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Training data for Computer Vision

The human solution to your machine learning project

The right annotators for your project

Ingedata’s teams of annotators segment and label all types of images. They are chosen for their skills and trained daily to produce rigorously reliable data for ever more efficient models.

Using raw images, our scalable teams segment and label large training sets requiring a high level of technicality. Ingedata’s ability to set up teams of annotators who are experts in their fields combined with our annotation tools enables us to efficiently handle very specific classes, in all their forms and nuances.
From semantic segmentation to cuboids, Ingedata supports all branches of image recognition technology.

An annotation platform designed for the production of

✓ With the necessary tools: 2D Bounding boxes, 3D Cuboids, Landmark annotations, Polygons, Lines and curves, Semantic segments, …

✓ All the right processes: Performance optimisation, Quality control processes, Real-time activity monitoring, Personalised training and talent management, Direct communication with teams, …

Why Ingedata?…

✓ Dedicated teams : Rely on dedicated teams. They are an extension of your internal resources.

✓ High quality datasets: Get reliable and accurate data guaranteed by our production processes and annotation tools.

✓ Autonomous management: Focus on your technological added value while we manage the coordination of the annotation project.

✓ Proactive regulatory compliance: Annotators all work in production centers that meet or exceed data management standards (DPMR, ISO 27001, etc.).

Using raw images, our scalable teams segment and label large training sets requiring a high level of technicality.

Ingedata’s ability to set up teams of annotators who are experts in their fields combined with our annotation tools allows us to efficiently handle very specific classes, in all their forms and nuances.

From semantic segmentation to cuboids, Ingedata supports all branches of image recognition technology.

They trust us

Some of the most common Computer Vision

Natural Language

Crawling of content

Scraping of articles

Cleaning and tandardization

Contextualized categorization

Images (photos and videos)

Trimming and cleaning

Segmentation

Location

Annotation