How can I build a real-time shuttlecock detection system?

To build a real-time shuttlecock detection system, you can use computer vision with deep learning. First, collect and annotate a dataset of shuttlecock images in different positions and lighting conditions.

Train a convolutional neural network (CNN) or use a pre-trained model like YOLO or SSD to detect and track the shuttlecock. These models can localize and classify the shuttlecock in real-time. Use OpenCV to preprocess the video feed and integrate it with the trained model.

Optimize the system for speed and accuracy by fine-tuning the model and employing hardware acceleration, such as GPUs or edge devices like NVIDIA Jetson, for real-time performance.