Tagged images with LEGO bricks - Panels - Open Research Data - Bridge of Knowledge

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Tagged images with LEGO bricks - Panels

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Description

The set contains images of LEGO bricks (from 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.

 

Illustration of the publication
Illustration of the publication

Dataset file

Panels.zip
23.3 MB, S3 ETag 09e7ad9e0268d1a47f48c8d4445f5154-1, downloads: 57
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5
download file Panels.zip

File details

License:
Creative Commons: by-nc 4.0 open in new tab
CC BY-NC
Non-commercial

Details

Year of publication:
2021
Verification date:
2021-06-21
Dataset language:
English
Fields of science:
  • information and communication technology (Engineering and Technology)
  • computer and information sciences (Natural sciences)
DOI:
DOI ID 10.34808/74bx-7w58 open in new tab
Series:
Verified by:
Gdańsk University of Technology

Keywords

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Version this document has several versions

DOI 10.34808/az7b-mz63 represents the latest version of the data.

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