Infusion Bottles and Bags Object Detection Image Dataset

The current medical industry faces challenges in identifying and managing infusion bottles and bags during use, particularly in high-intensity clinical environments where manual identification is prone to errors, resulting in improper medication administration to patients. Existing solutions often rely on manual inspection, which is inefficient and has a high error rate. This dataset aims to assist researchers and developers in building more accurate automated recognition systems by providing high-quality object detection image data, thereby improving the safety and efficiency of clinical operations. The dataset includes images of infusion bottles and bags taken in actual hospital settings, collected using high-resolution cameras to ensure image clarity and detail representation. After data collection, multiple rounds of annotation and expert review were conducted to ensure consistency and accuracy of annotations. The data is stored in JPG format with a clear organizational structure, facilitating further processing and analysis.