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Facial Recognition Attendance System is a final year project built with Python Flask, OpenCV, TensorFlow/Keras, and SQLite for students who want an AI-based college attendance web application. This final year project uses Haar cascade face detection, MobileNetV2 embeddings, and cosine similarity matching to identify students and mark attendance through a browser camera workflow. It includes separate portals for administrators, faculty, and students. Admins can manage departments, courses, semesters, sections, subjects, faculty, students, face datasets, system settings, attendance, notices, and reports. Faculty can mark or correct attendance for assigned classes and export reports. Students can view attendance history, download CSV reports, read notices, and request face-data refresh. With configurable attendance rules, reports, and camera-based marking, this project is suitable for a final year major project in Flask, OpenCV, TensorFlow, and computer vision.
Administrator
adminadmin123Faculty after seed
adesai / faculty123rverma / faculty123Student after seed
BEC24CS001priya.sharmastudent123BEC24CS001 to BEC24CS008/student/mark/api/mark endpoint for base64 camera image attendance marking.npy per studentpython -m venv .venv.venv\Scripts\activatesource .venv/bin/activatepip install -r requirements.txtpython seed.pypython seed.py --forcepython app.pyhttp://127.0.0.1:5000Administrator
adminadmin123Faculty after seed
adesai / faculty123rverma / faculty123Student after seed
BEC24CS001priya.sharmastudent123BEC24CS001 to BEC24CS008