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.github
 
 
Photo-Detector-V3-3
Photo-Detector-V3-3
 
 
classify
classify
 
 
data
data
 
 
models
models
 
 
segment
segment
 
 
utils
utils
 
 
.dockerignore
.dockerignore
 
 
.gitattributes
.gitattributes
 
 
.gitignore
.gitignore
 
 
.pre-commit-config.yaml
.pre-commit-config.yaml
 
 
CITATION.cff
CITATION.cff
 
 
CONTRIBUTING.md
CONTRIBUTING.md
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
README.zh-CN.md
README.zh-CN.md
 
 
benchmarks.py
benchmarks.py
 
 
collect_images.py
collect_images.py
 
 
detect.py
detect.py
 
 
export.py
export.py
 
 
hubconf.py
hubconf.py
 
 
phone.mp3
phone.mp3
 
 
phone_detector.pt
phone_detector.pt
 
 
phone_detector.py
phone_detector.py
 
 
requirements.txt
requirements.txt
 
 
setup.cfg
setup.cfg
 
 
streamlit_app.py
streamlit_app.py
 
 
test_phone_detection.ipynb
test_phone_detection.ipynb
 
 
train.py
train.py
 
 
tutorial.ipynb
tutorial.ipynb
 
 
val.py
val.py
 
 

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Welcome to the Focus Tracker by Ganesh and Aditya!

Our project detects the presence of a phone in a webcam frame. If this occurs, a series of punishments is triggered: an annoying audio file is played on max volume, this github page is opened up, and a text will be sent to your phone telling you to "GET OFF OF YOUR PHONE" via Twilio.

Our model has been trained with the YOLOv5 model from Ultralytics. Using a photo collection script, we generated our own data by rapidly taking photos via our laptop's webcam.

This project has been deployed to the web via Roboflow: https://universe.roboflow.com/aditya-kakarla-wfuyi/photo-detector-v3

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