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