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VideoFaceRecognition.vue
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VideoFaceRecognition.vue
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<script setup>
import * as faceapi from "@vladmandic/face-api";
import { onMounted, onUnmounted, reactive } from "vue";
/**属性状态 */
const state = reactive({
/**初始化模型加载 */
netsLoadModel: true,
/**算法模型 */
netsType: "ssdMobilenetv1",
/**模型参数 */
netsOptions: {
ssdMobilenetv1: undefined,
tinyFaceDetector: undefined,
},
/**目标图片数据匹配对象 */
faceMatcher: {},
/**目标图片元素 */
targetImgEl: null,
/**目标画布图层元素 */
targetCanvasEl: null,
/**识别视频元素 */
discernVideoEl: null,
/**识别画布图层元素 */
discernCanvasEl: null,
/**绘制定时器 */
timer: 0,
});
/**初始化模型加载 */
async function fnLoadModel() {
// 模型文件访问路径
const modelsPath = `/models`;
// 面部轮廓模型
await faceapi.nets.faceLandmark68Net.load(modelsPath);
// 面部识别模型
await faceapi.nets.faceRecognitionNet.load(modelsPath);
// 模型参数-ssdMobilenetv1
await faceapi.nets.ssdMobilenetv1.load(modelsPath);
state.netsOptions.ssdMobilenetv1 = new faceapi.SsdMobilenetv1Options({
minConfidence: 0.5, // 0 ~ 1
maxResults: 50, // 0 ~ 100
});
// 模型参数-tinyFaceDetector
await faceapi.nets.tinyFaceDetector.load(modelsPath);
state.netsOptions.tinyFaceDetector = new faceapi.TinyFaceDetectorOptions({
inputSize: 416, // 160 224 320 416 512 608
scoreThreshold: 0.5, // 0 ~ 1
});
// 输出库版本
console.log(
`FaceAPI Version: ${
faceapi?.version || "(not loaded)"
} \nTensorFlow/JS Version: ${
faceapi.tf?.version_core || "(not loaded)"
} \nBackend: ${
faceapi.tf?.getBackend() || "(not loaded)"
} \nModels loaded: ${faceapi.tf.engine().state.numTensors} tensors`
);
// 节点元素
state.targetImgEl = document.getElementById("page_draw-img-target");
state.targetCanvasEl = document.getElementById("page_draw-canvas-target");
state.discernVideoEl = document.getElementById("page_draw-video");
state.discernCanvasEl = document.getElementById("page_draw-video-canvas");
// 关闭模型加载
state.netsLoadModel = false;
}
/**根据模型参数识别绘制--目标图 */
async function fnRedrawTarget() {
console.log("Run Redraw Target");
const detect = await faceapi
.detectAllFaces(state.targetImgEl, state.netsOptions[state.netsType])
// 需引入面部轮廓模型
.withFaceLandmarks()
// 需引入面部识别模型
.withFaceDescriptors();
if (!detect.length) {
state.faceMatcher = null;
return;
}
// 原图人脸矩阵结果
state.faceMatcher = new faceapi.FaceMatcher(detect);
// 识别图像绘制
const dims = faceapi.matchDimensions(state.targetCanvasEl, state.targetImgEl);
const resizedResults = faceapi.resizeResults(detect, dims);
resizedResults.forEach(({ detection, descriptor }) => {
const best = state.faceMatcher.findBestMatch(descriptor);
// 目标原图绘制框
new faceapi.draw.DrawBox(detection.box, {
label: best.label,
boxColor: "#55b881",
}).draw(state.targetCanvasEl);
});
}
/**根据模型参数识别绘制 */
async function fnRedrawDiscern() {
if (!state.faceMatcher) return;
console.log("Run Redraw Discern");
// 暂停视频时清除定时
if (state.discernVideoEl.paused) {
clearTimeout(state.timer);
state.timer = 0;
return;
}
// 识别绘制人脸信息
const detect = await faceapi
.detectAllFaces(state.discernVideoEl, state.netsOptions[state.netsType])
// 需引入面部轮廓模型
.withFaceLandmarks()
// 需引入面部识别模型
.withFaceDescriptors();
// 无识别数据时,清除定时重新再次识别
if (!detect) {
clearTimeout(state.timer);
state.timer = 0;
fnRedrawDiscern();
return;
}
// 匹配元素大小
const dims = faceapi.matchDimensions(
state.discernCanvasEl,
state.discernVideoEl,
true
);
const result = faceapi.resizeResults(detect, dims);
result.forEach(({ detection, descriptor }) => {
// 最佳匹配 distance越小越匹配
const best = state.faceMatcher.findBestMatch(descriptor);
// 识别图绘制框
const label = best.toString();
new faceapi.draw.DrawBox(detection.box, { label }).draw(
state.discernCanvasEl
);
});
// 定时器句柄
state.timer = setTimeout(() => fnRedrawDiscern(), 0);
}
/**
* 视频暂停播放
*
* 播放视频,开始识别绘制
*
* 暂停视频,不清除画布
*/
function fnVidelPaused() {
if (state.discernVideoEl.paused) {
state.discernVideoEl.play();
setTimeout(() => fnRedrawDiscern(), 300);
} else {
state.discernVideoEl.pause();
}
}
/**更换图片 */
async function fnChangeTarget(e) {
if (!state.targetImgEl || !state.targetCanvasEl) return;
if (!e.target || !e.target.files.length) return;
// 将文件显示为图像并识别
const img = await faceapi.bufferToImage(e.target.files[0]);
state.targetImgEl.src = img.src;
fnRedrawTarget();
}
/**更换视频 */
function fnChangeDiscern(e) {
if (!state.discernVideoEl || !state.discernCanvasEl) return;
if (!e.target || !e.target.files.length) return;
// 将文件显示为视频并识别
state.discernVideoEl.pause();
state.discernVideoEl.src = URL.createObjectURL(e.target.files[0]);
clearTimeout(state.timer);
state.timer = 0;
setTimeout(() => {
// 清空画布
state.discernCanvasEl
.getContext("2d")
.clearRect(
0,
0,
state.discernCanvasEl.width,
state.discernCanvasEl.height
);
}, 300);
}
onMounted(() => {
fnLoadModel().then(() => fnRedrawTarget());
});
onUnmounted(() => {
clearTimeout(state.timer);
state.timer = 0;
});
</script>
<template>
<div class="page">
<div class="page_option">
<div>
<label>更换目标图片:</label>
<input
type="file"
accept="image/png, image/jpeg"
@change="fnChangeTarget($event)"
/>
</div>
<div>
<label>更换识别视频:</label>
<input
type="file"
accept="video/mp4, video/ogg, video/webm"
@change="fnChangeDiscern($event)"
/>
</div>
<div>
<label>视频媒体:</label>
<button @click="fnVidelPaused()">播放/暂停</button>
</div>
<div>
<label>算法模型:</label>
<select v-model="state.netsType">
<option value="ssdMobilenetv1">SSD Mobilenet V1</option>
<option value="tinyFaceDetector">Tiny Face Detector</option>
</select>
</div>
</div>
<div class="page_load" v-show="state.netsLoadModel">Load Model...</div>
<div class="page_draw" v-show="!state.netsLoadModel">
<h3>识别目标图像:</h3>
<div class="page_draw-target">
<img id="page_draw-img-target" src="/images/cp/cp01.jpg" />
<canvas id="page_draw-canvas-target"></canvas>
</div>
<h3>识别匹配视频:</h3>
<div class="page_draw-discern">
<video
id="page_draw-video"
poster="/images/720x480.png"
src="/videos/test.mp4"
muted
playsinline
></video>
<canvas id="page_draw-video-canvas"></canvas>
</div>
</div>
</div>
</template>
<style scoped></style>