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run_model_server.py | 9 months ago |
本模型为图像特征表示提取别模型,使用ViT作为主干网络,输入图像,输出图像的特征表示(image embedding),图像的特征表示可以用于计算两张图片之间的相似程度,从而判断两张图片中的人是不是同一个个体。
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4个API接口:
API接口1:
API端点: /api/data
HTTP方法: POST
HTTP请求体:
{
"action": "add_person"
"args": {
"name": <姓名>,
"img": <压缩图像的base64编码字符串(或其Data URL表示)>
}
}
HTTP响应体:
{
"status": "ok"|"err",
"value": 1(添加人脸成功)|0(图像中无人脸或有多余一个人脸)|-1(已经存在相似人脸)
}
API接口2:
API端点: /api/data
HTTP方法: POST
HTTP请求体:
{
"action": "predict"
"args": {
"img": <压缩图像的base64编码字符串(或其Data URL表示)>
}
}
HTTP响应体:
{
"status": "ok"|"err",
"value": [<识别结果>, <gps信息>, <带姓名标注的base64编码图像URL>]
}
API接口3:
API端点: /api/stream/predict
HTTP方法: POST
HTTP请求体:
<二进制编码的压缩图像字节流>
HTTP响应体:
{
"status": "ok"|"err",
"value": [<识别结果>, <gps信息>, <带姓名标注的base64编码图像URL>]
}
API接口4:
API端点: /api/file/predict
HTTP方法: POST
HTTP请求体:
<用于HTTP文件上传的XHR格式请求体>
HTTP响应体:
{
"status": "ok"|"err",
"value": [<识别结果>, <gps信息>, <带姓名标注的base64编码图像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》