Remove

image data

barriers

Precisely annotated synthetic image data solves cold start problems, increases existing training data’s efficiency, covers edge cases and reduces development time and cost. You don’t have to be a data rich company to benefit from synthetic data.

Total control over data distribution

Our data generation pipeline is fully customizable and free of bias. You can create any edge case you want, with virtually unlimited variations.

Total control over data distribution

Our data generation pipeline is fully customizable and free of bias. You can create any edge case you want, with virtually unlimited variations.

Precisely annotated data and metadata

Our generated images are automatically annotated, with a pixel level precision. You can train a model right out of generation process without any tedious quality checks. Also we generate a rich metadata that is hard to replicate with human annotation process.

Synthetic data has built-in privacy

Synthetic image data is generated from 3D models in a virtual world. Output images do not contain any personal identifiable information. 

Synthetic data has no privacy issues

Synthetic image data is generated from 3D models in a virtual world. Output images do not contain any personal identifiable information. 

More scalable
than real data

Synthetic data is cheaper and faster to acquire. It scales better with increasing variety than real data. Every scenario conceivable is achievable with synthetic data.

How does it work?

#1

Define the data distribution

Together, we define a set of variations and acceptable limits. If necessary, we develop custom variations.

#2

Create the generation pipeline

We create a procedural world based on agreed variations and generate a sample data.

#3

Fine tune
and reiterate

We optimize parameters until we create a desired sample dataset. Then, we generate your dataset.

Annotation types

Bounding Box

Depth

Segmantation

Keypoint

Use cases

Agriculture

  • Automated Weed Control
  • Harvest Picking
  • Rock Picking
  • Aerial Vision

Manufacturing

  • Defect Detection
  • Safety Monitoring
  • Robotic Automation

Non-Profit

  • Academic Research
  • NGOs
  • Think-tanks

Retail

  • Cashierless Checkout
  • In-store Analytics
  • Inventory Management

Transportation

  • Parking Lot Detection
  • Vehicle Counting
  • Passenger Observation
  • Pedestrian Detection

Other

  • Waste Detection
  • Construction/Mining
  • Site Progress
  • Food Detection
  • Animal Detection
  • Sports Analytics

Use cases

Agriculture

  • Automated Weed Control
  • Harvest Picking
  • Rock Picking
  • Aerial Vision

Manufacturing

  • Defect Detection
  • Safety Monitoring
  • Robotic Automation

Non-Profit

  • Academic Research
  • NGOs
  • Think-tanks

Retail

  • Cashierless Checkout
  • In-store Analytics
  • Inventory Management

Transportation

  • Parking Lot Detection
  • Vehicle Counting
  • Passenger Observation
  • Pedestrian Detection

Other

  • Waste Detection
  • Construction/Mining
  • Site Progress
  • Food Detection
  • Animal Detection
  • Sports Analytics

Contact

How can we help?
Just drop us a line at info@mirage.vision

-If you are curious about synthetic data
-If you want to see how synthetic data fits your use case
-If you want to join us (please include why you are interested and what you can contribute)

Mirage, 2021