| --- |
| dataset_info: |
| features: |
| - name: object_captions |
| list: string |
| - name: image_caption |
| dtype: string |
| - name: normalized_boxes |
| list: |
| list: float32 |
| - name: img_size_wh |
| list: int32 |
| - name: source_dataset |
| dtype: string |
| - name: relative_path |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 10259224594 |
| num_examples: 5788300 |
| download_size: 8572776179 |
| dataset_size: 10259224594 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| language: |
| - en |
| license: cc-by-4.0 |
| size_categories: |
| - 1M<n<10M |
| task_categories: |
| - object-detection |
| pretty_name: Breakpoint Grounding 5M |
| tags: |
| - object-detection |
| - bounding-boxes |
| - grounding |
| - image-captioning |
| --- |
| |
| # Breakpoint Grounding 5M |
|
|
| ## Quick start |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("BreakpointAI/breakpoint-grounding-5m", split="train") |
| ds[0] # {'source_dataset': ..., 'relative_path': ..., 'image_caption': ..., 'object_captions': [...], 'normalized_boxes': [...], 'img_size_wh': [...]} |
| ``` |
|
|
| ## Dataset summary |
|
|
| An annotations-only companion to |
| [Breakpoint Grounding 55M](https://huggingface.co/datasets/BreakpointAI/breakpoint-grounding-55m): |
| image-level captions, object bounding boxes, and a caption for every box, for **5,788,300 images** |
| drawn from 16 public object-detection/tracking benchmarks. |
|
|
| In contrast to the 55M dataset, where the bounding box annotations are model-generated, in this dataset the bounding box annotations here are hand-labeled. |
|
|
| **No image bytes are included in this release.** Several of the source benchmarks (notably |
| ImageNet and Objects365) restrict redistribution of their images. To stay clear of that, this |
| dataset publishes only the annotations Breakpoint authored, plus a `source_dataset` + |
| `relative_path` pointer back to each image — usable by anyone who already has their own licensed |
| copy of the relevant source dataset, laid out in its standard directory structure. |
|
|
| - **5,788,300 images**, each with one image-level caption |
| - **51,196,466 bounding boxes** (8.84 per image on average), each with its own caption |
|
|
| ## Source datasets |
|
|
| | Source | Share | Description | |
| |--------|------:|-------------| |
| | Open Images (train/test/val) | 34.7% | Google's large-scale detection/annotation dataset | |
| | Objects365 (train/test/unlabeled) | 34.8% | Megvii/BAAI large-vocabulary object detection dataset | |
| | LaSOT | 13.3% | Large-scale single-object tracking benchmark | |
| | ImageNet | 10.3% | Large-scale image classification dataset (ILSVRC) | |
| | COCO (train) | 2.0% | Common Objects in Context detection/captioning benchmark | |
| | Open Images (test) | 1.9% | (see above) | |
| | RoboFlow 100 | 1.7% | Benchmark aggregating 100 diverse object-detection datasets | |
| | LVIS (train) | 1.7% | Large-vocabulary instance segmentation, built on COCO images | |
| | ObjectNet3D | 1.6% | Object recognition/pose dataset | |
| | BDD100K | 1.4% | Berkeley DeepDrive large-scale driving-scene dataset | |
| | CrowdHuman | 0.3% | Pedestrian / crowd detection benchmark | |
| | UWISOccludedDataset | 0.15% | Occlusion-focused detection dataset | |
| | LOCO | 0.1% | Logistics-scene object detection dataset | |
|
|
| <!-- TODO: verify descriptions/full names above, especially UWISOccludedDataset and LOCO, whose |
| provenance we're least certain about. Percentages from an earlier per-source row count. --> |
| |
| ## How it was built |
|
|
| - **Object detection**: bounding boxes and class labels are given by the datasets, provided by human labelers. |
| - **Per-object captions**: [InternVL3-2B](https://huggingface.co/OpenGVLab/InternVL3-2B), served |
| via LMDeploy. Each detected box was cropped (no padding) and captioned with: |
| > `<image>` Describe this `<category name>` in 20 words or less and focus on its color, |
| > appearance, size, and style, etc. |
|
|
| where `<category name>` is the detector's class label for that box. |
| - **Image-level captions**: [InternVL3-8B](https://huggingface.co/OpenGVLab/InternVL3-8B), |
| prompted with: |
| > `<image>` Write a single, natural-language description of this image. Do not use bullet |
| > points or lists. Keep it under 100 words. |
|
|
| Captions are **not human-generated** and contain the usual model-generated hallucinations. |
|
|
| ## Dataset structure |
|
|
| | Field | Type | Description | |
| |-------|------|-------------| |
| | `source_dataset` | `string` | Which of the 16 source benchmarks this image came from. | |
| | `relative_path` | `string` | Path to the image within that source dataset's standard layout. | |
| | `image_caption` | `string` | A single natural-language caption describing the whole image. | |
| | `object_captions` | `Sequence(string)` | One caption per detected object. Index-aligned with `normalized_boxes`. | |
| | `normalized_boxes` | `Sequence(Sequence(float32))` | One bounding box per detected object: `[x_min, y_min, x_max, y_max]` (xyxy), normalized to `[0, 1]`. | |
| | `img_size_wh` | `Sequence(int32)` | Original image size as `[width, height]` in pixels. | |
|
|
| ## Licensing |
|
|
| **The annotations in this dataset** (`image_caption`, `object_captions`, `normalized_boxes`, |
| `img_size_wh`) are released by Breakpoint AI under **CC BY 4.0**. |
|
|
| **Images are not included.** To use this dataset with actual pixels, obtain each source dataset |
| separately under its own license/terms and join on `source_dataset` + `relative_path`. Several |
| sources (ImageNet, Objects365 in particular) restrict commercial use and/or redistribution — |
| check the terms of whichever source(s) you need before using their images. |
|
|
| **Removal requests.** If you believe your content is represented in these annotations and want |
| the corresponding row removed, open a discussion on this repository. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{breakpoint_grounding_5m, |
| title = {Breakpoint Grounding 5M}, |
| author = {Wang, Franklin and Zhong, Desmond and Murdoch, Jamie}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/BreakpointAI/breakpoint-grounding-5m} |
| } |
| ``` |
|
|
