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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 1 month 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 (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-02-04T14:02:47.000Z (almost 6 years ago)
- Last Synced: 2024-08-03T22:15:58.117Z (4 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)