Beehive Scene Recognition Dataset

The current agricultural industry faces the challenge of insufficient monitoring of beehive scenes. Traditional beekeeping management methods often rely on manual observation, which is inefficient and prone to errors. Existing solutions, although having introduced some image recognition technologies, still have limitations such as low accuracy and poor real-time performance. This dataset aims to address the issues of recognition accuracy and real-time performance in target detection by providing high-quality beehive scene images and annotations. The dataset includes 15,000 annotated beehive scene images, utilizing advanced image acquisition technologies and processing workflows. Image collection is conducted using high-resolution cameras in real beekeeping environments, ensuring data authenticity and diversity. Additionally, quality control of the data is ensured through multiple rounds of annotation and consistency checks, with each annotation being reviewed by experts. The data is stored in JPEG format with a clear organizational structure for easy subsequent use.