Datasets:
image_path
string | detections
sequence | verified
null |
---|---|---|
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image_5.jpg | [
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image_9.jpg | [
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image_19.jpg | [
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image_21.jpg | [
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image_22.jpg | [
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image_33.jpg | [
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image_43.jpg | [
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image_46.jpg | [
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image_47.jpg | [
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image_48.jpg | [
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image_51.jpg | [
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image_91.jpg | [
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image_93.jpg | [
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Rubber Duck Detection Dataset
Overview
This dataset contains 192 annotated images of rubber ducks, specifically curated for object detection tasks. It was used for experimentation related to the YOLOv8n Rubber Duck Detector model.
NOTE: I DO NOT RECOMMEND USING THIS DATASET AT THIS TIME. There is an open and ongoing discussion around the use of the datasets that were combined for this.
See related licensing discussion on the forum
Dataset Description
Dataset Summary
A specialized computer vision dataset featuring rubber ducks with bounding box annotations, designed for training object detection models. The dataset combines and enhances images from two existing datasets with manual verification and standardized annotations.
Supported Tasks
- Object Detection
- Image Classification
Languages
Visual data with English annotations
Dataset Structure
- Number of examples: 192
- Download size: 15,317 bytes
- Dataset size: 23,643 bytes
Data Fields
image_path
: Path to the image filedetections
: Bounding box coordinates in YOLO format (normalized)verified
: Verification status field
Data Splits
- Training set: 192 images
Source Data
Initial Data Collection and Normalization
This dataset combines images from two existing datasets:
- Norod78/Rubber-Duck-blip-captions
- linoyts/rubber_ducks NOTE: these datasets were unlicensed so usage is not clear. See related licensing discussion on the forum
Data Format
Each image has corresponding annotations in two formats:
- YOLO text format (.txt files)
- Structured format in the parquet file
The YOLO format annotations follow the convention:
- All values are normalized between 0 and 1
- Single class: rubber duck
- Coordinates represent the center point and dimensions of the bounding box
File Structure
data/ βββ images/ β βββ image_0.jpg β βββ image_1.jpg β βββ ... βββ labels/ β βββ image_0.txt β βββ image_1.txt β βββ ... βββ train-00000-of-00001.parquet Copy
Dataset Creation
Curation Rationale
This dataset was created to provide a specialized dataset for rubber duck detection, combining images from existing datasets with standardized annotations. The purpose was to see if we could enhance YOLOv8n to be better at detecting an assortment of rubber ducks.
Annotations
Annotations were created using a combination of:
- Manual annotation
- Machine-generated predictions with human verification
- Standardization to YOLO format
Usage
Loading the Dataset
from datasets import load_dataset
dataset = load_dataset("brainwavecollective/yolo-rubber-ducks")
Considerations for Using the Data
Discussion of Biases
- Dataset focuses specifically on strange rubber ducks
- Does not represent all possible variations of rubber ducks
- Limited environmental contexts
- Most of the images have a marketing focus
Additional Information
Dataset Curators
This dataset was curated by combining and enhancing existing rubber duck datasets with additional annotations and verification.
Licensing Information
NOTE: Licensing is currently under review. See related licensing discussion on the forum
Citation Information
If you use this dataset, please cite:
@misc{rubber-duck-detection,
author = {Daniel Ritchie},
title = {Rubber Duck Detection Dataset},
year = {2025},
publisher = {HuggingFace},
journal = {HuggingFace Hub},
howpublished = {\url{https://huggingface.co/datasets/brainwavecollective/yolo-rubber-ducks}}
}
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