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license: mit
task_categories:
- image-segmentation
- object-detection
tags:
- P&ID
- lines
- pipelines
- engineering
- diagrams
- line-detection
size_categories:
- 1K<n<10K
---
# P&ID Line Detection Dataset
This dataset contains cropped images from P&ID (Piping and Instrumentation Diagrams)
with line segment annotations for line detection and segmentation tasks.
## Dataset Description
- **Total source images:** 500
- **Total cropped samples:** 10000
- **Total line segments:** 44754
- **Crops per image:** 20
- **Image sizes:** Various sizes under 1000px (e.g., 300x500, 512x768, 900x900)
## Dataset Structure
Each sample contains:
- `file_name`: Image filename
- `source_image_idx`: Index of the original P&ID image
- `crop_idx`: Index of this crop from the source image
- `width`: Crop width in pixels
- `height`: Crop height in pixels
- `lines`: Dictionary with:
- `segments`: List of line segments as [x1, y1, x2, y2] (start and end points)
- `line_types`: List of line types ("solid" or "dashed")
- `pipelines`: List of pipeline names for each line
## Usage
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("imagefolder", data_dir="path/to/lines_dataset")
# Access a sample
sample = dataset["train"][0]
image = sample["image"]
lines = sample["lines"]
segments = lines["segments"] # [[x1, y1, x2, y2], ...]
line_types = lines["line_types"] # ["solid", "dashed", ...]
pipelines = lines["pipelines"] # ["5\"-EK-2648", ...]
# Draw lines on image
from PIL import ImageDraw
draw = ImageDraw.Draw(image)
for seg in segments:
x1, y1, x2, y2 = seg
draw.line([(x1, y1), (x2, y2)], fill="blue", width=3)
image.show()
```
## Line Segment Format
Each line segment is represented as `[x1, y1, x2, y2]` where:
- `(x1, y1)` is the start point
- `(x2, y2)` is the end point
- Coordinates are in pixels, relative to the cropped image
- Only lines where **both endpoints** are fully inside the crop are included
## Line Types
- `solid`: Continuous pipeline lines
- `dashed`: Dashed lines (often representing signal/instrument lines)
## License
MIT License
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