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run_model_server.py | 1 year ago |
使用OpenVino的open_model_zoo中的预训练模型 gmcnn-places2-tf 开发的图像修复应用。
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2个API接口:
API接口1:
API端点: /api/data
HTTP方法: POST
HTTP请求体:
{
"action": "predict",
"args": {
"img": <待修复压缩图像的base64编码字符串(或其Data URL表示)>,
"mask_boxes": [<需要修复的矩形框坐标列表>]
}
}
HTTP响应体:
{
"status": "ok"|"err",
"value": <修复好图像的base64编码压缩图像URL>
}
API接口2:
API端点: /api/data
HTTP方法: POST
HTTP请求体:
{
"action": "gen_masked_image",
"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": <随机生成的破损图像的base64编码压缩图像URL>, [<破损图像中需要修复的矩形框坐标列表>]
}
OpenVino图像修复
TypeScript Python HTML Shell Dockerfile other
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