Data from: Multi-species fruit flower detection using a refined semantic segmentation network

<p>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.</p>
<p>Funding provided through ARS Integrated Orchard Management and Automation for Deciduous Tree Fruit Crops. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: AppleA images.</p> <p>File Name: AppleA.zip</p><p>Resource Description: 147 images of an apple tree in bloom acquired with a Canon EOS 60D.</p></li><br><li><p>Resource Title: Training image names from Apple A dataset.</p> <p>File Name: train.txt</p><p>Resource Description: This is a list of filenames used in training; see related paper for details.</p></li><br><li><p>Resource Title: AppleA labels.</p> <p>File Name: AppleA_Labels.zip</p><p>Resource Description: Binary images for the Apple A set, where white represents flower pixels and black, non-flower pixels.<br>
June 25, 2018: 5 files added: 275.png, 316.png, 328.png, 336.png, 369.png.</p></li><br><li><p>Resource Title: Validation image names from Apple A dataset.</p> <p>File Name: val.txt</p><p>Resource Description: This is a list of filenames used in testing; see related paper for details. </p>
<p>June 25, 2018: 5 filenames added.<br>
IMG_0275.JPG
IMG_0316.JPG
IMG_0328.JPG
IMG_0336.JPG
IMG_0369.JPG</p></li><br><li><p>Resource Title: AppleB images.</p> <p>File Name: AppleB.zip</p><p>Resource Description: 15 images of an apple tree in bloom acquired with a GoPro HERO 5.</p>
<p>June 25, 2018: 3 files added.
23.bmp
28.bmp
42.bmp</p></li><br><li><p>Resource Title: AppleB labels.</p> <p>File Name: AppleB_Labels.zip</p><p>Resource Description: Binary images for the Apple B set, where white represents flower pixels and black, non-flower pixels.</p>
<p>June 25, 2018: 3 files added.
23.bmp
28.bmp
42.bmp</p></li><br><li><p>Resource Title: Peach.</p> <p>File Name: Peach.zip</p><p>Resource Description: 20 images of an peach tree in bloom acquired with a GoPro HERO 5.</p>
<p>June 25, 2018: 4 files added.
14.bmp
34.bmp
40.bmp
41.bmp</p></li><br><li><p>Resource Title: Peach labels.</p> <p>File Name: PeachLabels.zip</p><p>Resource Description: Binary images for the Peach set, where white represents flower pixels and black, non-flower pixels.</p>
<p>June 25, 2018: 4 files added.
14.bmp
34.bmp
40.bmp
41.bmp</p></li><br><li><p>Resource Title: Pear.</p> <p>File Name: Pear.zip</p><p>Resource Description: 15 images of a free-standing pear tree in bloom, acquired with a GoPro HERO5.</p>
<p>June 25, 2018:  3 files added.
1_25.bmp
1_62.bmp
2_28.bmp</p></li><br><li><p>Resource Title: Pear labels.</p> <p>File Name: PearLabels.zip</p><p>Resource Description: Binary images for the pear set, where white represents flower pixels and black, non-flower pixels.</p>
<p>June 25, 2018:  3 files added.
1_25.bmp
1_62.bmp
2_28.bmp</p></li><br><li><p>Resource Title: Apple A Labeled images from training set .</p> <p>File Name: AppleALabels_Train.zip</p><p>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.</p></li></ul><p></p>

Tags: algorithm, apple, ars, computer-vision, data-gov, flower, np305, peach, pear, precision-agriculture, segmentation
Organization: Department of Agriculture