Lemon dataset has been prepared to investigate the possibilities to tackle the issue of fruit quality control. It contains 2690 annotated images (1056 x 1056 pixels). Raw lemon images have been captured using the procedure described in the following blogpost and manually annotated using CVAT.
Here's an example of raw unannotated data:
and some annotated samples:
| Name | Attribute | Type | Default | Description | Example |
|---|---|---|---|---|---|
| condition | healthy | boolean | true | Determine whether the fruit is healthy. If not regions with identified issues are annotated |  |
| condition | greening | boolean | false | Determine whether the fruit contains areas that are not uniformly yellow and have green areas. |  |
| image_quality | blurry | boolean | false | Fruit image is blurry |  |
| image_quality | cropped | boolean | false | Not all fruit parts are on the image |  |
| image_quality | unnatural_color | boolean | false | There are issues with color representation. |  |
| image_quality | no_data | boolean | false | There are black spots on the fruit image that do not contain data. |  |
| illness | - | region | - | - |    |
| gangrene | - | region | - | - |  |
| mould | - | region | - | - |  |
| blemish | artificial | region + boolean | - | - |   |
| dark_style_remains | - | region | - | After pollination the remains of style are preserved in the fruit. A dark area around the remain of style indicates an unhealthy fruit. This place is the region from which the fruit starts rotting or catches mould. |   |
| pedicel | - | region | - | Pedicel refers to a structure connecting a single flower to its inflorescence. |  |
| artifact | - | region | - | Image contains artifacts i.e. regions that are not related to a fruit and are a result of wrong image processing. Those regions should be identified and described. |  |
You will notice that file names are composed to form a specific identifier e.g.:
0037_G_I_120_A: 0037 (individual fruit instance), 120 (relative photo angle), A (photo position). Some of them are restricted to the original project and cannot be published.
| File | Format | Version |
|---|---|---|
| Lemon Dataset | COCO | v1 |
COCO API can be utilized to read the dataset.
from pycocotools.coco import COCO
coco = COCO('../lemon-dataset/annotations/instances_default.json')If you use the lemons data set in a scientific publication, we would appreciate references to the following paper:
Biblatex entry:
@misc{softwaremill_2020,
author = {Maciej Adamiak},
title = {Lemons quality control dataset},
institution = {SoftwareMill},
month = jul,
year = 2020,
doi = {10.5281/zenodo.3965568},
url = {https://github.com/softwaremill/lemon-dataset}
}MIT License
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