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How Synthetic Computer Vision is Changing the Game

The Future of Retail Shelf Auditing:

Synthetic Computer Vision Is the Future of Retail Automation

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Get access high-quality training datasets in a just a few hours using the Neurolabs Platform.

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Access to

100k+ SKUs 

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Full control over the data 

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Award-winning RPA Partner

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Expert Support 

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STEP 1
3D Asset Catalogue

Select SKUs of interest

With direct access to 100,000+​ SKUs on demand and 2,000+ of the most popular SKUs out-of-the-box, we have you covered. 


Following best-in-class industry standards, SKUs are organised by category. Search through the catalogue by product name or EAN. 

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If you can't find your SKU in the catalogue, simply upload 6 photos and we'll generate a digital twin of the SKU in less than 48h.

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Finally, we also offer you the option to upload your own 3D assets.

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1

Pick a category

Start by choosing a category of objects. Check our public catalogue and leverage all existing categories.

2

Create your catalogue

Next, define your private catalogue by selecting specific objects from a category. 

3

Import your data

Still missing an SKU? Import 6 photos of the product from varying angles and we'll have digitise it for you. If you have the 3D asset already, you can simply upload it. 

STEP 2
Data Generation

Synthetic 
Dataset

It only takes 3 clicks to generate a highly diverse dataset.

 

Choose from a large variety of pre-built scene configurations that have been industry validated.

 

There are many out-of-the-box configurations available, such as SKU detection for shelves, smart carts or conveyor belts.

 

Easily customise each dataset using no-code mode or use expert mode to control low-level specifics of the scene, such as camera type, camera angle, scene lighting or occlusion rate.

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1

Define SKU catalogue

Start by choosing a category of objects. Check our public catalogue and leverage all existing categories.

2

Select a scene

Whether your use-case is shelf monitoring, smart cart or cashierless checkout, out-of-the-box configurations are waiting for you.

3

Customise the dataset

Have deeper control over the dataset by specifying key variables such as lighting type, camera positioning, occlusion rate, and much more.

 

Finally, choose the type of annotations you'd like for your images.

STEP 3
Data Validation

Validate and export your data

Once the dataset is ready, you will find it under your Datasets collection. ​

 

For your freshly generated dataset, a high-level summary is available.

 

Next, visualise the generated images, with or without annotations and labels. ​

 

Finally, export your dataset locally in the standard COCO format.

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1

Validate the meta-data

Take a high-level peak into your dataset to check that the output meets your expectations.

2

Visualise your data

Visually check samples from the dataset to validate their quality and relevance for your specific use-case.

3

Download the data

Export the data locally. You'll have instant access to the images and the annotations files in the industry-wide COCO standard.

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Get started with Synthetic Computer Vision today!

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