The dataset, comprising 1204 meticulously curated images, serves as a comprehensive resource for advancing real-time mosquito detection models. The dataset is strategically divided into training, validation, and test sets, accounting for 87%, 8%, and 5% of the images, respectively. A rigorous preprocessing phase involves auto-orientation and resizing to standardize dimensions at 640x640 pixels. To ensure dataset integrity, the filter null criterion mandates that all images must contain annotations. Augmentations, including flips, rotations, crops, and grayscale applications, enhance the dataset's diversity, fostering robust model training. With a focus on quality and variety, this dataset provides a solid foundation for evaluating and enhancing real-time mosquito detection models.

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