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huolongshe c190747679 | 2 months ago | |
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app | 10 months ago | |
docs | 1 year ago | |
mmgen | 1 year ago | |
webapp | 11 months ago | |
.gitignore | 10 months ago | |
Dockerfile | 1 year ago | |
LICENSE | 1 year ago | |
README.md | 2 months ago | |
application.yml | 11 months ago | |
build-docker.sh | 1 year ago | |
pack_model.py | 1 year ago | |
pip-install-reqs.sh | 10 months ago | |
requirements.txt | 10 months ago | |
run_model_server.py | 1 year ago |
使用 MMGeneration 中的预训练模型 biggan-deep_512x512_cvt_hugging-face_rgb 开发的无条件图像生成应用。
MMGeneration 是一款基于 PyTorch 的强有力的生成模型工具箱,尤其专注于 GAN 模型,它是 OpenMMLab 项目的一部分。
模型下载:
pip3 install openmim==0.3.7
mim install mmgen==0.7.3
mim download mmgen --config biggan-deep_512x512_cvt_hugging-face_rgb --dest model_data
得到:
模型文件: biggan-deep_imagenet1k_512x512_cvt_hugging-face_rgb_20210728_112346-a42585f2.pth
配置文件: biggan-deep_512x512_cvt_hugging-face_rgb.py
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",
"args": {
"sample_model": <样本模型,可选,缺省为:ema>,
"num_samples": <生成样本数,可选,缺省为:6>,
"num_batches": <推理批量数,可选,缺省为:1>,
"nrow": <每行图像数,可选,缺省为:3>,
"padding": <图像间隔像素,可选,缺省为:10>,
}
}
HTTP响应体:
{
"status": "ok"|"err",
"value": [<拼接后的生成图像>]
}
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