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WebRTCFaceDetector.vue
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WebRTCFaceDetector.vue
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<script setup>
import * as faceapi from "@vladmandic/face-api";
import { onMounted, onUnmounted, reactive, watch } 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,
},
/**检测人脸 多或单 */
detectFace: "detectAllFaces",
/**面框分值, 面部轮廓, 面部表情, 年龄性别 */
draws: ["box", "landmark", "expression", "ageGender"],
/**视频元素 */
videoEl: null,
/**画布图层元素 */
canvasEl: null,
/**绘制定时器 */
timer: 0,
/**视频媒体参数配置 */
constraints: {
audio: false,
video: {
/**ideal(应用最理想的) */
width: {
min: 320,
ideal: 720,
max: 1280,
},
height: {
min: 200,
ideal: 480,
max: 720,
},
/**frameRate 受限带宽传输时,低帧率可能更适宜 */
frameRate: {
min: 7,
ideal: 15,
max: 30,
},
/**facingMode 摄像头前后切换 */
facingMode: "environment",
},
},
/**视频流 */
stream: null,
});
/**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);
// 面部表情模型
await faceapi.nets.faceExpressionNet.load(modelsPath);
// 年龄性别模型
await faceapi.nets.ageGenderNet.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: ${faceapi.tf.engine().state.numTensors} tensors`
);
// 节点元素
state.videoEl = document.getElementById("page_draw-video");
state.canvasEl = document.getElementById("page_draw-video-canvas");
// 关闭模型加载
state.netsLoadModel = false;
}
/**根据模型参数识别绘制 */
async function fnRedraw() {
if (!state.videoEl || !state.canvasEl) return;
console.log("Run Redraw");
// 暂停视频时清除定时
if (state.videoEl.paused) {
clearTimeout(state.timer);
state.timer = 0;
return;
}
// 识别绘制人脸信息
const detect = await faceapi[state.detectFace](
state.videoEl,
state.netsOptions[state.netsType]
)
// 需引入面部轮廓模型
.withFaceLandmarks()
// 需引入面部表情模型
.withFaceExpressions()
// 需引入年龄性别模型
.withAgeAndGender();
// 无识别数据时,清除定时重新再次识别
if (!detect) {
clearTimeout(state.timer);
state.timer = 0;
fnRedraw();
return;
}
// 匹配元素大小
const dims = faceapi.matchDimensions(state.canvasEl, state.videoEl, true);
const result = faceapi.resizeResults(detect, dims);
// 面框分值
if (state.draws.includes("box")) {
faceapi.draw.drawDetections(state.canvasEl, result);
}
// 面部轮廓
if (state.draws.includes("landmark")) {
// 需引入面部轮廓模型
faceapi.draw.drawFaceLandmarks(state.canvasEl, result);
}
// 面部表情
if (state.draws.includes("expression")) {
// 需引入面部表情模型
faceapi.draw.drawFaceExpressions(state.canvasEl, result, 0.05);
}
// 年龄性别
if (state.draws.includes("ageGender")) {
// 需引入年龄性别模型模型
const drawItem = (item) => {
const { age, gender, genderProbability } = item;
new faceapi.draw.DrawTextField(
[
`${Math.round(age)} Age`,
`${gender} (${Math.round(genderProbability)})`,
],
item.detection.box.topRight
).draw(state.canvasEl);
};
// 多结果
if (Array.isArray(result)) {
result.forEach((item) => drawItem(item));
} else {
drawItem(result);
}
}
// 定时器句柄
state.timer = setTimeout(() => fnRedraw(), 0);
}
/**启动摄像头视频媒体 */
async function fnOpen() {
if (state.stream !== null) return;
try {
state.stream = {}; // 置为空对象,避免重复点击
const stream = await navigator.mediaDevices.getUserMedia(state.constraints);
state.stream = stream;
state.videoEl.srcObject = stream;
state.videoEl.play();
setTimeout(() => fnRedraw(), 300);
} catch (error) {
state.stream = null; // 置为空,可点击
console.error(error);
alert("视频媒体流获取错误: " + error);
}
}
/**结束摄像头视频媒体 */
function fnClose() {
if (state.stream === null) return;
state.videoEl.pause();
state.videoEl.srcObject = null;
state.stream.getTracks().forEach((track) => track.stop());
state.stream = null;
clearTimeout(state.timer);
state.timer = 0;
setTimeout(() => {
// 清空画布
state.canvasEl
.getContext("2d")
.clearRect(0, 0, state.canvasEl.width, state.canvasEl.height);
}, 500);
}
// 摄像头前后切换 启用时,关闭后重开
watch(
() => state.constraints.video.facingMode,
() => {
if (state.stream !== null) {
fnClose();
fnOpen();
} else {
fnClose();
}
}
);
onMounted(() => {
fnLoadModel();
});
onUnmounted(() => {
fnClose();
});
</script>
<template>
<div class="page">
<div class="page_option">
<div>
<label>摄像头视频媒体:</label>
<button @click="fnOpen()" :disabled="state.stream !== null">
启动
</button>
<button @click="fnClose()">结束</button>
</div>
<div>
<label>前置or后置切换:</label>
<select v-model="state.constraints.video.facingMode">
<option value="user">前置</option>
<option value="environment">后置</option>
</select>
</div>
<div>
<label>面框分值:</label>
<input type="checkbox" value="box" v-model="state.draws" />
</div>
<div>
<label>面部轮廓:</label>
<input type="checkbox" value="landmark" v-model="state.draws" />
</div>
<div>
<label>面部表情:</label>
<input type="checkbox" value="expression" v-model="state.draws" />
</div>
<div>
<label>年龄性别:</label>
<input type="checkbox" value="ageGender" v-model="state.draws" />
</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>
<label>检测人脸:</label>
<select v-model="state.detectFace">
<option value="detectSingleFace">Detect Single Face</option>
<option value="detectAllFaces">Detect All Faces</option>
</select>
</div>
</div>
<div class="page_load" v-show="state.netsLoadModel">Load Model...</div>
<div class="page_draw" v-show="!state.netsLoadModel">
<div class="page_draw" v-show="!state.netsLoadModel">
<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>