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claytonsds
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UTM_Detection_Dataset

Tasks:
Image Segmentation
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Languages:
Portuguese
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1K<n<10K
Tags:
object-detection
u-tube-manometer
gauge-reader
water-column
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DOI UTM Dataset UTM Detection Dataset

Dataset Description

This dataset was created to support Article: VisionGauge: a computer vision model to detect and read U-tube manometers.

It consists of images of U-tube manometers constructed using a transparent PVC water level hose (5/16" × 1 mm) and flexible measuring tapes of different colors, each with a length of 150 cm (60 inches). The manometric fluids represented in the dataset include water, oil, and dyed water, and the dataset is intended for computer vision object detection tasks, specifically targeting the detection of liquid column levels.

The dataset includes 8889 images, and all annotations were performed using the RoboFlow Annotate Tool.

Dataset Split

  • Training set: 6253 images (70%)
  • Validation set: 1758 images (20%)
  • Test set: 878 images (10%)

Data Structure

The dataset follows a standard split structure:

dataset/
├── train/
│   ├── images/
│   │   ├── image5214.jpg
│   │   └── ...
│   └── labels/
│       ├── image5214.txt
│       └── ...
├── valid/
│   ├── images/
│   │   ├── image3710.jpg
│   │   └── ...
│   └── labels/
│       ├── image3710.txt
│       └── ...
└── test/
│   ├── images/
│   │   ├── image18313.jpg
│   │   └── ...
│   └── labels/
│       ├── image18313.txt
│       └── ...
└── data.yaml
  • The dataset includes TXT annotations and a YAML configuration file compatible with YOLOv8.

License

This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. You are free to share and adapt the material, provided you give appropriate credit and distribute any derivative works under the same license. For details, see the LICENSE file.

Citation 

@misc{santos2026utm,
    author    = {Santos, C.S. and Arima, M. N.},
    title     = {{UTM Detection Dataset}},
    year      = {2026},
    month     = {jan},
    publisher = {Hugging Face},
    doi       = {10.57967/hf/7783},
    url       = {https://huggingface.co/datasets/claytonsds/UTM_Detection_Dataset}
}
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