“BrowZen correlates your emotional states with the web sites you visit to give you actionable insights about your time on the web.
A webcam attached to an NVIDIA Jetson Xavier NX captures periodic images of the user of the computer as a background process. These images are classified (see classify_emotion.py) by a VGG19 convolutional neural network that has been pretrained to recognize seven emotional states (“Angry”, “Disgust”, “Fear”, “Happy”, “Sad”, “Surprise”, and “Neutral”). Observations (emotional state, datetime stamp) are recorded in an SQLite3 database. For privacy protection, images are destroyed after classification, and all processing takes place locally—nothing is sent to the cloud.
Next, analysis.py connects to the SQLite3 database that stores web history in Chrome/Chromium and correlates web site visit times with the database of emotional state observations created by the classification step. The result of the analysis, the sum of each emotional state observed while visiting each web site, is stored in an SQLite3 database table.
Finally, the analysis results are used to generate a web dashboard (generate_dashboard.py) to provide a simple way to visualize, on average, how each web site one visits impacts their emotional state. The web dashboard (dashboard.html) relies on only HTML5 and JavaScript.”