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| # AI分析看电视行为 | ||
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| <img src="https://enpei-md.oss-cn-hangzhou.aliyuncs.com/imgIMG_6178.PNG?x-oss-process=style/wp" style="width:300px;" /> | ||
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| #### 一、功能： | ||
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| * 人脸识别：检查谁在看 | ||
| * 头部姿态估计：检查是否在看 | ||
| * 距离估计：检查是否离电视太近 | ||
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| #### 二、硬件： | ||
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| * Windows10或11（无需GPU）或MacOS 都测试可行 | ||
| * 普通RBG USB摄像头 | ||
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| #### 三、软件： | ||
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| * python 3.7.10 | ||
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| `pip`安装一下依赖包 | ||
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| ``` | ||
| dlib | ||
| opencv-contrib-python（可能需要先卸载opencv-python：pip uninstall opencv-python） | ||
| ``` | ||
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| #### 四、使用方法： | ||
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| `python demo.py --命令=参数` | ||
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| ``` | ||
| -h, --help 显示帮助 | ||
| --mode MODE 运行模式：collect,train,distance,run对应：采集、训练、评估距离、主程序 | ||
| --label_id LABEL_ID 采集照片标签id. | ||
| --img_count IMG_COUNT | ||
| 采集照片数量 | ||
| --img_interval IMG_INTERVAL | ||
| 采集照片间隔时间 | ||
| --display DISPLAY 显示模式，取值1-5 | ||
| --w W 画面宽度 | ||
| --h H 画面高度 | ||
| ``` | ||
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| ##### 4.1 自定义人脸识别照片 | ||
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| 项目使用最简单的opencv内置的人脸识别算法（精度有限），需要识别自己的人脸请按以下步骤： | ||
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| 1. **采集照片：**`python demo.py --mode='collect' --label_id={人脸ID} --img_count={该ID采集照片数量，一般1-3张即可} --img_interval={照片采集间隔（秒）}； ` | ||
| 2. **修改label：**修改`./face_mode/label.txt`文件，每行代表一个人，如`1,恩培`表示`label_id=1`的人脸叫恩培； | ||
| 3. **训练模型：**`python demo.py --mode='train'`训练人脸识别模型，模型是`./face_model/model.yml`； | ||
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| ##### 4.2 设置距离参数 | ||
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| 项目使用相似三角形原理估算（`f`为相机焦距）： | ||
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| <img src="https://enpei-md.oss-cn-hangzhou.aliyuncs.com/img20211226120754.png?x-oss-process=style/wp" style="width:600px;" /> | ||
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| 公式中的`a`取值为人眼角像素距离，参数在`demo.py`第27行`self.eyeBaseDistance = 65`，如果觉得距离不准，请修正这个参数，运行`python demo.py --mode='distance'`，保持相机和人眼睛高度一样，距离相机1.5m处。 | ||
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| ##### 4.3 主程序 | ||
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| `python demo.py --mode='run' --w={宽度} --{高度} --display={显示模式}`，`display`取值对应： | ||
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| * 1：人脸框 | ||
| * 2：68个人脸关键点 | ||
| * 3：人脸梯形框框 | ||
| * 4：人脸方向指针 | ||
| * 5：人脸三维坐标系 | ||
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