Are you sure you want to delete this task? Once this task is deleted, it cannot be recovered.
huolongshe c47851911b | 2 months ago | |
---|---|---|
app | 10 months ago | |
demo_data | 10 months ago | |
docs | 10 months ago | |
.gitignore | 10 months ago | |
Dockerfile | 10 months ago | |
LICENSE | 10 months ago | |
README.md | 2 months ago | |
application.yml | 10 months ago | |
build-docker.sh | 10 months ago | |
pack_model.py | 10 months ago | |
pip-install-reqs.sh | 10 months ago | |
requirements.txt | 9 months ago | |
run_model_server.py | 10 months ago |
图像画质损伤分析模型分析输入图像,输出常见画质损伤的各维度客观评分,包括清晰度评估、点状噪声水平评估、压缩噪声水平评估。
本模型采用resnet50结构,使用图片网站 pexels 中最受欢迎的 130,000 张图片作为训练集,通过模拟各种降质来训练模型对清晰度、点状噪声、压缩噪声的评估。
模型来源:
https://www.modelscope.cn/models/damo/cv_resnet50_image-quality-assessment_degradation/summary
引用:
@inproceedings{wang2021rich,
title={Rich features for perceptual quality assessment of UGC videos},
author={Wang, Yilin and Ke, Junjie and Talebi, Hossein and Yim, Joong Gon and Birkbeck, Neil and Adsumilli, Balu and Milanfar, Peyman and Yang, Feng},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={13435--13444},
year={2021}
}
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": "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": [<results>, <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": "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)AI处理结果的base64编码压缩图像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: 同API接口1
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: 同API接口1
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》