cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34808/s8ga-g431
title: Tagged images with LEGO bricks - Bricks Curved

description: The set contains images of LEGO bricks (from Bricks Curved category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/t1zt-h431
title: Tagged images with LEGO bricks - Transportation - Land

description: The set contains images of LEGO bricks (from Transportation - Land category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/xqf1-9030
title: Tagged images with LEGO bricks - Tiles Special

description: The set contains images of LEGO bricks (from Tiles Special category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.15468/dl.kgmjgw
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nepeta balouchestanica Jamzad & Ingr."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046771-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/86w1-ck82
title: Tagged images with LEGO bricks - Technic Special

description: The set contains images of LEGO bricks (from Technic Special category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/pq3s-r511
title: Tagged images with LEGO bricks - Technic Pins

description: The set contains images of LEGO bricks (from Technic Pins category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/4wsx-rc41
title: Tagged images with LEGO bricks - Plates Angled

description: The set contains images of LEGO bricks (from Plates Angled category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/ah8d-pr68
title: Tagged images with LEGO bricks - Technic Panels

description: The set contains images of LEGO bricks (from Technic Panels category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/hqdv-3094
title: Tagged images with LEGO bricks - Tiles Round and Curved

description: The set contains images of LEGO bricks (from Tiles Round and Curved category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/4sna-xe46
title: Video of LEGO bricks on conveyor belt - narrow special plates

description: 







The set contains videos of LEGO bricks (narrow special plates) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final conveyor belt.
 
The videos were recorded using Huawei p20 Pro camera (1920x1080 resolution, H.264 high profile codec, 15 frames per second) located 14.5 cm over the belt. The bricks have random colors. The videos were placed in a seperate file for different pin type.
 
Sample images are presented below.
DOI: 10.34808/jdhr-jk67
title: Tagged images with LEGO bricks - Plates

description: The set contains images of LEGO bricks (from Plates category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/mt1k-5m66
title: Tagged images with LEGO bricks - Bricks Round and Cones

description: The set contains images of LEGO bricks (from Bricks Round and Cones category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/86xs-pr26
title: Tagged images with LEGO bricks - Tiles

description: The set contains images of LEGO bricks (from Tiles category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/9knk-3973
title: Tagged images with LEGO bricks moving on the conveyor belt

description: The data set conatins tagged images conatining LEGO bricks used for traning LEGO bricks detecting network. The dataset contains frames taken from video recordings of lego bricks moving on a conveyor belt. The images conatin from 0 to 7 bricks. In total there are 5459 tagged lego bricks in 4340 images and 3390 images without any bricks in them. The images are in FullHD resolution (1920x1080) and were taken from videos recorded with a Huawei p20 Pro camera (1920x1080 resolution, H.264 high profile codec, 15 frames per second).
The immages were tagged with coordinates of LEGO bricks bounding boxes. The label are stored in text files named as the image. The label were generated using labeImg software (https://github.com/tzutalin/labelImg) and are stored in YOLO format. The classes names are stored in classes.txt file inside the dataset. The content of the classes.txt file is as follows:
BricksNarrowBricksSpecialBricksTechnicWheelsAndOtherTechnicPinsTechnicAxlesAccessriesGearsFlagsSignsBricksWideAnimalsWeaponsHelmetshatshairLegsMicrofiguresPlantsHeadsserptineTorsoHeadsGunsArmouredshieldsbrickswithstudesplateswithstudes
The images below shows sample screenshots from the labelImg application:
DOI: 10.34808/q6pz-3080
title: Tagged images with LEGO bricks - Plants and Animals

description: The set contains images of LEGO bricks (from Plants and Animals category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.15468/dl.fwenn5
title: Occurrence Download

description: A dataset containing 13750 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hypoedaleus guttatus (Vieillot, 1816))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 13750 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0294140-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gttcj3
title: Occurrence Download

description: A dataset containing 182 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Betula tianschanica Rupr."
 ]
}

 The dataset includes 182 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289982-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/6bxc-cz59
title: Tagged images with LEGO bricks - Hinges Arms and Turntables

description: The set contains images of LEGO bricks (from Hinges Arms and Turntables category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.34808/fjkg-p357
title: Tagged images with LEGO bricks - Bricks Sloped

description: The set contains images of LEGO bricks (from Bricks Sloped category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.
The images were extracted from photos taken using Huawei p20 Pro camera (2160x3840 resolution, JPEG file format). The bricks were illuminated using two top-down facing 1600lm, 4000K LED lamps. The shutter speed and ISO were set to 1/100 and 50 respectively (to match the lamps frequency). Each file is limited to a bounding box as detected using LegoSorter app (https://github.com/legosorter). The bounding boxes were created using YOLO trained neural network designated to detect (but not differentiate) LEGO bricks.
The bricks have random colors. The photos are organized using official LEGO part numbers, photos of each brick located in a folder named after the part number. 
Sample images are presented below.
DOI: 10.15468/dl.8g4tus
title: Occurrence Download

description: A dataset containing 79 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is November",
 "TaxonKey is Lophophorus sclateri Jerdon, 1870"
 ]
}

 The dataset includes 79 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046781-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ckjamk
title: Occurrence Download

description: A dataset containing 909 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lathyrus hierosolymitanus Boiss."
 ]
}

 The dataset includes 909 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004518-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ukaakq
title: Occurrence Download

description: A dataset containing 4616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Psilopogon rafflesii (R.Lesson, 1839))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4616 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0294147-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wu9p3v
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nepeta bombaiensis Dalzell"
 ]
}

 The dataset includes 16 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046784-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsegz7
title: Occurrence Download

description: A dataset containing 176 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megachasmidae"
 ]
}

 The dataset includes 176 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289998-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cfkd7w
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nepeta bracteata Benth."
 ]
}

 The dataset includes 65 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046791-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z8m9w4
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Clytoctantes atrogularis S.Lanyon, Stotz & Willard, 1991)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 59 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0294141-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.