Random Superimposed Circles Dataset

Random Superimposed Circles Dataset


Random Superimposed Circles Dataset


Random Circles Dataset

Use Case

Random Circles Dataset


Explore the Random Superimposed Circles Dataset, featuring high-quality public domain landscape images with randomly placed circles.

Random Superimposed Circles Dataset


The Random Circles Dataset is designed to facilitate the development of neural networks capable of detecting the coordinates of circles superimposed on images. This dataset consists of various public domain landscape images, each featuring a randomly placed circle. The primary goal is to train models to accurately identify the position and size of these circles within the images.

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Dataset Composition:

  • Images: A collection of high-quality landscape images from the public domain.
  • Annotations: Each image contains a single circle superimposed at a random location.

Label Format:

  • The labels for each image are provided in a straightforward text format.
  • Line 1: x-coordinate of the circle’s center (in pixels, integer value).
  • Line 2: y-coordinate of the circle’s center (in pixels, integer value).
  • Line 3: Radius of the circle (in pixels, integer value).

Usage: This dataset is ideal for training and testing neural networks focused on object detection tasks, specifically for identifying circular shapes. The provided labels enable precise training, allowing models to learn how to detect and size circles accurately.

Potential Applications:

  • Object detection model training.
  • Computer vision research and development.
  • Educational purposes for learning object detection techniques.

Key Challenge: Developing a neural network that can accurately determine the position (x, y) and radius of the circles in the images, testing the model’s precision and robustness.

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