Datasets:
Tasks:
Object Detection
Modalities:
Image
Formats:
parquet
Size:
1K - 10K
Tags:
object-detection
License:
| license: apache-2.0 | |
| task_categories: | |
| - object-detection | |
| tags: | |
| - object-detection | |
| size_categories: | |
| - 1K<n<10K | |
| pretty_name: Bb Challenge Boxes | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| - split: test | |
| path: data/test-* | |
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: image_id | |
| dtype: int64 | |
| - name: width | |
| dtype: int32 | |
| - name: height | |
| dtype: int32 | |
| - name: objects | |
| struct: | |
| - name: id | |
| sequence: int64 | |
| - name: bbox | |
| sequence: | |
| sequence: float32 | |
| length: 4 | |
| - name: category | |
| sequence: | |
| class_label: | |
| names: | |
| '0': box | |
| - name: area | |
| sequence: float64 | |
| # Bb Challenge Boxes | |
| Object detection dataset hosted at `blackbeedrones/bb-challenge-boxes`. | |
| ## Dataset Structure | |
| | Split | Images | | |
| |-------|--------| | |
| | train | 1565 | | |
| | validation | 149 | | |
| | test | 75 | | |
| **Total images:** 1789 | |
| **Classes:** `box` | |
| **Annotation format:** COCO bbox `[x_min, y_min, width, height]`. | |
| ## Usage | |
| ### Load with HuggingFace Datasets | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("blackbeedrones/bb-challenge-boxes") | |
| example = dataset["train"][0] | |
| print(example["objects"]) | |
| ``` | |
| ### Use with Nectar SDK | |
| ```python | |
| from nectar.ai.detection.datasets import HuggingFaceHandler | |
| handler = HuggingFaceHandler("data/local") | |
| handler.download(repo_id="blackbeedrones/bb-challenge-boxes", format_type="coco") | |
| # data/local now contains train/_annotations.coco.json and image files | |
| ``` | |