I will do opencv, tensorflow, yolo projects on raspberry pi

Got an idea for a smart camera, object detector, or automated vision system but not sure how to get it running on real hardware? I build and deploy computer vision projects specifically for Raspberry Pi and edge devices not just code that works on a powerful laptop, but code that actually runs smoothly on limited hardware in the real world.

With a background in embedded systems and PCB design, I understand the full picture: from camera modules and GPIO integration to power constraints and thermal limits. This means I don't just write a Python script I build something that's actually deployable.

What I can help you with:

• Real-time object detection and tracking using YOLO (v5/v8) optimized for Pi
• Custom TensorFlow/TensorFlow Lite models trained and deployed on-device
• OpenCV-based image processing pipelines (motion detection, face detection, counting, measurement, etc.)
• Integrating CV output with hardware servos, relays, LEDs, sensors, alerts
• Model optimization for speed on Pi (quantization, TFLite conversion, frame rate tuning)
• Camera setup and streaming (Pi Camera Module, USB cams, MJPEG/RTSP streams)
• Full pipeline: capture detect act, all running locally on the Pi