ravi-11 / Social-Distancing-and-Face-Mask-Detection

Social Distancing and Face Mask Detection using TensorFlow. Install all required Libraries and GPU drivers as well. Refer to README.md or REPORT for know to installation requirement

Social Distancing and Face Mask Detection 😷

                      

                                                              😷C O V I D - 1 9                           A L E R T!🙏

Team Members:

                Shantanu Gupta - 1816410243 - Group_no (18),
                Ravi Pratap - 1816410217 - Group_no (14-A),
                Rishabh Gupta - 1816410218 - Group_no (14-A),
                Sachin Soni - 1816410225 - Group_no (23)

About--

                  Social Distancing and Face Mask Detection Platform utilizes Artificial Network to perceive if a person walk with maintain social distance and does/doesn’t wear a mask as well. The application can be associated with any current or new IP cameras to identify individuals maintaining social distance with/without a mask. 😷

System Requirement -- 🖥️

• SOFTWARE--      
  • Software:                 Anaconda + Python 3.x (3.8 or earlier)
  • Editor:                      VS Code/ PyCharm/ Sublime/ Spyder
    
  • Environment:          TensorFlow
  • GPU Drivers:           Nvidia® CUDA® 11.0 requires 450.x or above
                                   CUDA® Toolkit (TensorFlow >= 2.4.0)
                                   cuDNN SDK 8.0.4 (TensorFlow >= 2.4.0)

• HARDWARE--
  • GPU:                                     Graphics Processor (NVIDIA) ̶min 2GB
  • Camera:                                CCTV/ Webcam/ Mobile Camera (Sharing Camera)
  • Storage Disk (Optional):       SSD – Min 400MB/s Read Speed

Installation Process--

• Download Anaconda Software --

	Operating System	Download Link
👉	Windows	click here
👉	Mac	click here
👉	Linux	click here

📢 During Installation be sure to check to set Environmental variable path

• Create new Environment for the installation of libraries:
  • Open Command Prompt / Anaconda Prompt and type conda create --name tf_python
    you can set any name in place of tf_python to create a new envionment. and after type y and enter.
  • Install all required Libraries given in requirement.txt by using command pip install -r requirement.txt

Required Libraries--

•          TensorFlow
•    TensorFlow-GPU
•                  Python
•        Scikit Learn
•         Computer Vision
•                  Scientific Python

File Required to Download --

• DATASETS :
          Using datasets to train the model for Face Mask Detection model. To download the dataset -- 👉 Click here  :point_left: (Dataset with 4,000 Images Sampels) :star2:File contain 2 Sub-Folder i.e. With_mask & Without_mask (each folder contain 2k samples of images).

This is a balanced dataset containing faces with and without masks with a mean height of 283.68 and mean width of 278.77

• Yolo Weights (V3) -- Pre-Trained model:
          YOLO (You Only Live Once), the pre-trained weights of the neural network are stored in yolov3.weights                                     Download the Weight File 👉 Click here 👈

Trained Result of Face Mask Model--

File Structure

Set all downloaded files to their respective folders/path as given in Folder Structure Diagram.

RUN the Main Module--

• Using Command Prompt or Anaconda Prompt:
  • To activate environment:--      conda activate tf_python
  • Run main module:-- python main.py

Outputs--

Contribute:

                🔥 Contributions are always welcome!

Drop a ⭐ if you like this Repository.. 😄

    

👉👉👉                               :point_left::point_left::point_left: