Datasets:
Tasks:
Object Detection
Modalities:
Image
Formats:
parquet
Size:
1K - 10K
Tags:
object-detection
License:
Search is not available for this dataset
image imagewidth (px) 1.28k 1.28k | image_id int64 0 1.56k | width int32 1.28k 1.28k | height int32 720 720 | objects dict |
|---|---|---|---|---|
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End of preview. Expand in Data Studio
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
from datasets import load_dataset
dataset = load_dataset("blackbeedrones/bb-challenge-boxes")
example = dataset["train"][0]
print(example["objects"])
Use with Nectar SDK
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
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