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# Datasets-Structure |
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**(YOLOv8 format)** |
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The Yolov8 dataset for segmentation is usually structured as follows: |
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``` |
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yolo_dataset/ |
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│ |
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├── train/ |
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│ ├── images/ |
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│ │ └── 🖼️ img_n # Example image |
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│ │ |
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│ └── labels/ |
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│ └── 📄 img_n_labels.txt # Example labels file |
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│ |
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├── valid/ |
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│ │ ... (similar) |
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│ |
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└── 📄 data.yaml |
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``` |
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Each ```img_x_labels.txt``` file contains multiple annotations (one per line) with corresponding class ID and segmentation coordinates: |
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`<class-index> <x1> <y1> <x2> <y2> ... <xn> <yn>` |
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The file `data.yaml` contains keys such as: |
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- names (the class names) |
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- nc (number or classes) |
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- train (path/to/train/images/) |
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- val (path/to/val/images/) |
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**(COCO Instance Segmentation format)** |
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``` |
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coco_dataset/ |
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│ |
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├── train/ |
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│ ├── 🖼️ img_n # Example image |
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│ └── 📄 annotations.json # The annotations json file |
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│ |
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└── valid/ |
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└── ... (similar) |
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``` |
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The annotations json file contains a dictionary of lists: |
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- images (a list of dictionaries) |
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- id - image ID |
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- file_name |
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- height |
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- width |
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- annotations (a list of dictionaries) |
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- id |
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- image_id |
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- category_id |
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- bbox |
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- area |
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- segmentation (a segmentation polygon) |
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- iscrowd |
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- categories (a list of dictionaries) |
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- id |
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- name |
