Data from: Multi-species fruit flower detection using a refined semantic segmentation network
This dataset consists of four sets of flower images, from three different species: apple, peach, and pear, and accompanying ground truth images. The images were acquired under a range of imaging conditions. These datasets support work in an accompanying paper that demonstrates a flower identification algorithm that is robust to uncontrolled environments and applicable to different flower species. While this data is primarily provided to support that paper, other researchers interested in flower detection may also use the dataset to develop new algorithms. Flower detection is a problem of interest in orchard crops because it is related to management of fruit load.
Funding provided through ARS Integrated Orchard Management and Automation for Deciduous Tree Fruit Crops.
Resources in this dataset:
Resource Title: AppleA images.
File Name: AppleA.zip
Resource Description: 147 images of an apple tree in bloom acquired with a Canon EOS 60D.
Resource Title: Training image names from Apple A dataset.
File Name: train.txt
Resource Description: This is a list of filenames used in training; see related paper for details.
Resource Title: AppleA labels.
File Name: AppleA_Labels.zip
Resource Description: Binary images for the Apple A set, where white represents flower pixels and black, non-flower pixels.
June 25, 2018: 5 files added: 275.png, 316.png, 328.png, 336.png, 369.png.Resource Title: Validation image names from Apple A dataset.
File Name: val.txt
Resource Description: This is a list of filenames used in testing; see related paper for details.
June 25, 2018: 5 filenames added.
IMG_0275.JPG IMG_0316.JPG IMG_0328.JPG IMG_0336.JPG IMG_0369.JPGResource Title: AppleB images.
File Name: AppleB.zip
Resource Description: 15 images of an apple tree in bloom acquired with a GoPro HERO 5.
June 25, 2018: 3 files added. 23.bmp 28.bmp 42.bmp
Resource Title: AppleB labels.
File Name: AppleB_Labels.zip
Resource Description: Binary images for the Apple B set, where white represents flower pixels and black, non-flower pixels.
June 25, 2018: 3 files added. 23.bmp 28.bmp 42.bmp
Resource Title: Peach.
File Name: Peach.zip
Resource Description: 20 images of an peach tree in bloom acquired with a GoPro HERO 5.
June 25, 2018: 4 files added. 14.bmp 34.bmp 40.bmp 41.bmp
Resource Title: Peach labels.
File Name: PeachLabels.zip
Resource Description: Binary images for the Peach set, where white represents flower pixels and black, non-flower pixels.
June 25, 2018: 4 files added. 14.bmp 34.bmp 40.bmp 41.bmp
Resource Title: Pear.
File Name: Pear.zip
Resource Description: 15 images of a free-standing pear tree in bloom, acquired with a GoPro HERO5.
June 25, 2018: 3 files added. 1_25.bmp 1_62.bmp 2_28.bmp
Resource Title: Pear labels.
File Name: PearLabels.zip
Resource Description: Binary images for the pear set, where white represents flower pixels and black, non-flower pixels.
June 25, 2018: 3 files added. 1_25.bmp 1_62.bmp 2_28.bmp
Resource Title: Apple A Labeled images from training set .
File Name: AppleALabels_Train.zip
Resource Description: Binary images for the Apple A set, where white represents flower pixels and black, non-flower pixels. These images form the training set. Resource added August 20, 2018. User noted that this resource was missing.
Funding
USDA-ARS
History
Data contact name
Tabb, AmyData contact email
amy.tabb@ars.usda.govPublisher
Ag Data CommonsIntended use
The primary intended use of the dataset is as supplementary material for the accompanying paper. However, the data can also be used to develop new algorithms for flower or general object detection.Temporal Extent Start Date
2016-01-01Temporal Extent End Date
2017-12-31Theme
- Not specified
Geographic Coverage
{"type":"FeatureCollection","features":[{"geometry":{"type":"Point","coordinates":[-77.87,39.35]},"type":"Feature","properties":{}}]}ISO Topic Category
- farming
National Agricultural Library Thesaurus terms
data collection; flowers; apples; peaches; pears; image analysis; algorithms; orchards; crops; computer vision; precision agricultureOMB Bureau Code
- 005:18 - Agricultural Research Service
OMB Program Code
- 005:040 - National Research
ARS National Program Number
- 305
Pending citation
- No
Public Access Level
- Public