Python YOLO V8

My Study for data science and artificial intelligence

Concepts

• Artificial Intelligence (AI)
• Python (3.12)
• YOLO V8
• Stratification Dataset
• Sklearn

Stratification

• Train: 80%
• Validate: 10%
• Test: 10%

Train 1

Network: yolov8n.pt

Commands

# Train
yolo mode=train task=detect model=yolov8n.pt data=$(pwd)/dataset/data.yaml epochs=150 cache=ram batch=-1 imgsz=640 degrees=+180
# Validate
yolo mode=val task=detect model=$(pwd)/runs/detect/train/weights/best.onnx data=$(pwd)/dataset/data.yaml
# Test
yolo mode=predict task=detect model=$(pwd)/runs/detect/train/weights/best.onnx source=$(pwd)/dataset/test/images conf=0.5 imgsz=650

Results train

Train 2

Network: yolov8s.pt

Commands

# Train
yolo mode=train task=detect model=yolov8s.pt data=$(pwd)/dataset2/data.yaml epochs=120 cache=ram batch=-1 imgsz=640 degrees=+180
# Validate
yolo mode=val task=detect model=$(pwd)/runs2/detect/train/weights/best.onnx data=$(pwd)/dataset2/data.yaml
# Test
yolo mode=predict task=detect model=$(pwd)/runs2/detect/train/weights/best.onnx source=$(pwd)/dataset2/test/images conf=0.5 imgsz=650

Train 3

Network: /runs/detect/train/weights/bets.pt

Commands

# Train
yolo mode=train task=detect model=$(pwd)/runs/detect/train/weights/bets.pt data=$(pwd)/dataset2/data.yaml epochs=120 cache=ram batch=-1 imgsz=640 degrees=+180
# Validate
yolo mode=val task=detect model=$(pwd)/runs3/detect/train/weights/best.onnx data=$(pwd)/dataset2/data.yaml
# Test
yolo mode=predict task=detect model=$(pwd)/runs3/detect/train/weights/best.onnx source=$(pwd)/dataset2/test/images conf=0.5 imgsz=650

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© Giovane Santos