8938661850
Features: - Auto-labeling pipeline: CSV values -> PDF search -> YOLO annotations - Flexible date matching: year-month match, nearby date tolerance - PDF text extraction with PyMuPDF - OCR support for scanned documents (PaddleOCR) - YOLO training and inference pipeline - 7 field types: InvoiceNumber, InvoiceDate, InvoiceDueDate, OCR, Bankgiro, Plusgiro, Amount Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
60 lines
1.5 KiB
YAML
60 lines
1.5 KiB
YAML
# YOLO Training Configuration
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# Use with: yolo train data=dataset.yaml cfg=training.yaml
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# Model
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model: yolov8s.pt
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# Training hyperparameters
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epochs: 100
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patience: 20 # Early stopping patience
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batch: 16
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imgsz: 1280
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# Optimizer
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optimizer: AdamW
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lr0: 0.001 # Initial learning rate
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lrf: 0.01 # Final learning rate factor
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momentum: 0.937
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weight_decay: 0.0005
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# Warmup
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warmup_epochs: 3
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warmup_momentum: 0.8
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warmup_bias_lr: 0.1
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# Loss weights
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box: 7.5 # Box loss gain
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cls: 0.5 # Class loss gain
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dfl: 1.5 # DFL loss gain
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# Augmentation
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# Keep minimal for document images
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hsv_h: 0.0 # No hue augmentation
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hsv_s: 0.1 # Slight saturation
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hsv_v: 0.2 # Brightness variation
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degrees: 5.0 # Rotation ±5°
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translate: 0.05 # Translation
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scale: 0.2 # Scale ±20%
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shear: 0.0 # No shear
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perspective: 0.0 # No perspective
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flipud: 0.0 # No vertical flip
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fliplr: 0.0 # No horizontal flip
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mosaic: 0.0 # Disable mosaic (not suitable for documents)
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mixup: 0.0 # Disable mixup
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copy_paste: 0.0 # Disable copy-paste
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# Validation
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val: true
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save: true
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save_period: 10
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cache: true
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# Other
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device: 0 # GPU device (0, 1, etc.) or 'cpu'
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workers: 8
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project: runs/train
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name: invoice_fields
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exist_ok: true
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pretrained: true
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verbose: true
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