LogoLogo
HomeDocumentationProjectsForumStudio
  • Edge Impulse Datasets
  • Image
    • Image Classification
      • Fire extinguisher safety pin
      • Microscope
    • Object Detection
      • Bottles rack
      • Cans on conveyor belt
      • Cubes colors on conveyor belt
      • Dice
      • Dice colors
      • Self Attention - Cubes on conveyor belt
    • Visual Anomaly Detection
      • Capsule
      • DHT11
      • Fire extinguisher head thread
      • Flat washers
      • Thermostatic valves
    • Visual Regression
      • Vial tubes
  • Audio
    • Audio Classification
      • Faucet vs noise
      • Glass breaking
      • Keyword Spotting
  • Time-series
    • Motion and Vibration Classification
      • Coffee machine stages
      • Continuous motion recognition
    • Sensor Fusion Classification
      • Coffee machine stages
Powered by GitBook
On this page
  • Description
  • Compatible Blocks
  • Dataset Details
  • Usage
  • Citation
Export as PDF
  1. Image
  2. Visual Anomaly Detection

DHT11

PreviousCapsuleNextFire extinguisher head thread

Last updated 2 months ago

Task: Visual Anomaly Detection

License: BSD 3-Clause Clear

Description

This dataset has been collected by Edge Impulse teams and contains a single DHT11 sensor, centered in the frame, with a similar size and a uniform background.

The training dataset only contains "nominal" (no anomaly) images whereas the testing dataset contains both nominal and anomalous images.

The DHT11 have been used to teach IoT classes in the past and have been manipulated by students extensively. When not wiring the pins properly, it can cause an overheat which often lead to the plastic melting. Some other anomalous images are missing wiring pins.

Compatible Blocks

  • Feature extraction: Image

  • Learning block: Visual Anomaly Detection (FOMO-AD)

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

Dataset Details

  • Total Data Items: 195

  • Labeling Method: single label

  • Train/Test Split: 69.74% / 30.26%

Training Set

Testing Set

Total Data Items

136

59

Labels

no anomaly

anomaly, no anomaly

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

Citation

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

@misc{edgeimpulse_dataset_497422,
    title = {Visual Anomaly Detection - DHT11},
    author = {Edge Impulse},
    year = {2024},
    url = {https://studio.edgeimpulse.com/public/497422/latest},
    note = {Apache 2.0}
}
Dataset Screenshot