Nanase1234/egoobject-intention-eval

--- license: mit task_categories: - image-to-text - object-detection language: - en tags: - egocentric-vision - intention-recognition - evaluation size_categories: - 1K<n<10K --- # EgoObject Intention Dataset (Eval Split) Egocentric images with human intention annotations for object interaction - **Evaluation Split**. ## Fields | Field | Description | |-------|-------------| | `id` | Sample ID | | `image` | Egocentric view image (1920×1080) | | `target_category` | Target object category (e.g., "sink", "charger") | | `bbox` | Bounding box `[x, y, w, h]` in COCO format | | `scene_reasoning` | Scene context description | | `intention_1/2/3` | Three plausible interaction intentions | ## BBox Format **COCO format**: `[x, y, width, height]` - `x, y`: Top-left corner coordinates (pixels) - `width, height`: Box dimensions (pixels) ## Quick Start ```python from datasets import load_dataset ds = load_dataset("Nanase1234/egoobject-intention-eval") sample = ds["train"][0] print(sample["target_category"]) # e.g., "sink" print(sample["bbox"]) # e.g., [303.6, 183.6, 334.8, 115.2] print(sample["intention_1"]) # First intention ``` ## Stats - **Samples**: 5,049 - **Split**: Evaluation - **Resolution**: 1920×1080