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README.md

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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+---
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+## TTA Dataset: Tidal Turbine Assembly Dataset
+
+This folder contains a sample version of the TTA (Tidal Turbine Assembly) dataset , introduced in our paper "Computer Vision as a Data Source for Digital Twins in Manufacturing: a Sim2Real Pipeline".
+The dataset is designed to support object detection in industrial assembly environments, combining controlled captures, synthetic renderings, and real-world footage desired for test . This version includes a representative subset with annotations for reproducibility and testing purposes.
+TTA is a mixed-data object detection dataset designed for sim-to-real research in industrial assembly environments. It includes spontaneous real-world footage , controlled real data captured via cobot-mounted camera , and domain-randomized synthetic images generated using Unity, targeting seven classes related to tidal turbine components at various stages of assembly. The dataset supports reproducibility and benchmarking for vision-based digital twins in manufacturing.
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6824a993a483759e267a5f43/vLIuDGB3H3Gkw-WTSDehp.png)
+
+## Dataset Card Abstract 
+TTA  contains over 120,000 annotated images across three data types:
+
+-Spontaneous Real Data : Captured from live assembly and disassembly operations, including operator presence with face blurring for privacy, dedicated for test and fine-tuning.
+-Controlled Real Data : 15, 000 Structured scenes recorded under uniform lighting and positioning using a cobot-mounted high-resolution camera.
+-Synthetic Data : 105,000 of auto-labeled images generated using Unity 2022 with domain randomization techniques.
+
+The dataset targets seven object classes representing key turbine components:
+
+-Tidal-turbine
+-Body-assembled
+-Body-not-assembled
+-Hub-assembled
+-Hub-not-assembled
+-Rear-cap-assembled
+-Rear-cap-not-assembled
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+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6824a993a483759e267a5f43/rAPOJSummo6nHgJV5Ra_Y.png)
+
+## Folder Structure Overview
+
+dataset/
+        The full dataset, including video recordings, will be made publicly available upon publication. To ensure reproducibility, the annotations are provided for evaluation purposes.
+├ data_annotation/          # Annotation files and documentation
+
+│     ├── spontaneous_real_data.zip/     # Manual annotations (where available)
+
+│     ├── controlled_real_data.zip/      # Bounding box labels in YOLO format
+
+│     ├── synthetic_data.zip/            # Auto-generated JSON and mask labels
+
+└ README.md                 # This file
+
+## Dataset Description
+data_annotation/
+   
+Contains annotation files for training and evaluation:
+
+🔹 spontaneous_real_data.zip/
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+Semi-automatic annotations where available.
+
+Format:YOLO-compatible .txt files.
+
+🔹 controlled_real_data.zip/
+
+Annotated with YOLO-style bounding boxes.
+
+High-quality labels created semi-automatically using CVAT with AI-assisted tools.
+
+🔹 synthetic_data.zip/
+
+Auto-labeled by Unity with accurate bounding boxes and semantic masks.
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+