📚 Adding readme file

Author: Achraf KHAZRI

README.md

@@ -1,13 +1,51 @@
-# Automatic Number Plate Recognition
+# Automatic License Plate Detection & Recognition using deep learning
+[![Licence](https://img.shields.io/github/license/GuiltyNeuron/ANPR?style=plastic)](https://github.com/GuiltyNeuron/ANPR/blob/master/LICENSE)
+[![Documentation](https://img.shields.io/badge/documentation-TowardsDataScience-blue)](https://towardsdatascience.com/automatic-license-plate-detection-recognition-using-deep-learning-624def07eaaf)
+[![Dataset](https://img.shields.io/badge/Dataset-Kaggle-red)](https://www.kaggle.com/)
+[![Fork](https://img.shields.io/github/forks/GuiltyNeuron/ANPR?style=social)](https://github.com/GuiltyNeuron/ANPR/network/members)
+[![Stars](https://img.shields.io/github/stars/GuiltyNeuron/ANPR?style=social)](https://github.com/GuiltyNeuron/ANPR/stargazers)
+
+In this repos we study number plate detection and recognition using different deep learning models and computer vision approches.
+
+### Licence plate detection using Yolo :
+In order to detect licence we will use Yolo ( You Only Look Once ) deep learning object detection architecture based on convolution neural networks.
+This architecture was introduced by Joseph Redmon , Ali Farhadi, Ross Girshick and Santosh Divvala first version in 2015 and later version 2 and 3.
+
+Yolo v1 : Paper [link](https://arxiv.org/pdf/1506.02640.pdf).
+
+Yolo v2 : Paper [link](https://arxiv.org/pdf/1612.08242.pdf).
+
+Yolo v3 : Paper [link](https://arxiv.org/pdf/1804.02767.pdf).
+
+Yolo is a single network trained end to end to perform a regression task predicting both object bounding box and object class.
+This network is extremely fast, it processes images in real-time at 45 frames per second. A smaller version of the network, Fast YOLO, processes an astounding 155 frames per second.
+
+You will find more information about how to train Yolo on your customized dataset in this [Link](https://towardsdatascience.com/automatic-license-plate-detection-recognition-using-deep-learning-624def07eaaf).
+
+There is also other Deep learning object detector that you can use such as Single Shot Detector (SSD) and Faster RCNN.
+#### How to use : 
+We used python v3.5.5
+install requirement
+````
+pip install -r requirement.txt
+````
+
+To detect from an image
+````
+python detector.py --image test.jpg
+````
+
+To detect from a video
+````
+python detector.py --video test.mp4
+````
+
+#### Examples :
+
+Detection from image :
+![Licence_plate_detection_from_image](Licence_plate_detection/test_yolo_out_py.jpg)
+
+
 
-In this repos we study Tunisian number plate detection and recognition using different machine learning models and computer vision approches.
 
-### Yolo weights, config file and classes names file :
-```
-https://www.kaggle.com/achrafkhazri/licence-plate-detection-yolo-v3-trained-wights
-```
 
-### Dataset :
-```
-https://www.kaggle.com/achrafkhazri/anpr-dataset-tunisian-plates-and-digits
-```