-
Notifications
You must be signed in to change notification settings - Fork 81
/
FaceRecognitionMore.vue
213 lines (194 loc) · 6.32 KB
/
FaceRecognitionMore.vue
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
<script setup>
import * as faceapi from "@vladmandic/face-api";
import { onMounted, 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,
},
/**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,
/**识别图片元素盒子 */
discernCanvasBoxEl: 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.discernCanvasBoxEl = document.getElementById("page_draw-canvas-box");
// 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() {
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(src) {
if (!state.faceMatcher) return;
// 节点对象创建-识别项盒子
const divEl = document.createElement("DIV");
divEl.className = "page_draw-discern";
// 节点对象创建-识别图片
const imgEl = document.createElement("IMG");
imgEl.id = "page_draw-img-discern";
imgEl.src = src;
divEl.appendChild(imgEl);
// 节点对象创建-识别图层
const canvasEl = document.createElement("CANVAS");
canvasEl.id = "page_draw-canvas-discern";
divEl.appendChild(canvasEl);
state.discernCanvasBoxEl.appendChild(divEl);
// 添加虚线
state.discernCanvasBoxEl.appendChild(document.createElement("HR"));
// 识别人脸
const detect = await faceapi
.detectAllFaces(imgEl, 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) return;
// 显示的图层匹配图片尺寸
const dims = faceapi.matchDimensions(canvasEl, imgEl);
const resizedResults = faceapi.resizeResults(detect, dims);
resizedResults.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(canvasEl);
});
}
/**更换图片 */
async function fnChange(e, keyEl) {
if (!e.target || !e.target.files.length) return;
// 清空识别图区
state.discernCanvasBoxEl.innerHTML = "";
if (keyEl === "target") {
const img = await faceapi.bufferToImage(e.target.files[0]);
state.targetImgEl.src = img.src;
fnRedrawTarget().then(() => fnRedrawDiscern(state.targetImgEl.src));
} else {
for (const file of e.target.files) {
const img = await faceapi.bufferToImage(file);
fnRedrawDiscern(img.src);
}
}
}
// 模型变更
watch(
() => state.netsType,
() => {
state.discernCanvasBoxEl.innerHTML = "";
fnRedrawTarget().then(() => fnRedrawDiscern(state.targetImgEl.src));
}
);
onMounted(() => {
fnLoadModel()
.then(() => fnRedrawTarget())
.then(() => fnRedrawDiscern(state.targetImgEl.src));
});
</script>
<template>
<div class="page">
<div class="page_option">
<div>
<label>更换目标图:</label>
<input
type="file"
accept="image/png, image/jpeg"
@change="fnChange($event, 'target')"
/>
</div>
<div>
<label>更换匹配图:</label>
<input
type="file"
accept="image/png, image/jpeg"
multiple="multiple"
@change="fnChange($event, 'discern')"
/>
</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/cp04.jpg" />
<canvas id="page_draw-canvas-target"></canvas>
</div>
<h3>识别匹配图像:</h3>
<div id="page_draw-canvas-box"></div>
</div>
</div>
</template>
<style scoped></style>