| --- |
| license: apache-2.0 |
| task_categories: |
| - image-segmentation |
| - object-detection |
| - robotics |
| language: |
| - en |
| tags: |
| - robotics |
| - navigation |
| - frontiers |
| - autonomous-systems |
| - field-robotics |
| - vision-foundation-models |
| - outdoor-navigation |
| - traversability |
| - exploration |
| pretty_name: WildOS Frontiers Dataset |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "**" |
| --- |
| |
| # WildOS Frontiers Dataset |
|
|
| <div align="center"> |
| <img src="https://leggedrobotics.github.io/wildos/static/images/Teaser-V.svg" alt="WildOS Teaser" width="800"/> |
| </div> |
|
|
| ## Dataset Description |
|
|
| This dataset provides **visual frontier annotations** for outdoor long-range navigation, created for [WildOS: Open-Vocabulary Object Search in the Wild](https://leggedrobotics.github.io/wildos/). The annotations are built on top of images from the [GrandTour Dataset](https://huggingface.co/datasets/leggedrobotics/grand_tour_dataset). |
|
|
| **Visual Frontiers** denote regions in the image that correspond to candidate locations for further exploration — such as the end of a trail, an opening |
| between trees, or a road turning at a curve. This dataset enables training of models to predict visual frontiers from RGB images, extending navigation reasoning beyond the geometric depth horizon. |
|
|
| ## Dataset Structure |
|
|
| ``` |
| wildos/ |
| ├── annotations/ # Frontier annotations (362 JSON files) |
| │ └── annotation_00000.json ... annotation_00389.json |
| ├── RGB_frames/ # Raw RGB frames (390 images + metadata) |
| │ ├── metadata.json # Maps to original GrandTour images |
| │ └── rgb_00000.png ... rgb_00389.png |
| ├── RGB_rectified/ # Rectified RGB images (390 images) |
| │ └── rect_00000.png ... rect_00389.png |
| └── SAM_boundaries/ # SAM-2 boundary masks (390 images) |
| └── bound_00000.png ... bound_00389.png |
| ``` |
|
|
| ### File Descriptions |
|
|
| | Folder | Description | Count | |
| |--------|-------------|-------| |
| | `annotations/` | JSON files containing frontier bounding box annotations | 362 | |
| | `RGB_frames/` | Original RGB frames from GrandTour dataset | 390 + 1 metadata | |
| | `RGB_rectified/` | Rectified (undistorted) RGB images | 390 | |
| | `SAM_boundaries/` | Binary masks from SAM-2 boundary detection | 390 | |
|
|
| > **Note:** Some images do not have corresponding annotations (362 out of 390 images are annotated). Images without annotations were excluded during quality control. The `SAM_boundaries/` folder contains SAM-2 boundary masks used in an ablation study, where frontiers were defined as the SAM boundary segments within human-annotated bounding boxes. |
| |
| ## Annotation Format |
| |
| Each annotation file contains a list of frontier detections with the following structure: |
| |
| ```json |
| [ |
| { |
| "label": "frontier", |
| "start": [1326.0, 618.0], |
| "end": [1352.0, 636.0] |
| } |
| ] |
| ``` |
| |
| | Field | Description | |
| |-------|-------------| |
| | `label` | Frontier label (currently `"frontier"` for all annotations) | |
| | `start` | Top-left corner `[x, y]` of the bounding box | |
| | `end` | Bottom-right corner `[x, y]` of the bounding box | |
| |
| > **Note:** The `label` field exists because we initially experimented with labeling frontiers of varying strengths. In the final dataset, all annotations use the single label `"frontier"`. |
| |
| ## Example Annotations |
| |
| <div align="center"> |
| <table> |
| <tr> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00001.png" width="400"/></td> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00024.png" width="400"/></td> |
| </tr> |
| <tr> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00037.png" width="400"/></td> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00086.png" width="400"/></td> |
| </tr> |
| <tr> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00191.png" width="400"/></td> |
| <td><img src="https://leggedrobotics.github.io/wildos/static/images/label_examples/rect_00264.png" width="400"/></td> |
| </tr> |
| </table> |
| </div> |
| |
| *Red regions indicate visual frontiers — candidate locations for further exploration.* More examples can be viewed [here](https://leggedrobotics.github.io/wildos/#frontier-annotations). |
| |
| ## Usage |
| |
| ### Loading Individual Files |
| |
| ```python |
| import json |
| from PIL import Image |
| |
| # Load an annotation |
| with open("wildos/annotations/annotation_00000.json", "r") as f: |
| annotations = json.load(f) |
| |
| # Load corresponding image |
| image = Image.open("wildos/RGB_rectified/rect_00000.png") |
|
|
| print(f"Image size: {image.size}") |
| print(f"Number of frontiers: {len(annotations)}") |
| ``` |
| |
| ### Visualizing Annotations |
| |
| Visualize frontier annotations on images: |
| |
| ```python |
| import os |
| import json |
| import cv2 |
| import numpy as np |
|
|
| def visualize_frontiers(image_path, annotation_path, output_path=None): |
| """Draw frontier annotations on an image.""" |
| # Load image |
| img = cv2.imread(image_path) |
| |
| # Load annotations |
| with open(annotation_path, "r") as f: |
| annotations = json.load(f) |
| |
| # Draw each frontier |
| for ann in annotations: |
| x1, y1 = int(ann["start"][0]), int(ann["start"][1]) |
| x2, y2 = int(ann["end"][0]), int(ann["end"][1]) |
| color = (0, 0, 255) # Red in BGR |
| |
| # Draw semi-transparent rectangle |
| overlay = img.copy() |
| cv2.rectangle(overlay, (x1, y1), (x2, y2), color, -1) |
| cv2.addWeighted(overlay, 0.35, img, 0.65, 0, img) |
| cv2.rectangle(img, (x1, y1), (x2, y2), color, 2) |
| |
| if output_path: |
| cv2.imwrite(output_path, img) |
| |
| return img |
| |
| # Example usage |
| visualize_frontiers( |
| "wildos/RGB_rectified/rect_00000.png", |
| "wildos/annotations/annotation_00000.json", |
| "output_visualization.png" |
| ) |
| ``` |
| |
| ### Metadata Mapping |
|
|
| The `metadata.json` file in `RGB_frames/` maps each image index to its source path in the GrandTour dataset: |
|
|
| ```python |
| import json |
| |
| with open("wildos/RGB_frames/metadata.json", "r") as f: |
| metadata = json.load(f) |
| |
| # Find original GrandTour image for a specific frame index |
| original_path = metadata["0"] # e.g., "release_2024-11-03-07-57-34/hdr_front/hdr_front_01342.png" |
| print(f"Original GrandTour path: {original_path}") |
| ``` |
|
|
| ## Related Resources |
|
|
| - **Project Page**: [WildOS: Open-Vocabulary Object Search in the Wild](https://leggedrobotics.github.io/wildos/) |
| - **Source Dataset**: [GrandTour Dataset](https://huggingface.co/datasets/leggedrobotics/grand_tour_dataset) |
|
|
| ## Citation |
|
|
| If you use this dataset in your research, please cite: |
|
|
| ```bibtex |
| @misc{shah2026wildosopenvocabularyobjectsearch, |
| title={WildOS: Open-Vocabulary Object Search in the Wild}, |
| author={Hardik Shah and Erica Tevere and Deegan Atha and Marcel Kaufmann and Shehryar Khattak and Manthan Patel and Marco Hutter and Jonas Frey and Patrick Spieler}, |
| year={2026}, |
| eprint={2602.19308}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.RO}, |
| url={https://arxiv.org/abs/2602.19308}, |
| } |
| ``` |
|
|
| ## License |
|
|
| This dataset is released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). |
|
|