We are developing a real-time billiard training app at Remiza that uses low-energy high-efficiency neural networks. The app analyzes users' gameplay and offers visual hints in augmented reality on the screen to enhance their skills. Our app is designed to operate smoothly and quickly on older mobile devices, and users can select from various game modes to meet their skill levels. This project is a prime example of how low-energy high-efficiency neural networks can help build innovative and beneficial mobile applications.
// Initialize the camera and neural network models
camera = initCamera();
nnModel = initNeuralNetwork();
camera = initCamera();
nnModel = initNeuralNetwork();
// Start real-time analysis of the user's gameplay
startGameplayAnalysis(camera, nnModel);
startGameplayAnalysis(camera, nnModel);
// Display visual hints in augmented reality
displayHintsAR();
displayHintsAR();
// Allow users to select different game modes
selectGameMode();
selectGameMode();
// Save user progress and results to the cloud
saveToCloud();
saveToCloud();