PhysiSens : Real Time Physics Lab Instrument Image Dataset

The "PhysiSens" dataset contains 5,185 annotated images of physics instrument sourced from the Physics Lab Support Room, the United International University (UIU). This dataset was specifically designed to facilitate the development and validation of machine learning models for the real-time detection of physics instrument. To mimic real-world scenarios and enhance the robustness of models trained on this data, images were captured under varied lighting conditions and against diverse backgrounds. Each electronic component was photographed from multiple angles, and following collection, images were standardized through auto-orientation and resized to 640x640 pixels, introducing augmentation increases brightness (0 to 20%) . The dataset is organized into 20 distinct classes of commonly used physics instrument. The dataset were split into training (70%), validation (20%), and test (10%) sets. For textual reasoning generation each image is linked with a natural language reasoning statement that explains the lab instrument . A BLIP model was used to generate these explanations, achieving strong performance on BLEU, BERTScore, and ROUGE-L metrics.