NEW Evaluation Dataset for Advance Perception Training & Validation

NEW Evaluation Dataset

The right synthetic data can make all the difference in advance perception training and testing!
By using a unique proprietary unbiased render engine, at ANYVERSE we generate data that matches your sensors and thus meets the exact specs of your perception model

Try this Evaluation Dataset and get in touch for a custom one according to your needs.

ASHS Dataset

The ANYVERSE Suburban Highway Scenes (ASHS) is a synthetic dataset composed of nearly 5K HD images to be used for research purposes only.  It provides metadata including pixel-accurate, instance-specific, 2D bounding-box and depth annotations for a set of objects in the context of ADAS, autonomous driving and UAV.  The images are generated using unique suburban and highway scenes with randomly-placed objects of interest (pedestrians and vehicles) for greater variability in your machine learning. 

ASHS Dataset

The ANYVERSE Suburban Highway Scenes (ASHS) is a synthetic dataset composed of nearly 5K HD images to be used for research purposes only. 
The dataset provides pixel-accurate, instance-specific, 2D bounding-box and depth annotations for a set of objects in the context of autonomous driving.
The images are generated using unique suburban and highway scenes with randomly-placed objects of interest (pedestrians and vehicles) for greater variability. 

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Sample Images

Color

SAMPLE IMAGE - color.31 copia

Instance

SAMPLE IMAGE - instance.31 copia

Depth

SAMPLE IMAGE - depth.31 copia

Semantic

SAMPLE IMAGE - label.31 copia

Request our evaluation dataset for non-comercial use to see how ANYVERSE fits in your pipeline!

Request Evaluation Dataset 

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Let's talk synthetic data!

Design your dataset

Let us take you through the steps required for a customizable ANYVERSE dataset. 
We will provide you with some samples afterwards or will get in touch to understand better your data needs.

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Application
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Scenario
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Sensors
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Camera Lens
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Resolution
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Data Output
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About you

Let’s start with the practical use of your dataset!

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Where does the action take place? Pick a scenario!

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Would you like to add camera(s) and/or LiDAR to your ego vehicle?

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Do you require a specific camera lens ?

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What resolution does your model require?

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Finally, tick all the additional metadata channels you’d like to have!

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