Bottles rack

Task: Object Detection

License: Apache 2.0

Description

This dataset has been collected by Edge Impulse teams and contains images of bottle racks on different backgrounds and different orientations. It can be used to count the number of beers in the rack. The two labels - empty or full - is used to distinguish if the beer has a cap or not.

Compatible Blocks

• Feature extraction: Image

• Learning block: Object Detection, NVIDIA TAO,

Not sure what to choose? Try out this dataset with the EON Tuner.

Dataset Details

• Total Data Items: 130

• Labeling Method: object detection

• Train/Test Split: 74.62% / 25.38%

Usage

• Clone the public project.

  To clone and use this project, visit the Edge Impulse Studio link, click on the Clone button on the top-right corner and follow the cloning instructions.

• Download

  • Direct link

  • HuggingFace - Soon

  • Kaggle - Soon

• Import this dataset to your Edge Impulse project

  This project uses the Edge Impulse Exporter Format (info.labels). See this documentation page for more info.

  Edge Impulse also supports different data sample formats and dataset annotation formats that you can import into your project to build your edge AI models:

  • Studio uploader

  • CLI uploader

  • CSV Wizard

  • Python SDK

  • Ingestion API

  • Import from S3 buckets

  • Upload portals (Enterprise feature)

Citation

If you use this dataset in your research paper, please cite it using the following BibTeX:

@misc{edgeimpulse_dataset_497424,
    title = {Object Detection - Bottles rack},
    author = {Edge Impulse},
    year = {2024},
    url = {https://studio.edgeimpulse.com/public/497424/latest},
    note = {Apache 2.0}
}