Two new gifts with purchase have been revealed at LEGO.com. 40601 Majisto's Magical Workshop, a re-imagining of the set with the same name 6048 which was released in 1993, and 40602 Winter Market Stall, which is probably the first of several seasonal GWPs.

We don't have concrete information on availability or spend thresholds yet, although they are most likely going to be available during the Insiders weekend, 18-19th, and again during the Black Friday / Cyber Monday event the following weekend.

There are 20,268 items in the Brickset database Brickset members have written 39,160 set reviews 10,115 members have logged in in the last 24 hours, 23,431 in the last 7 days, 38,166 in the last month 500 people have joined this week. There are now 311,998 members Between us we own 40,037,605 sets worth at least US$1,377,743,192 and containing 13,917,936,518 pieces

People(lego) And Car

## Overview

People(lego) And Car is a dataset for object detection tasks - it contains Lego annotations for 670 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Context

Derived from the LEGO Database https://www.kaggle.com/rtatman/lego-database , flattened into a single CSV file for use in a Kernel I plan to build with the Pandas Python library.

Content

The original data files were imported into MS SQL Server, and then exported after performing a huge join across all of the tables. A bunch of data was excluded form my export query to simplify the data set for my research goals. Certain part categories such as minifigs as well as some themes like Duplo have been excluded.

Acknowledgements

This is derived from the LEGO database https://www.kaggle.com/rtatman/lego-database which is courtesy of https://www.kaggle.com/rtatman and in turn originated from Rebrickable.

Inspiration

This is a fun data set to play with for learning data wrangling. I personally identify with it as a LEGO fan!

Context

LEGO is the largest toy manufacturer on the planet, and there is a growing market for LEGO set investments. Some studies have even shown that you can beat the S&P 500. For example, a single Boba Fett minifigure is now valued at over $3,000. With the goal of looking at this trend, this data has the most up to date list of sets and features along with list and resale prices.

Content

This dataset uses a combination of data from two API's from Brickset.com and Bricklink.com. The features include name, year, theme, theme group, subtheme, category, packaging type, number of instructions, retail availability, number of pieces, number of minifigures, user reviews (out of 5 stars), list price in USD, and latest resale price in USD.

List prices and features - Brickset API as of 05/10/2023

Resale Price - Bricklink API as of 05/10/2023

In 2024, the Lego Group had net sales amounting to approximately 35.4 billion Danish kroner in the Americas region. The toy manufacturer had net sales of over 74 billion Danish kroner that year.

Color classification is interesting because it is a real world problem, and it is difficult. Color classification is a subtask in computer vision and robotics: recognising an object by its color is often used in robot navigation. There are robot football leagues where the two goals and the ball have different colors and the robots must recognize goals, the ball and other robots based on color. Humans are generally good at sorting lego by color, son one would expect that color classification is an easy task. Unfortunately, it is surprisingly difficult. The same object will appear to have different colors depending on the lighting conditions. The human eye and brain are good compensate for the lighting conditions automatically, so most people are quite good at this task. Electronic cameras are not so good at this, and computers and robots thus often make mistakes. The example shown below shows that the same lego object can register as light grey or dark grey depending on the circumstance. It will be hard to classify these two colors correctly in all photos.

The Legocolor dataset was created by taking multiple pictures of the same lego setup. Lego was chosen so that other researchers can recreate the results and extend the dataset if needed. Anyone can order the required lego sets, build the same setup and make additional photos. The Lego setup was photographed in different locations, with different cameras and different lighting conditions. Given the color values from an image, you determine the color of a lego block.

The Legocolor dataset was created by Rosalie Fischer for her Bachelor thesis at the Vrije Universiteit. The dataset was designed with the following requirements:

• The dataset must be linked to a classification problem.
• Unlike existing datasets, the problem should have only a few inputs with identical impact on the final result.
• The problem should not be a yes/no classification, but a problem with multiple labels.
• The dataset must be based on a real world problem and use real data.
• The dataset should not contain personal data, so that it can be used without privacy risks or ethical risks.