Description: I can assist in creating sophisticated AI-driven Computer Vision systems utilizing cutting-edge Deep Learning techniques for applications such as automated security, attendance tracking, or live data analysis.

I specialize in developing high-efficiency solutions using YOLOv8, OpenCV, and MediaPipe for the real-time identification, recognition, and tracking of individuals or items. My expertise covers various needs, including intelligent monitoring setups, crowd counting applications, or industrial automation tools.

Services Provided:

• Identification and recognition of individuals (OpenCV, Dlib, FaceNet)
• Item identification using YOLOv5/v8, SSD, or Faster-RCNN
• Tracking of multiple items (Deep SORT, ByteTrack)
• User interface development (Tkinter, PyQT, Flask)
• Preparation of data and model training
• Integration with network or local cameras
• Logging, generation of reports, and data extraction capabilities

Technologies Used: Python, OpenCV, YOLOv8, PyTorch, Flask, SQLite, Raspberry Pi, MediaPipe