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

bee_dataset/bee_dataset_200
FeaturesDict({
'input': Image(shape=(200, 100, 3), dtype=uint8),
'output': FeaturesDict({
'cooling_output': float64,
'pollen_output': float64,
'varroa_output': float64,
'wasps_output': float64,
}),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
input |
Image |
(200, 100, 3) |
uint8 |
|
output |
FeaturesDict |
|
|
|
output/cooling_output |
Tensor |
|
float64 |
|
output/pollen_output |
Tensor |
|
float64 |
|
output/varroa_output |
Tensor |
|
float64 |
|
output/wasps_output |
Tensor |
|
float64 |
|

bee_dataset/bee_dataset_150
FeaturesDict({
'input': Image(shape=(150, 75, 3), dtype=uint8),
'output': FeaturesDict({
'cooling_output': float64,
'pollen_output': float64,
'varroa_output': float64,
'wasps_output': float64,
}),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
input |
Image |
(150, 75, 3) |
uint8 |
|
output |
FeaturesDict |
|
|
|
output/cooling_output |
Tensor |
|
float64 |
|
output/pollen_output |
Tensor |
|
float64 |
|
output/varroa_output |
Tensor |
|
float64 |
|
output/wasps_output |
Tensor |
|
float64 |
|

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Last updated 2022-11-23 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-11-23 UTC."],[],[],null,["# bee_dataset\n\n\u003cbr /\u003e\n\n- **Description**:\n\nThis dataset contains images and a set of labels that expose certain\ncharacterisitics of that images, such as *varroa-mite* infections, bees carrying\n*pollen-packets* or bee that are *cooling the hive* by flappingn their wings.\nAdditionally, this dataset contains images of *wasps* to be able to distinguish\nbees and wasps.\n\nThe images of the bees are taken from above and rotated. The bee is vertical and\neither its head or the trunk is on top. All images were taken with a green\nbackground and the distance to the bees was always the same, thus all bees have\nthe same size.\n\nEach image can have multiple labels assigned to it. E.g. a bee can be cooling\nthe hive and have a varrio-mite infection at the same time.\n\nThis dataset is designed as mutli-label dataset, where each label, e.g.\n*varroa_output*, contains 1 if the characterisitic was present in the image and\na 0 if it wasn't. All images are provided by 300 pixel height and 150 pixel\nwitdh. As default the dataset provides the images as 150x75 (h,w) pixel. You can\nselect 300 pixel height by loading the datset with the name\n\"bee_dataset/bee_dataset_300\" and with 200 pixel height by\n\"bee_dataset/bee_dataset_200\".\n\nLicense: GNU GENERAL PUBLIC LICENSE\n\nAuthor: Fabian Hickert [Fabian.Hickert@raspbee.de](mailto:Fabian.Hickert@raspbee.de)\n\n- **Homepage** : \u003chttps://raspbee.de\u003e\n\n- **Source code** :\n [`tfds.datasets.bee_dataset.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/bee_dataset/bee_dataset_dataset_builder.py)\n\n- **Versions**:\n\n - **`1.0.0`** (default): No release notes.\n- **Download size** : `192.39 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 7,490 |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('input', 'output')`\n\n- **Citation**:\n\n @misc{BeeAlarmed - A camera based bee-hive monitoring,\n title = \"Dataset for a camera based bee-hive monitoring\",\n url={https://github.com/BeeAlarmed}, journal={BeeAlarmed},\n author = \"Fabian Hickert\",\n year = \"2021\",\n NOTE = \"\\url{https://raspbee.de/} and \\url{https://github.com/BeeAlarmed/BeeAlarmed}\"\n }\n\nbee_dataset/bee_dataset_300 (default config)\n--------------------------------------------\n\n- **Config description**: BeeDataset images with 300 pixel height and 150\n pixel width\n\n- **Dataset size** : `97.96 MiB`\n\n- **Feature structure**:\n\n FeaturesDict({\n 'input': Image(shape=(300, 150, 3), dtype=uint8),\n 'output': FeaturesDict({\n 'cooling_output': float64,\n 'pollen_output': float64,\n 'varroa_output': float64,\n 'wasps_output': float64,\n }),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|-----------------------|--------------|---------------|---------|-------------|\n| | FeaturesDict | | | |\n| input | Image | (300, 150, 3) | uint8 | |\n| output | FeaturesDict | | | |\n| output/cooling_output | Tensor | | float64 | |\n| output/pollen_output | Tensor | | float64 | |\n| output/varroa_output | Tensor | | float64 | |\n| output/wasps_output | Tensor | | float64 | |\n\n- **Figure** ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nbee_dataset/bee_dataset_200\n---------------------------\n\n- **Config description**: BeeDataset images with 200 pixel height and 100\n pixel width\n\n- **Dataset size** : `55.48 MiB`\n\n- **Feature structure**:\n\n FeaturesDict({\n 'input': Image(shape=(200, 100, 3), dtype=uint8),\n 'output': FeaturesDict({\n 'cooling_output': float64,\n 'pollen_output': float64,\n 'varroa_output': float64,\n 'wasps_output': float64,\n }),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|-----------------------|--------------|---------------|---------|-------------|\n| | FeaturesDict | | | |\n| input | Image | (200, 100, 3) | uint8 | |\n| output | FeaturesDict | | | |\n| output/cooling_output | Tensor | | float64 | |\n| output/pollen_output | Tensor | | float64 | |\n| output/varroa_output | Tensor | | float64 | |\n| output/wasps_output | Tensor | | float64 | |\n\n- **Figure** ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nbee_dataset/bee_dataset_150\n---------------------------\n\n- **Config description**: BeeDataset images with 200 pixel height and 100\n pixel width\n\n- **Dataset size** : `37.43 MiB`\n\n- **Feature structure**:\n\n FeaturesDict({\n 'input': Image(shape=(150, 75, 3), dtype=uint8),\n 'output': FeaturesDict({\n 'cooling_output': float64,\n 'pollen_output': float64,\n 'varroa_output': float64,\n 'wasps_output': float64,\n }),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|-----------------------|--------------|--------------|---------|-------------|\n| | FeaturesDict | | | |\n| input | Image | (150, 75, 3) | uint8 | |\n| output | FeaturesDict | | | |\n| output/cooling_output | Tensor | | float64 | |\n| output/pollen_output | Tensor | | float64 | |\n| output/varroa_output | Tensor | | float64 | |\n| output/wasps_output | Tensor | | float64 | |\n\n- **Figure** ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]