README.md

---
license: apache-2.0
task_categories:
- image-feature-extraction
tags:
- camera
- camera-calibration
- imagenet
- camera-parameters
size_categories:
- 1M<n<10M
---

# ImageNet-1K-Camera

Per-image **camera parameter** annotations for the full **ImageNet-1K** dataset
(1,000 training classes + the 50,000-image validation split, ~1.35M images,
**0 failures**), predicted by the **Puffin** camera-centric multimodal model
(Qwen2.5-7B + C-RADIOv3-H visual encoder).

## Format

The archive mirrors the source ImageNet WebDataset layout: one `.tar` per source
shard (`n*.tar` per class, plus `val.tar`), each containing one `.json` per image
whose name matches the source image stem.

Each JSON holds the predicted monocular camera parameters:

| field | meaning | unit |
|-------|---------|------|
| `roll`  | camera roll        | radians |
| `pitch` | camera pitch       | radians |
| `vfov`  | vertical field of view | radians |
| `k1`    | radial distortion coefficient | – |
| `parse_ok` | whether the model output parsed within valid ranges | bool |

Example:

```json
{"roll": 0.0123, "pitch": -0.0871, "vfov": 1.0123, "k1": -0.012, "parse_ok": true}
```

## Camera-parameter distributions

Histograms of the predicted roll / pitch / vertical-FoV over the whole dataset,
**train and val plotted separately** (proportion of valid samples per 10° bin;
`parse_ok=False` samples excluded).

### Train (1,278,950 images)

![train camera stats](analysis/imagenet1k_train_camera_stats.png)

### Val (49,924 images)

![val camera stats](analysis/imagenet1k_val_camera_stats.png)

| split | roll μ / med / σ | pitch μ / med / σ | FoV μ / med / σ |
|-------|------------------|-------------------|-----------------|
| train | 0.1° / 0.0° / 7.8° | −7.8° / −3.7° / 15.7° | 28.9° / 25.6° / 8.9° |
| val   | 0.1° / 0.0° / 8.5° | −8.8° / −4.5° / 16.7° | 30.3° / 27.5° / 9.1° |

**Reading the distributions**

- **Roll** is sharply peaked at 0° — ImageNet photos are overwhelmingly shot
  upright/level, with only a small tilted tail.
- **Pitch** is centered slightly **negative** (≈ −4° to −8°), i.e. cameras tend
  to look marginally downward at the subject, with a noticeably wider spread
  than roll.
- **FoV** is concentrated in the **20–40°** range (median ≈ 26–28°), typical of
  everyday / mild-telephoto photography; a long thin tail reaches wide-angle.
- **Train vs val agree closely** on all three parameters, indicating consistent
  capture statistics across the two splits.

## Notes

- Annotations are model predictions, not ground truth.
- Generated with greedy decoding (deterministic) at 640px input.
- Figures reproduce `scripts/annotation/stat_camera_captions.py` from the Puffin
  repo (read directly from the packed tars).