File size: 2,226 Bytes
919865e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | #!/bin/bash
# Master Launch Script — runs entire pipeline when GPU frees
# Usage: nohup bash Scripts/launch_all.sh > logs/launch_all.log 2>&1 &
source ~/miniconda3/etc/profile.d/conda.sh
conda activate dairygoat
cd ~/goat
echo "=========================================="
echo " FULL PIPELINE LAUNCH"
echo " Start: $(date)"
echo "=========================================="
# Step 0: Wait for GPU
echo "[Step 0] Waiting for GPU > 18GB free..."
while true; do
FREE=$(nvidia-smi --query-gpu=memory.free --format=csv,noheader | head -1 | awk '{print $1}')
if [ "$FREE" -gt 18000 ]; then
echo " GPU free: ${FREE}MiB — STARTING!"
break
fi
echo " $(date +%H:%M:%S) GPU free: ${FREE}MiB — waiting..."
sleep 300
done
# Step 1: CPU Analysis
echo "[Step 1] Running CPU analysis..."
python3 -u Scripts/analyze_cameras.py 2>&1 | tail -20
python3 -u Scripts/analyze_annotations.py 2>&1 | tail -20
echo " Analysis done."
# Step 2: Cross-Validation
echo "[Step 2] Running cross-validation..."
python3 -u Scripts/eval_crossval.py 2>&1 | tee logs/eval_crossval.log
echo " Cross-val done."
# Step 3: Checkpoint Ensemble
echo "[Step 3] Running checkpoint ensemble..."
python3 -u Scripts/checkpoint_ensemble.py 2>&1 | tee logs/checkpoint_ensemble.log
echo " Checkpoint ensemble done."
# Step 4: Adaptive WBF Master Pipeline
echo "[Step 4] Running adaptive WBF pipeline..."
python3 -u Scripts/pipeline_master.py 2>&1 | tee logs/pipeline_master.log
echo " Adaptive WBF done."
# Step 5: Final Summary
echo "[Step 5] Generating final summary..."
python3 -u -c "
import json, os
results = {}
for name in ['crossval', 'checkpoint_ensemble', 'pipeline_master', 'kitchen_sink_v2']:
path = f'logs/{name}_results.json'
if os.path.exists(path):
with open(path) as f: results[name] = json.load(f)
with open('logs/ALL_RESULTS.json', 'w') as f:
json.dump(results, f, indent=2)
print('All results saved to logs/ALL_RESULTS.json')
for name, data in sorted(results.items()):
print(f' {name}: {json.dumps(data)[:200]}')
"
echo ""
echo "=========================================="
echo " FULL PIPELINE COMPLETE"
echo " End: $(date)"
echo "=========================================="
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