Photo Editing Software

Annotation for Skylum, AI-Powered Photo Editing

Name: Data Annotation Service
Brand: Label Your Data
Rating: 4.9 (36 reviews)

Location:

Ukraine

Services:

Data Collection Data Annotation

Overview

Skylum needed labeled photo data to train multiple face and body detection models for its AI editing software. Label Your Data handled both sourcing and annotation in parallel:

6000 images collected

22 categories

3 annotators

Client

Photo-editing software company using AI to enhance portraits and facial features automatically across multiple editing tools.

Challenges

In-house team couldn’t scale data tasks across model projects; public datasets lacked edge cases like scars, moles, and freckles.

Solutions

Collected 6 000 images and labeled 70 000 detailed face and body parts using CVAT and client tools, with dedicated QA and pilot review.

Results

10 AI models launched on time; fast feedback loops and flexible task scope kept data flowing across ongoing development cycles.

Client

Skylum is a photo-editing software company. Its tools use AI to enhance portraits, skin, and facial features automatically without manual masking.

Edit photos effortlessly with AI-powered software

Challenges

Skylum’s in-house team couldn’t keep up with data demands across multiple model pipelines.

Public datasets lacked edge cases (e.g. scars, moles, freckles)

Internal teams couldn’t scale data collection or labeling

Needed ongoing support across sub-projects and shifting deadlines

Solution

The Label Your Data team ran the entire pipeline, from sourcing to annotation, inside CVAT and the client’s custom platform.

Collected ~6 000 face/body photos from online sources

Labeled 70 000 detailed features: lips, eyes, blemishes, and more

Split workflows for sourcing vs. annotation to keep pace

Delivered structured outputs in client’s required format

Example of labeled photo used for facial and body feature annotation in data labeling project

Training

The project began with a pilot batch
and example references from Skylum.

Label Your Data built edge-case guidelines, held live Q&A sessions, and added a QA lead.

A team of 7 annotators scaled up with
minimal revision cycles.

Results

10 new AI editing models launched on time

Feedback loop helped maintain speed and quality

Rolling data batches supported evolving model needs

Flexible scope allowed Skylum to ramp work up or down as needed

Annotated image of a man with skin markings used for AI training

Annotated image of a woman with body feature labels for computer vision

Annotated image highlighting facial features for AI model training

Man with labeled skin features for dataset creation

Annotated photo showing body segmentation and labeled areas

Woman sitting with annotated skin areas for data labeling project

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What stands out is their ability to scale any data collection and annotation process, no matter the size or scope. The fast responses and iterative workflow mean we always get quality data right when we need it.

Oleksii Tretiak

Head of R&D

Trusted by ML Professionals

Why Projects Choose Label Your Data

No Forced Commitment

Check our performance based on a free trial

Flexible Pricing

Pay per labeled object or per annotation hour

Tool-Agnostic

Working with every labeling tool, even your custom tools

Quality Backed by SLAs

We commit to accuracy and deadlines – or you don’t pay