Crime Detection using Machine Learning and web3 is a project that aims to detect criminal activities in video footage using machine learning techniques and store the information in a database using django and web3 as auth.
Download or clone the repository
git clone https://github.com/AkhilAndroid/Crime-Detection-using-Machine-Learning.git
cd Crime-Detection-using-Machine-Learning-and-web3
Now install the dependencies for web3
pip install -r requirement.txt
pip install web3_auth_django-0.7-py3-none-any.whl
If you face any issues while installing web3_auth_django refer this repo
And then install python dependencies
pip install -r requirement-main.txt
Download the pre-trained models and video from Google Drive.
https://bit.ly/40m9Ka4
Extract the files and place them in the root directory of the project.
First build the Docker file
sudo docker build -t crime-detection .
Cerify the image was created
docker images
You should see something like this
crime-detection-app latest c7b090dc63 3 days ago 1.22GB
You can then run the container by
sudo docker run crime-detection
And then open http://127.0.0.1:8000/api in browser to access the web interface.
Run the following command
Start the server:
python manage.py runserver
Make sure you install Metamask in
Open http://127.0.0.1:8000/api in browser to access the web interface.
Replace video4.mp4 with your video in main.py
# Load the video
vid = imageio.get_reader('video4.mp4', 'ffmpeg')
cap = cv2.VideoCapture('video4.mp4')
Now run:
python main.py
To check every frame in a video run
python all_frame_check.py
To run multiple video run
python multiple_video.py
Check the result in the website