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https://github.com/gbnk0/simple-image-classifier

Simple image classifier microservice using tensorflow and sanic
https://github.com/gbnk0/simple-image-classifier

api classifier image label learning machine sanic simple tensorflow

Last synced: about 2 months ago
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Simple image classifier microservice using tensorflow and sanic

Host: GitHub
URL: https://github.com/gbnk0/simple-image-classifier
Owner: gbnk0
License: mit
Created: 2018-07-18T20:49:51.000Z (about 6 years ago)
Default Branch: master
Last Pushed: 2019-02-04T14:02:47.000Z (over 5 years ago)
Last Synced: 2024-06-23T07:42:39.107Z (3 months ago)
Topics: api, classifier, image, label, learning, machine, sanic, simple, tensorflow
Language: Python
Homepage:
Size: 105 KB
Stars: 25
Watchers: 3
Forks: 8
Open Issues: 4
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

awesome-sanic - Simple-image-classifier - A microservice for image classification, based on tensorflow (Resources / Built with Sanic)

README

        # simple-image-classifier

Simple image classifier microservice using tensorflow

![pipeline status](https://travis-ci.org/gbnk0/simple-image-classifier.svg?branch=master)

![dockerbuild](https://img.shields.io/docker/automated/jrottenberg/ffmpeg.svg)

[![](https://images.microbadger.com/badges/image/gbnk0/simple-image-classifier.svg)](https://microbadger.com/images/gbnk0/simple-image-classifier)

[![](https://images.microbadger.com/badges/version/gbnk0/simple-image-classifier.svg)](https://microbadger.com/images/gbnk0/simple-image-classifier)

[![](https://images.microbadger.com/badges/commit/gbnk0/simple-image-classifier.svg)](https://microbadger.com/images/gbnk0/simple-image-classifier)

[![Codacy Badge](https://api.codacy.com/project/badge/Grade/2541d5b6ddaa48c8a5d834ea03649372)](https://www.codacy.com/app/gbnk0/simple-image-classifier?utm_source=github.com&utm_medium=referral&utm_content=gbnk0/simple-image-classifier&utm_campaign=Badge_Grade)

![python_version](https://img.shields.io/badge/python-3.5%2C3.6-blue.svg)

#### PREREQUISITES FOR LOCAL RUN

- A linux system

- python >= 3.5

#### QUICKSTART GUIDE

##### RUN WITH DOCKER

``` 

docker run -p8080:8080 gbnk0/simple-image-classifier:latest

```

##### LOCAL RUN WITH PYTHON

Go to the app folder:

```

cd app/

pip3 install -r requirements.txt

python3 app.py

```

It will listen on localhost:8080

#### EXAMPLES:

```

cd example-lib/

edit the example.py file with your set of pictures

python3 example.py

```

#### POPULATING DATASET

When you successfully created a dataset using the /datasets endpoint:

One method for populating the new dataset is to copy all your categories folders (dog, cat, fish, people) to the data/{datasetName}/labels/ folder.

#### API DOCUMENTATION:

[![Run in Postman](https://run.pstmn.io/button.svg)](https://documenter.getpostman.com/view/3045659/RWMHM7ir)