ChemEq25: A Novel Multiclass Dataset for Detecting Chemical Laboratory Apparatus Using Deep Learning Approach

The "ChemEq25" dataset comprises 4,599 annotated images of chemical laboratory equipment, collected from three locations: Bangladesh Atomic Energy Chemical Lab, Biochemical Laboratory of United International University, and Chemistry Laboratory of Dhaka Imperial College. Designed for machine learning applications, it supports real-time equipment detection. Images were captured under varying lighting and backgrounds to enhance model robustness. Each item was photographed from multiple angles, auto-oriented, and resized to 640x640 pixels, introducing slight stretching. The dataset includes 25 classes of common lab equipment, divided into training (70%), validation (20%), and test (10%) sets.