Update README.md

README.md

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 # Social_Distancing_with_AI
-This project aims at monitoring people violating Social Distancing over CCTV footage during these tough COVID19 times. It uses YOLOv3 for localizing the intruders. A face mask classifier model (Resnet50) is trained on augmented masked faces (using face landmarks) for finding people not wearing a face mask.
+This project aims at monitoring people violating Social Distancing over video footage coming from CCTV Cameras. Uses YOLOv3 along with DBSCAN clustering for recognizing potential intruders. A Face Mask Classifier model (Resnet50) is trained and deployed for identifying people not wearing a face mask. Augmented masked faces are generated using facial landmarks for aiding the training process.
+
+A detailed description of this project along with the results can be found [here](#project-description-and-results).
+
+## Getting Started
+
+### Prerequisites
+Running this project on your local system requires the following packages to be installed :
+
+* numpy
+* matplotlib
+* sklearn
+* PIL
+* cv2
+* keras 
+* face_detection
+* face_recognition
+* tqdm
+
+They can be installed from the Python Package Index using pip as follows :
+
+     pip install numpy
+     pip install matplotlib
+     pip install sklearn
+     pip install Pillow
+     pip install opencv-python
+     pip install Keras
+     pip install face-detection
+     pip install face-recognition
+     pip install tqdm
+     
+You can also use [Google Colab](https://colab.research.google.com/) in a Web Browser with most of the libraries preinstalled.
+
+### Usage
+This project is implemented using interactive Jupyter Notebooks. You just need to open the notebook on your local system or on [Google Colab](https://colab.research.google.com/) and execute the code cells in sequential order. The function of each code cell is properly explained with the help of comments.
+
+Please download the following files (from the given links) and place them in the Models folder in the root directory :
+1. YOLOv3 weights : https://pjreddie.com/media/files/yolov3.weights
+2. Face Mask Classifier ResNet50 Keras Model : https://drive.google.com/drive/folders/1Q59338kd463UqUESwgt7aF_W46Fj5OJd?usp=sharing
+
+Also before starting you need to make sure that the path to various files and folders in the notebook are updated according to your working environment. If you are using [Google Colab](https://colab.research.google.com/), then :
+1. Mount Google Drive using : 
+
+        from google.colab import drive
+        drive.mount('drive/')
+        
+2. Update file/folder locations as `'drive/path_to_file_or_folder'`.