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bee_dataset

  • Description:

This dataset contains images and a set of labels that expose certain characterisitics of that images, such as varroa-mite infections, bees carrying pollen-packets or bee that are cooling the hive by flappingn their wings. Additionally, this dataset contains images of wasps to be able to distinguish bees and wasps.

The images of the bees are taken from above and rotated. The bee is vertical and either its head or the trunk is on top. All images were taken with a green background and the distance to the bees was always the same, thus all bees have the same size.

Each image can have multiple labels assigned to it. E.g. a bee can be cooling the hive and have a varrio-mite infection at the same time.

This dataset is designed as mutli-label dataset, where each label, e.g. varroa_output, contains 1 if the characterisitic was present in the image and a 0 if it wasn't. All images are provided by 300 pixel height and 150 pixel witdh. As default the dataset provides the images as 150x75 (h,w) pixel. You can select 300 pixel height by loading the datset with the name "bee_dataset/bee_dataset_300" and with 200 pixel height by "bee_dataset/bee_dataset_200".

License: GNU GENERAL PUBLIC LICENSE

Author: Fabian Hickert Fabian.Hickert@raspbee.de

Split Examples
'train' 7,490
@misc{BeeAlarmed - A camera based bee-hive monitoring,
  title =   "Dataset for a camera based bee-hive monitoring",
  url={https://github.com/BeeAlarmed}, journal={BeeAlarmed},
  author =  "Fabian Hickert",
  year   =  "2021",
  NOTE   = "\url{https://raspbee.de/} and \url{https://github.com/BeeAlarmed/BeeAlarmed}"
}

bee_dataset/bee_dataset_300 (default config)

  • Config description: BeeDataset images with 300 pixel height and 150 pixel width

  • Dataset size: 97.96 MiB

  • Feature structure:

FeaturesDict({
    'input': Image(shape=(300, 150, 3), dtype=tf.uint8),
    'output': FeaturesDict({
        'cooling_output': tf.float64,
        'pollen_output': tf.float64,
        'varroa_output': tf.float64,
        'wasps_output': tf.float64,
    }),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
input Image (300, 150, 3) tf.uint8
output FeaturesDict
output/cooling_output Tensor tf.float64
output/pollen_output Tensor tf.float64
output/varroa_output Tensor tf.float64
output/wasps_output Tensor tf.float64

Visualization

bee_dataset/bee_dataset_200

  • Config description: BeeDataset images with 200 pixel height and 100 pixel width

  • Dataset size: 55.48 MiB

  • Feature structure:

FeaturesDict({
    'input': Image(shape=(200, 100, 3), dtype=tf.uint8),
    'output': FeaturesDict({
        'cooling_output': tf.float64,
        'pollen_output': tf.float64,
        'varroa_output': tf.float64,
        'wasps_output': tf.float64,
    }),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
input Image (200, 100, 3) tf.uint8
output FeaturesDict
output/cooling_output Tensor tf.float64
output/pollen_output Tensor tf.float64
output/varroa_output Tensor tf.float64
output/wasps_output Tensor tf.float64

Visualization

bee_dataset/bee_dataset_150

  • Config description: BeeDataset images with 200 pixel height and 100 pixel width

  • Dataset size: 37.43 MiB

  • Feature structure:

FeaturesDict({
    'input': Image(shape=(150, 75, 3), dtype=tf.uint8),
    'output': FeaturesDict({
        'cooling_output': tf.float64,
        'pollen_output': tf.float64,
        'varroa_output': tf.float64,
        'wasps_output': tf.float64,
    }),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
input Image (150, 75, 3) tf.uint8
output FeaturesDict
output/cooling_output Tensor tf.float64
output/pollen_output Tensor tf.float64
output/varroa_output Tensor tf.float64
output/wasps_output Tensor tf.float64

Visualization