Ascendify is an advanced tool for analyzing bouldering movements using video pose detection. It extracts pose data, calculates movement metrics, and offers real-time feedback to enhance climbing performance. Features include data visualization, machine learning integration, and actionable insights.
Incorporate machine learning models to enhance the classification of movements and prediction of performance. This will enable more sophisticated analysis and provide deeper insights into bouldering techniques.
Integrate machine learning models to classify movements:
Select appropriate machine learning models for movement classification.
Integrate the chosen models into the existing system.
Ensure the models can accurately classify different types of movements.
Train models on collected pose data to predict performance:
Collect and preprocess pose data for training.
Train the machine learning models using the collected data.
Validate and test the models to ensure they can reliably predict performance metrics.
Additional Context
No response
Expected Actions
[ ] Integrate machine learning models to classify movements
[ ] Train models on collected pose data to predict performance
Description
Incorporate machine learning models to enhance the classification of movements and prediction of performance. This will enable more sophisticated analysis and provide deeper insights into bouldering techniques.
Integrate machine learning models to classify movements:
Train models on collected pose data to predict performance:
Additional Context
No response
Expected Actions
Definition Of Done