Preparation of a dataset that includes a large array of standardized homogeneous data. It is crucial to withstand all the conditions of technical assignment since the quality of the final neural network depends on it.

Data collection

Сбор данных для машинного обучения

What goals can you achieve with data collection

We collect lots of homogeneous data for various machine learning tasks. One of the advantages of a dataset assembled for a specific goal is the easiness of its subsequent use.
By ordering data collection in LabelMe, you will simultaneously solve two problems. First, you'll avoid heterogeneity in sizes, formats, and data types. Secondly, you can easily scale quantitative indicators: you need more data — we collect more data.

Our data collection features

Manual collection
It is especially relevant when working with small volumes of specific data. Our trained specialists can extract data from a variety of resources and platforms. This method allows you to take into account the technical requirements even at the collection stage. For example, size, quality, and formats.
Data parsing
Parsing is the process of automatically extracting the necessary data from websites and platforms. It's suitable for collecting a large number of files of the same type. We are developing a list of sites, open-source datasets, databases, tags, and queries. Then we use special software for mass unloading. The work's final stage is an additional verification of all data for compliance with the technical assignment.
Data creation
If there is not enough data in open sources or if the data is specific, we will create it for you on a turnkey basis. For instance, Human Pose Estimation and Human Action Recognition datasets when people need to repeat specific actions. We can attract photographers and cameramen ourselves, look for location and props, and rent additional equipment if necessary. It allows us to perfectly comply with all the technical requirements and get unique materials.

Application examples

The LabelMe team is working on data labeling for a wide variety of businesses:
If you need a detailed analysis of your competitors, we'll provide you with all the necessary data. For example, the appearance of websites, application interfaces, branding, various video materials, or statistical data.
We have successful cases for collecting indicators of utility meters and utility bills for 10 years in different regions. Our specialists will find a way to extract everything you need to solve your problems.
Mobile app development
You may need a large amount of homogeneous data to train neural networks to perform various tasks.
For example, 10 thousand photos of elderly people to create an "aging" filter. Or 20 thousand comments for automated moderation. We can collect any kind of data.
Retail and e-commerce
We collected data for different trading platforms to make their services smarter.
For instance, we collected examples of different clothes by class so that our client could improve recommendation algorithms and the photo search function.
Security systems
For example, we engaged and filmed respondents to collect biometric data. The customer's goal is to create an analog of FaceID: a facial recognition algorithm for unlocking and authorization. We also collected video from surveillance cameras that captured the moment of the theft. Next, it'll be used to improve and automate theft detection.
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Why should you order data labeling from LabelMe

We have an additional validation stage for any annotation task. You won't have to look for mistakes — there won't be any

Annotation verification is already included in the price

They will keep you up to date with the execution of the order and answer all your questions

Personal manager

This way, you can evaluate the quality, and we can make measurements on the complexity, duration, and cost of the order

Free test dataset

We work both with our tools and with partner labeling platforms. We train our specialists before letting them to work

Any annotation tools

We can scale the number of performers so that you get even a large dataset on time

Performance adaptation

LabelMe Services