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课堂专注度及考试作弊系统、课堂动态点名，情绪识别、表情识别和人脸识别结合

推荐使用下方的扩展项目，我们提供了完整的部署流程和权重链接。

• [PyQt Demo（推荐）]
• [Java 版本]
• [前后端系统（推荐）]

课堂专注度分析

课堂专注度+表情识别

作弊检测

关键点计算方法

转头(probe)+低头(peep)+传递物品(passing)

侧面的传递物品识别

逻辑回归关键点

下载权重

1. [Halpe dataset] (136 keypoints)

Model	Backbone	Detector	Input Size	AP	Speed	Download	Config	Training Log
[Fast Pose]	ResNet50	YOLOv3	256x192	69.0	3.54 iter/s	[Google][Baidu]	[cfg]	[log]

• 放到detection_system/checkpoints

2. Human-ReID based tracking (Recommended)

Currently the best performance tracking model. Paper coming soon.

Getting started

Download [human reid model] and place it into AlphaPose/trackers/weights/.

Then simply run alphapose with additional flag --pose_track

You can try different person reid model by modifing cfg.arch and cfg.loadmodel in ./trackers/tracker_cfg.py.

If you want to train your own reid model, please refer to this [project]

3. Yolo Detector

Download the object detection model manually: yolov3-spp.weights([Google Drive]| [Baidu pan]). Place it into detector/yolo/data.

4. face boxes 预训练权重

[google drive]

• 放到face_recog/weights文件夹下

5. 其他

百度云 提取码：rwtl

人脸识别：dlib_face_recognition_resnet_model_v1.dat

• detection_system/face_recog/weights

人脸对齐：shape_predictor_68_face_landmarks.dat

• detection_system/face_recog/weights

作弊动作分类器：cheating_detector_rfc_kp.pkl

• detection_system/weights

使用

运行setup.py安装必要内容

python setup.py build develop

[windows上安装scipy1.1.0可能会遇到的问题]

运行demo_inference.py

将detection_system设置为source root

使用摄像头运行程序

python demo_inference.py --vis --webcam 0

参考项目

• [人体姿态估计 AlphaPose]
• [头部姿态估计 head-pose-estimation]
• [人脸检测 faceboxes]