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build-docker.sh | 9 months ago | |
pack_model.py | 9 months ago | |
pip-install-reqs.sh | 9 months ago | |
requirements.txt | 9 months ago | |
run_model_server.py | 9 months ago |
检测并识别视频流媒体中所包含的动作。算法内部每连续采样4帧图像后输入到动作检测模型进行检测并返回结果。支持检测的动作:举手、吃喝、吸烟、打电话、玩手机、趴桌睡觉、跌倒、洗手、拍照。
模型来源: https://modelscope.cn/models/damo/cv_ResNetC3D_action-detection_detection2d/summary
本模型基于 ServiceBoot微服务引擎 进行服务化封装,参见: 《CubeAI模型开发指南》
$ sh pip-install-reqs.sh
$ serviceboot start
或
$ python3 run_model_server.py
一键式本地容器化部署和运行,参见: 《CubeAI模型独立部署指南》 或 CubeAI Docker Builder
本模型服务可一键发布至 CubeAI智立方平台 进行共享和部署,参见: 《CubeAI模型发布指南》
本模型提供了1个API接口:
API接口1:
API端点: /api/data
HTTP方法: POST
HTTP请求体:
{
"action": "predict_video",
"args": {
"url": <云端视频流媒体URL, 例如: rtmp://localhost/live/ch1>
}
}
HTTP响应体:
{
"status": "ok"|"err",
"value": <(流媒体当前帧图像)带目标检测标注的base64编码压缩图像URL>
}
No Description
Python Shell Dockerfile Text
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》