https://github.com/xd-deng/flask-app-for-mxnet-img-classifier

A Flask (Python) Web Interface for MXNet Image Classifier
https://github.com/xd-deng/flask-app-for-mxnet-img-classifier

Last synced: 3 months ago
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A Flask (Python) Web Interface for MXNet Image Classifier

• Host: GitHub
• URL: https://github.com/xd-deng/flask-app-for-mxnet-img-classifier
• Owner: XD-DENG
• Created: 2017-07-09T05:13:01.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T02:57:30.000Z (about 2 years ago)
• Last Synced: 2024-10-04T18:23:52.350Z (3 months ago)
• Language: Python
• Homepage:
• Size: 353 KB
• Stars: 53
• Watchers: 7
• Forks: 23
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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README

        
# Image Classifier Written with MXNet + Flask







A Flask (Python) Web Interface for [MXNet](http://mxnet.io/) Image Classifier.

This app simply invoked the [pre-trained model](http://mxnet.io/tutorials/python/predict_image.html) provided by MXNet community. 

## Deployment Using Docker

```bash

docker run -p 8000:8000 xddeng/flask-app-for-mxnet-img-classifier:v2

```

Now you can try to access the service at http://localhost:8000

## Deployment

### Step - 1: Environment

```bash

sudo yum install python-pip

sudo yum install git

sudo yum install numpy opencv*

pip install Flask

pip install mxnet

pip install gunicorn

```

### Step - 2: Clone This Project

```bash

git clone https://github.com/XD-DENG/flask-app-for-mxnet-img-classifier.git

```

### Step - 3: Download Pre-Trained MXNet Model

From http://data.mxnet.io/models/imagenet-11k/, download

- resnet-152/resnet-152-symbol.json

- resnet-152/resnet-152-0000.params

- synset.txt

Note that we need to put all these three files under application directory.

### Step - 4: Start Service

```bash

gunicorn -b 0.0.0.0:80 app:app

```