Created
September 9, 2018 08:49
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顔認識するやつ
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<canvas id="canvas" width="640" height="480"></canvas> | |
<script> | |
const img = new Image; | |
img.src = "lena.png"; | |
let ctx; | |
let arr; | |
img.onload = () => { | |
ctx = canvas.getContext("2d"); | |
ctx.drawImage(img, 0, 0); | |
arr = ctx.getImageData(0, 0, 640, 480).data; | |
}; | |
const fugafuga = new Uint8Array(640 * 480); | |
</script> | |
<script src="opencv.js"></script> | |
<script> | |
cv.onRuntimeInitialized = async () => { | |
const fileName = "haarcascade_frontalface_default.xml"; | |
const frontalface = new Uint8Array(await fetch(fileName).then(res => res.arrayBuffer())); | |
cv.FS_createDataFile("/", fileName, frontalface, true, true); | |
const classifier = new cv.CascadeClassifier(); | |
classifier.load(fileName); | |
const frame = cv.imread("canvas"); | |
const grayFrame = new cv.Mat(); | |
cv.cvtColor(frame, grayFrame, cv.COLOR_RGBA2GRAY); | |
cv.equalizeHist(grayFrame, grayFrame); | |
const faces = new cv.RectVector(); | |
classifier.detectMultiScale(grayFrame, faces, 1.1, 3); | |
const box = faces.get(0); | |
ctx.rect(box.x, box.y, box.width, box.height); | |
ctx.stroke(); | |
}; | |
</script> |
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