Valve and Rect Computer Vision Project
Symbol Detection
Updated 5 months ago
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* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Grayscale (CRT phosphor)
* Random rotation of between -45 and +45 degrees
* Resize to 2048x2048 (Fit (white edges))
* Salt and pepper noise was applied to 1 percent of pixels
* collaborate with your team on computer vision projects
* understand and search unstructured image data
* use active learning to improve your dataset over time
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==============================
For state of the art Computer Vision training notebooks you can use with this dataset,
PNID are annotated in YOLOv8 format.
The dataset includes 189 images.
The following augmentation was applied to create 3 versions of each source image:
The following pre-processing was applied to each image:
The following transformations were applied to the bounding boxes of each image:
visit https://github.com/roboflow/notebooks
A description for this project has not been published yet.
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Cite This Project
LICENSE
CC BY 4.0 If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
valve-and-rect_dataset,
title = { Valve and Rect Dataset },
type = { Open Source Dataset },
author = { Symbol Detection },
howpublished = { \url{ https://universe.roboflow.com/symbol-detection-boj78/valve-and-rect } },
url = { https://universe.roboflow.com/symbol-detection-boj78/valve-and-rect },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jun },
note = { visited on 2024-11-24 },
}