Datasets-Structure.md

Datasets-Structure

(YOLOv8 format)

The Yolov8 dataset for segmentation is usually structured as follows:

yolo_dataset/
│
├── train/
│ ├── images/
│ │ └── 🖼️ img_n # Example image 
│ │
│ └── labels/
│   └── 📄 img_n_labels.txt # Example labels file 
│
├── valid/
│ │ ... (similar)
│
└── 📄 data.yaml

Each img_x_labels.txt file contains multiple annotations (one per line) with corresponding class ID and segmentation coordinates:

<class-index> <x1> <y1> <x2> <y2> ... <xn> <yn>

The file data.yaml contains keys such as:

• names (the class names)
• nc (number or classes)
• train (path/to/train/images/)
• val (path/to/val/images/)

(COCO Instance Segmentation format)

coco_dataset/
│
├── train/
│  ├── 🖼️ img_n # Example image 
│  └── 📄 annotations.json # The annotations json file
│
└── valid/ 
   └── ... (similar)

The annotations json file contains a dictionary of lists:

• images (a list of dictionaries)

  • id - image ID
  • file_name
  • height
  • width

• annotations (a list of dictionaries)

  • id
  • image_id
  • category_id
  • bbox
  • area
  • segmentation (a segmentation polygon)
  • iscrowd

• categories (a list of dictionaries)

  • id
  • name