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electric-pylon-detection-in-rsi/README.dataset.txt

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+# electric-pylon-detection-in-rsi-q6qra-psut > 2025-03-13 2:55pm
+https://universe.roboflow.com/rf-100-vl/electric-pylon-detection-in-rsi-q6qra-psut
+
+Provided by a Roboflow user
+License: MIT
+
+# Overview
+- [Introduction](#introduction)
+- [Object Classes](#object-classes)
+  - [Pylon](#pylon)
+
+# Introduction
+This dataset focuses on detecting electric pylons in remote sensing imagery. The goal is to accurately identify and annotate pylons from aerial views to assist in infrastructure monitoring and maintenance. The dataset contains one class:
+
+- **Pylon**: Tall structures supporting electrical wires above ground.
+
+# Object Classes
+
+## Pylon
+### Description
+Pylons are tall metal structures distinctively seen from above as linear and grid-like patterns often intersecting fields or open areas. They may appear as interlocking triangular or rectangular patterns with visible legs that cast shadows.
+
+### Instructions
+- Draw bounding boxes tightly around the entire visible structure of the pylon, ensuring that all metallic grid lines are encompassed.
+- If multiple pylons are visible, draw separate bounding boxes for each distinct structure.
+- In case the pylon is occluded by trees or other objects, extend the bounding box to cover the estimated area based on the visible parts.
+- Do not annotate pylons if they are too blurry to be identified with certainty. Avoid labeling if the structure is less distinct and not certain.
+- Ensure no part of the pylon structure extends beyond the bounding box.

electric-pylon-detection-in-rsi/README.roboflow.txt

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+
+electric-pylon-detection-in-rsi-q6qra-psut - v2 2025-03-13 2:55pm
+==============================
+
+This dataset was exported via roboflow.com on March 14, 2025 at 3:09 AM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 1498 images.
+Electric-pylon-detection-in-rsi-q6qra-psut are annotated in COCO format.
+
+The following pre-processing was applied to each image:
+
+No image augmentation techniques were applied.
+
+