TTA: Tidal Turbine Assembly Images for Sim2Real Object Detection

The TTA (Tidal Turbine Assembly) dataset is a sample version introduced in the paper 'Computer Vision as a Data Source for Digital Twins in Manufacturing: a Sim2Real Pipeline'. It is designed for object detection in industrial assembly environments, combining controlled captures, synthetic renderings, and real-world footage. The dataset was created by NeFr25 and last updated on Hugging Face on 2026-04 13.

Use Cases

• Train object detection models based on the described combination of synthetic and real industrial imagery.
• Benchmark Sim2Real transfer performance based on the dataset's controlled, synthetic, and real-world footage.
• Develop digital twin visual components for manufacturing based on the industrial assembly environment focus.

Strengths

• Dataset is designed for a specific, documented research purpose as described in the associated paper.
• Combines multiple data sources (controlled captures, synthetic renderings, real-world footage) as mentioned in the description.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count, column definitions, and file formats are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

NeFr25 on Hugging Face.

Collection Method

Likely contains controlled captures, synthetic renderings, and real-world footage as described.

Time Range

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Freshness

Last updated 2026-04-13 15:09:37; freshness should be verified.

Geography

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