Domain Randomisation to handle real world deployment.
Trusted by industry leaders & innovators.
Why use Repli5?
0 Days
waiting for logging or annotation of training data
10:1
Repli5-to-Real image ratio for comparable model performance
$2,200
estimated savings per 1000 images vs. market rates
FOUNDATIONAL RESEARCH
State of The Art
A curation selection of technical papers that inform and inspire our approach to training data generation.
Pixel-perfect alignment.
Our annotations are not the added to the image. They are the DNA of the scene. Generate bounding boxes or semantic labels natively aligned to the geometry.
WEATHER: Clear
Environment:Town_10
REVEAL_GROUND_TRUTH
REVEAL_WEATHER_VARIATION
Environment:Town_02
Time_of_Day:Evening
Long tail training data
A single semantic frame can spawn infinite visual variations. Instantly toggle between heavy rain, blinding sun or midnight blizzards whilst maintaining consistent labelling.
Generate the impossible to break model biases. Decouple object features from background noise to improve model detection in the field.
Hello / Good morning
Bonjour
OBJECT_INSERTION
Environment:EMPTY
REVEAL_RANDOM_SCENE
