dillonj
f458eeee82
- Create dataset_coco/ for RF-DETR (COCO format) - Rename dataset_split/ to dataset_yolo/ for clarity - Add setup_datasets.py script for automated multi-format setup - Update YOLOv6 script with correct 10-class configuration - Update README with framework comparison and training instructions - Update .gitignore to exclude both dataset directories
111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""
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Setup multi-format datasets for different model frameworks.
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Creates:
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- dataset_coco/ for RF-DETR (COCO format)
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- dataset_yolo/ for YOLOX/YOLOv6/YOLOv8 (YOLO format)
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Usage:
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python setup_datasets.py
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"""
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import json
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import shutil
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from pathlib import Path
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def setup_coco_dataset():
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"""Set up COCO format dataset for RF-DETR."""
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print("Setting up COCO format dataset...")
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coco_dir = Path("dataset_coco")
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yolo_dir = Path("dataset_yolo")
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if not yolo_dir.exists():
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print("Error: dataset_yolo/ not found. Run split_coco_dataset.py first!")
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return False
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# Create COCO directories
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for split in ["train", "valid", "test"]:
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split_dir = coco_dir / split
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split_dir.mkdir(parents=True, exist_ok=True)
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# Copy images from YOLO dataset
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yolo_images = yolo_dir / split / "images"
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if yolo_images.exists():
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for img_file in yolo_images.glob("*"):
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shutil.copy2(img_file, split_dir)
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# Copy COCO annotations
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coco_ann = yolo_dir / split / "_annotations.coco.json"
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if coco_ann.exists():
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shutil.copy2(coco_ann, split_dir)
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print(f"COCO dataset created at: {coco_dir}")
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return True
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def update_yolov6_data_config():
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"""Update YOLOv6 data config to use correct number of classes."""
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print("Updating YOLOv6 data configuration...")
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# Load the COCO annotations to get class information
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coco_file = Path("dataset_yolo/train/_annotations.coco.json")
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if not coco_file.exists():
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print("Warning: Cannot find COCO annotations to update YOLOv6 config")
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return
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with coco_file.open('r') as f:
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data = json.load(f)
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categories = data['categories']
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nc = len(categories)
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names = [cat['name'] for cat in categories]
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# Update the YOLOv6 training script
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yolov6_script = Path("train_yolov6.py")
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if yolov6_script.exists():
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content = yolov6_script.read_text()
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# Replace hardcoded nc: 1 and names: ['knot']
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old_config = "nc: 1\nnames: ['knot']"
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new_config = f"nc: {nc}\nnames: {names}"
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if old_config in content:
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content = content.replace(old_config, new_config)
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yolov6_script.write_text(content)
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print(f"Updated YOLOv6 script with {nc} classes: {names}")
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else:
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print("YOLOv6 config already updated or not found")
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def main():
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print("Setting up multi-format datasets for different ML frameworks...\n")
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# Setup COCO format for RF-DETR
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if setup_coco_dataset():
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print("✅ COCO format dataset ready for RF-DETR")
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else:
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print("❌ Failed to setup COCO dataset")
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return
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# Update YOLOv6 configuration
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update_yolov6_data_config()
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print("\n" + "="*60)
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print("DATASET SETUP COMPLETE!")
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print("="*60)
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print("Available datasets:")
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print(" 📁 dataset_coco/ → RF-DETR (COCO format)")
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print(" 📁 dataset_yolo/ → YOLOX, YOLOv6, YOLOv8 (YOLO format)")
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print()
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print("Training commands:")
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print(" 🔶 RF-DETR: python train_rfdetr.py --dataset-dir dataset_coco --output-dir runs/rfdetr")
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print(" 🔵 YOLOX: python train_yolox.py --dataset-dir dataset_yolo --model yolox-nano")
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print(" 🟡 YOLOv6: python train_yolov6.py --dataset-dir dataset_yolo --model yolov6n")
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print("="*60)
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if __name__ == "__main__":
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main() |