https://github.com/ngthanhvinh/objtest
A web app which is able to recognize the object in images. (Flask backend, React frontend, Keras, Tensorflow)
https://github.com/ngthanhvinh/objtest
bootstrap4 flask-backend reactjs tensorflow-experiments vgg16
Last synced: 6 months ago
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A web app which is able to recognize the object in images. (Flask backend, React frontend, Keras, Tensorflow)
- Host: GitHub
- URL: https://github.com/ngthanhvinh/objtest
- Owner: ngthanhvinh
- Created: 2019-03-19T03:17:27.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-12-10T16:59:01.000Z (almost 3 years ago)
- Last Synced: 2025-04-04T07:14:20.240Z (6 months ago)
- Topics: bootstrap4, flask-backend, reactjs, tensorflow-experiments, vgg16
- Language: JavaScript
- Homepage:
- Size: 5.47 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 19
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# ObjTest
**ObjTest** is a web app which can predict the object in images (with up to 1000 classes of object).
The app does not prioritize speed and design, it is just a fun and random experiment of mine regarding to the field of machine learning and web development. :laughing:
**Utilizing:**
* [Flask](http://flask.pocoo.org/)
* [ReactJS](https://reactjs.org)
* [Bootstrap](https://getbootstrap.com/)
* [Tensorflow](https://tensorflow.org)
* [VGG16 pre-trained model with the ImageNet dataset](https://neurohive.io/en/popular-networks/vgg16/).
## Quick Overview
## How to run the app locally?
First, clone this repository:
```bash
git clone https://github.com/ngthanhvinh2000/ObjTest
cd ObjTest
```
### Run Flask back-end
From the root, open a terminal window and run the following commands:
```bash
cd backend
pip install -r requirements.txt
python3 server.py
```
The back-end server is hosted at: [http://localhost:5000](http://localhost:5000).
### Run React front-end
From the root, open another terminal window and run the following commands:
```bash
cd frontend
npm install
npm start
```
Access [http://localhost:3000](http://localhost:3000) and enjoy the React app!
### Note
It may take some time to load...