Pollen detection dataset

Overview This dataset is about corbicular pollen loads as foraged by honey bees (apis mellifera). Pollen were obtained by using pollen traps and show a wide range of colors. A total of 12568 (training) and 1629 (validation) pollen were annotated on 64 (training) and 5 images (validation), respectively. The images were partly from photographs and partly from scanned pollen. From these images, 96x96 pixel images were randomly cropped and augmented. Suitable masks were also created and saved together with the corresponding images and csv files. These cropped images form the given data set. File structure train/ train/imgs/ 495k images contain a total of 1410991 pollen. Images have shape (96px * 96px * 3 channels). Details on augmentation can be found in README.md. ~20% of the images show no pollen. Mathematically, each labeled pollen appears on 112 images in the data set. train/imgs/masks For each image exists a binary mask suitable for U-net training. The mask is not a real segmentation, but a white circle marking the center of the pollen. Each white circle has a black border that guarantees that no white circles overlap. This helps the U-net to learn the separation of the pollen segmentations, which simplifies the detection of blobs or local maxima on the output map of the U-net. train/imgs/coords For each image exists a .csv file with the annotated pollen centers. val/ val/imgs/ 50k images contain a total of 284125 pollen. Images have shape (96px * 96px * 3 channels). Details on augmentation can be found in README.md.. ~20% of the images show no pollen. Mathematically, each labeled pollen appears on 108 images in the data set. val/imgs/masks For each image exists a binary mask suitable for U-net training. The mask is not a real segmentation, but a white circle marking the center of the pollen. Each white circle has a black border that guarantees that no white circles overlap. This helps the U-net to learn the separation of the pollen segmentations, which simplifies the detection of blobs or local maxima on the output map of the U-net. val/imgs/coords For each image exists a .csv file with the annotated pollen centers.

搜集汇总

背景与挑战

背景概述

该数据集包含蜜蜂采集的花粉负载图像，提供96x96像素的裁剪图像、二进制掩码和坐标文件，适用于U-net训练和花粉检测研究。数据集分为训练集和验证集，分别包含12568和1629个花粉标注，图像来源于照片和扫描。