Vision Tools
15 tools for video analysis and computer vision
Vision Capabilities
Pose Estimation: MediaPipe, OpenPose, MoveNet | Object Detection: YOLOv8, Faster R-CNN | Stroke Classification: CNN architectures (ResNet, EfficientNet, MobileNet)
Training & Validation (4 tools)
Analyze training history from vision model logs (loss, accuracy curves)
K-fold cross-validation for tennis vision models
Learning curves showing performance vs training data size
Tune learning rate, batch size, optimizer, scheduler
Model Analysis (3 tools)
Benchmark ResNet, EfficientNet, MobileNet for stroke classification
Model parameters, FLOPs, memory footprint analysis
PCA/t-SNE/UMAP visualization of model embeddings
Detection & Pose (3 tools)
Ball/player/court/racket detection metrics (IoU, precision, recall)
Pose estimation metrics: PCK, OKS, MPJPE for form analysis
Image statistics: mean, std, size distribution for video frames
Stroke Classification (3 tools)
Precision, recall, F1 with micro/macro/weighted averaging
Confusion matrix analysis showing top confusions
Class imbalance analysis with mitigation strategies
Data & Utilities (2 tools)
Frame/image distribution across stroke types and sessions
Data augmentation strategies for tennis video/image data
List all available tennis vision tools by category
Supported Architectures
| Model | Type | Use Case |
|---|---|---|
| ResNet-18/50 | CNN | Stroke classification, feature extraction |
| EfficientNet-B0 | CNN | Efficient stroke classification |
| MobileNet-V2 | CNN | Mobile/edge deployment |
| YOLOv8 | Detection | Ball/racket detection |
| Faster R-CNN | Detection | High-accuracy object detection |
| MediaPipe | Pose | Real-time pose estimation |
| OpenPose | Pose | Multi-person pose estimation |
| MoveNet | Pose | Fast pose estimation |