| | --- |
| | license: other |
| | task_categories: |
| | - image-segmentation |
| | tags: |
| | - cvat |
| | - segmentation |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # Sinon_Less - Segmentation Dataset |
| | |
| | Instance Segmentation dataset with polygon annotations. |
| | |
| | ## Dataset Description |
| | |
| | - **Source**: CVAT Annotation Platform |
| | - **Format**: Segmentation |
| | - **Total Samples**: 2535 |
| | - **Splits**: train: 1497, val: 267, test: 771 |
| | |
| | ## Labels |
| | |
| | - `Person` |
| | - `Hard Hat` |
| | - `No Head Protection` |
| | - `Cleanroom Suit` |
| | - `Splash Proof Gown` |
| | - `No Protective Clothing` |
| | - `Full Face Mask` |
| | - `No Full Face Mask` |
| | |
| | ## Usage |
| | |
| | ```python |
| | from datasets import load_dataset |
| |
|
| | # Load the dataset |
| | dataset = load_dataset("Daniel246/cvat-sinon_less-segmentation") |
| |
|
| | # Access splits |
| | train_data = dataset["train"] |
| | val_data = dataset["val"] |
| | test_data = dataset["test"] |
| | |
| | # Example: iterate over samples |
| | for sample in train_data: |
| | image = sample["image"] |
| | # Process annotations based on format type |
| | ``` |
| | |
| | ## Dataset Structure |
| |
|
| | ### Data Fields |
| |
|
| | - `image`: PIL Image |
| | - `image_id`: Unique identifier for the image |
| | - `width`: Image width in pixels |
| | - `height`: Image height in pixels |
| | - `objects`: List of segmented objects with: |
| | - `bbox`: Bounding box [x_center, y_center, width, height] (normalized) |
| | - `polygon`: List of [x, y] points (normalized) |
| | - `category_id`: Class index |
| | - `category_name`: Class name |
| |
|
| | ## License |
| |
|
| | Please check the original data source for licensing information. |
| |
|
| | --- |
| | *Generated by CVAT Training System* |
| |
|
