YOLO stands for you only look once and is a process for object detection. This app uses YOLO detection to monitor a video stream and send real-time alerts.
- Advanced object detection
- Realtime E-Mail alerts
- If you don't already have one, make a burner E-Mail. I'd strongly recommend GMail for the purpose of uploading images to its Google photos account.
- Go to Google Security and do a find for "Less secure app access". Turn on less secure app access, this allows your dummy account to send E-Mails within the app.
- Run
cp skeleton_config.py config.pyand fill in the variables with the proper values - Preferably within a dedicated virtual environment, run
pip install -r requirements.txt
- Run
./tf_gpu_setup.sh - Add this to the bottom of your .bashrc
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"
export CUDA_HOME=/usr/local/cuda
export PATH="$PATH:/usr/local/cuda/bin"- Instead of doing a pip install on requirements use tf_gpu_requirements.txt
For more info on setting up TF GPU TF GPU
# This is it. I know, anti-climactic
python main.py- Store detected object sightings in Elasticsearch
- Auto backup video into glacier
- Upload backup of discovered object capture into google pictures (cause free)
- Broadcast live stream
- Sniff for mac address & tie to image
- Set which objects to take note of
- Expand list of possible detected objects
- Allow for an offset of objects e.g. ignore 1 vehicle
- Text alerts
- Create profiles on frequently detected objects
It's a public repo, do whatever.