Since we know, that already a lot of work has been done in the field of face recognition, we wanted to do something new, therefore we integrated real time mask detection with our project. In this, we capture the images in real time and detect whether they are with or without mask.

Image_Mask_Detection.py (L-22) :

[f for f in glob.glob(r'Address Of Image_input/' + name1 + "/**/*", recursive = True) if not os.path.isdir(f)]

Face_Recognition.py (L-37) :

[f for f in glob.glob(r'Address Of NoMaskStd/'+ str(name2)

• Step 0) Download project on your system.
• Step 1) Install all the dependencies from requirements.txt, using command prompt ' pip install -r requirements.txt '.
• Step 2) Run detect_Mask_webcam.py file, now you'll see realtime mask recognition with counter.
• Step 3) Press "p" to capture image, press "m" to trigger the whole process, press "q" to quit.

Note: After pressing "m" whole process is triggered automatically, you don't need to run Image_Mask_Detection.py, and Face_Recognition.py separately.

• Capture : Mask Detection with Counter.
• NoMaskStd : Non-masked faces.
• Known : Non-masked faces recognized through dataset.
• Unknown : Non-masked faces not present in dataset.

Note : - All the captures in each directories are saved in a different folder everyday. - All the captures of the day are processed in eack run.

Attendence.csv : Stores the Counter value of each image, with Date & time.

No_Mask_Std.csv : Stores names of non-masked faces recognized by system, with Date & time.

• Loss: 0.0233
• Accuracy: 0.9928
• Validation loss: 0.0505
• Validation accuracy: 0.9868

• Link for downloading the Model : https://drive.google.com/drive/folders/1bh-MMlvRwwhIl78Mqq1KUBzCdWYw_hbC?usp=sharing
• Paste this file in the folder, and replace it with the 'mask_detection.model' already present inside the master folder.
• 'mask_detection.model' trained on the Sequential CNN model upto 100epochs (training file not uploaded due to copyright issues).

Note : To run on your self trained model make sure to Edit the code in to read the model in detect_Mask_webcam.py, Image_Mask_Detection.py files.

• For mask detection : https://www.kaggle.com/dhruvmak/face-mask-detection
• For face recognition : self made, feel free to add more faces. Just make sure to name each image ;)