PHASE1_TRAINING_STARTED.md

Phase 1 Training Started - Domain Adaptation

Status: ✅ TRAINING ACTIVE

Started: Phase 1 training with domain adaptation strategy
Config: configs/resume_with_domain_adaptation.yaml
Starting Epoch: 39 checkpoint → Training epochs 40-50
Log File: training_phase1_domain_adaptation.log

What's Running

Training Configuration

• Epochs: 40-50 (10 epochs)
• Batch Size: 2 (physical)
• Gradient Accumulation: 20 steps (effective batch = 40)
• Resolution: 1120 (will increase to 1288 in Phase 1.5)
• Learning Rate: 0.0002
• Multi-scale: Disabled (will enable in Phase 3)

Domain Adaptation Augmentations (Config)

The config includes:

• Motion blur (prob=0.5, max_kernel_size=15)
• Gaussian blur (prob=0.3)
• ISO noise (prob=0.3)
• JPEG compression (prob=0.2)
• Copy-paste (prob=0.5, max_pastes=3)
• Color jitter (reduced intensity)

⚠️ Important Note: RF-DETR may have its own internal augmentation system. The augmentation section in the config might not be directly used by RF-DETR's train() function. We need to verify if augmentations are being applied.

Expected Results

Target: Small objects mAP improvement from 0.598 to 0.63-0.65 over 10 epochs

Monitoring:

• Check small objects mAP after each epoch
• Watch for improvement in motion-blurred ball detection
• Monitor training loss trends

Next Steps

1. Monitor Training: tail -f training_phase1_domain_adaptation.log
2. After Epoch 45: Evaluate and switch to Phase 1.5 (high-res)
3. Verify Augmentations: Check if RF-DETR is applying augmentations
4. If Augmentations Not Applied: Preprocess dataset offline with augmentations

Commands

Monitor Training

tail -f training_phase1_domain_adaptation.log

Check GPU Usage

watch -n 1 nvidia-smi

Evaluate After Epoch 40

python scripts/comprehensive_training_evaluation.py configs/resume_with_domain_adaptation.yaml

Changes Made

1. ✅ Inference Threshold Fixed: src/perception/local_detector.py - Changed default from 0.5 to 0.05
2. ✅ Domain Adaptation Config Created: configs/resume_with_domain_adaptation.yaml
3. ✅ Training Started: Phase 1 with domain adaptation strategy

Verification Needed

• Verify RF-DETR is applying augmentations (check training images or RF-DETR source)
• If not, preprocess dataset with augmentations offline
• Monitor small objects mAP improvement
• Check for any errors in training log