HungLV package
Project description
[GreenLab] - Libraries
1. Description
This library is built for specific tasks
- Face Recognition Project
- Face Detection
- Extract Face Embedding
- Search Face in database
- License Plate Recognition Project
Documentation: https://leviethung2103.github.io/
Pypi Project: https://pypi.org/project/greenlab-library/
2. Table of Contents
- Setup guide
- Usage
- Examples
- APIs
- References
3. Setup guide
3.1 System requirements
- Python>=3.6
- CUDA==10.0
- MXNet
- Tensorflow
- Keras==2.2.0
3.2 Installation
Create a new virtual environment, you can choose virtualenv
or anaconda
.
Virtualenv
python3 -m venv venv
source venv/bin/activate
Anaconda
# create environment
conda create --name face_recog_test python=3.6
conda activate face_recog_test
Install packages and dependencies
# install dependencies for cpu
pip install -r requirements-cpu.txt
# or install dependencies for gpu
pip install -r requirements-gpu.txt
# install face recognition library
pip install --upgrade greenlab-library
4. Usage
4.1 Face Recognition Library
Documentation: https://leviethung2103.github.io/pkg/face_recognition.html
Getting started code: https://github.com/leviethung2103/face-recognition-baseline
git clone https://github.com/leviethung2103/face-recognition-baseline
python main.py
4.2 License Plate Library
Documentation: https://leviethung2103.github.io/pkg/license_recog.html
Getting started code: https://github.com/leviethung2103/license-plate-baseline
5. APIs
6. References
7. Maintainers
Author: Hung Le Viet
Last Update: July 14, 2020
Updates
[Jul 9]
Initial version[Jul 13]
Make the models can run on GPU/CPU. Integratedrcnn
library.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for greenlab_library-0.1.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | be51ddc2f0cf88b12c9492b7b350256a1107f34abd92bab39d9230ecb830e714 |
|
MD5 | 0f1c72596946539910b0ac50895b2e4e |
|
BLAKE2b-256 | 1b1baf7003adfaf2a875e8074432e056bd299a23f12236ef37bbb6495b34c3dc |