基于CNN的2019-nCov新冠肺炎检测鉴定云平台

• 使用DenseNet网络进行迁移学习，构建新冠肺炎CT影像检测模型。

• 使用GradCam++算法对类激活图进行可视化，了解神经网络决策依据。

• 基于 keras-flask-deploy-webapp 的Flask框架部署网络检测平台。

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Deploy Pytorch Model with Flask as Web App

# 1. First, clone the repo
$ git clone [email protected]:lxysl/covid_web.git

$ cd covid_web

# 2. Install Python packages
$ pip install -r requirements.txt

# please note the torchcam package needs to be installed separately
# for more details, see https://github.com/frgfm/torch-cam/issues/72#issuecomment-943168322
$ pip install git+https://github.com/frgfm/torch-cam.git#egg=torchcam

# 3. Run!
$ python app.py

Open http://localhost:5000 and have fun. 😃

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Run with Docker

With Docker, you can quickly build and run the entire application in minutes 🐳

# 1. First, clone the repo
$ git clone [email protected]:lxysl/covid_web.git
$ cd covid_web

# 2. Build Docker image
$ docker build -t covid_web .

# 3. Run!
$ docker run -it --rm -p 5000:5000 keras_flask_app

Open http://localhost:5000 and wait till the webpage is loaded.

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Dataset - COVIDx CT

Model

The model training file is COVID-19.ipynb.

Performance

More resources

Building a simple Keras + deep learning REST API