image的buffer轉(zhuǎn)為base64進行輸出。
• 識別信息（text）：設(shè)置為{{msg.classes}}實現(xiàn)將識別類型和數(shù)量進行輸出
• template：將保存在msg.image中的base64碼的圖片進行輸出

<img src="data:image/png;base64,{{msg.image}}"/>

3、將使用相機拍攝并智能識別

將文件路徑節(jié)點換成webcam相機節(jié)點即可實現(xiàn)使用相機拍照并智能識別顯示在UI界面。

Webcam節(jié)點：需要下載node-red-contrib-webcam節(jié)點，此節(jié)點支持多個相機的選擇。

4、源碼

包含有使用文件和相機識別的源碼，導(dǎo)入后記得file in節(jié)點中修改文件路徑為自己電腦上的圖片哦。

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