Data-Set-Generator

Generating data set to train a neural network

Screen Defects Detection Dataset

Overview

This repository contains a synthetic dataset for training a neural network to identify screen defects. The dataset includes three types of defects: bubbles, scratches, and dirt stains. Each image in the dataset is labeled with its corresponding defect type.

Dataset Generation

The dataset is generated using Python and OpenCV. The data_set_generator.py script creates synthetic images with defects such as ellipses for bubbles, irregular lines for scratches, and blob-like shapes for dirt stains.

Usage

• The data_set_generator.py script can be modified to adjust the parameters of the synthetic dataset generation.
• The generated dataset can be used to train and test a neural network for screen defect detection.

Dataset Structure

The dataset is organized into two main folders:

• images: Contains the generated images.
• labels: Contains the corresponding labels for each image.

Getting Started

1. Clone the repository:

   git clone https://github.com/your-username/screen-defects-dataset.git
   cd screen-defects-dataset