使用TensorFlow服务和Flask部署模型

共13个文件

html：3个

py：2个

jpeg：2个

Python

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使用TensorFlow服务和Flask部署模型关键概念 1. Serve a TensorFlow model with TensorFlow Serving and Docker.<br> 2. Create a web application with Flask to work as an interface to a served model.

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Deploy-Models-with-TensorFlow-Serving-and-Flask-master.zip （13个子文件）

Deploy-Models-with-TensorFlow-Serving-and-Flask-master

app

dog.jpeg 4KB

templates

index.html 471B

show.html 356B

base.html 116B

inference.py 767B

static

dog.jpeg 4KB

pets

variables

variables.index 15KB

variables.data-00000-of-00001 8.72MB

saved_model.pb 3.75MB

__pycache__

inference.cpython-37.pyc 939B

app.py 867B

LICENSE 1KB

README.md 230B

共 13 条

# Deploy-Models-with-TensorFlow-Serving-and-Flask # Key Concepts 1. Serve a TensorFlow model with TensorFlow Serving and Docker.<br> 2. Create a web application with Flask to work as an interface to a served model.

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