Voilence Detection for protest management

This is a project that aims to detect violence in protests.
The project uses live data from CCTV cameras and the footage is captured using computer vision. Through the video, it detects if there are any objects being thrown or people being assaulted.
The LSTM model was used to identify objects in the video footage. It is based on neural networks and can be trained to recognize certain types of objects or actions. The CNN model was used for detecting violence, which works by identifying movement and human shapes in the image. It flags them as potential violence contributors (source) including weapons.

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
.vscode		.vscode
__pycache__		__pycache__
static		static
templates		templates
Model.py		Model.py
README.md		README.md
Voilence_lstm_flas_app.py		Voilence_lstm_flas_app.py
__init__.py		__init__.py
app.py		app.py
expression.model		expression.model
face_main.py		face_main.py
haar_cascade_face_detection.xml		haar_cascade_face_detection.xml
mamonbest947oscombo.h5		mamonbest947oscombo.h5
requirements.txt		requirements.txt

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