Image Capture Best Practices

LandingLens is built on a data-centric approach. This means that having a dataset of high-quality images is more important than finetuning model parameters. This also means that it’s better to have fewer high-quality images than many poor-quality ones. 

A dataset is the foundation of a model in LandingLens. Therefore, you’re more likely to build a high-perforing model if you start with a dataset of high-quality images.

Choosing the right hardware—cameras, lenses, and lighting—is one component to creating high-quality images. Thinking about the dataset as a whole in the context of your use case and goals is another component. 

To learn how to build a high-quality dataset, check out the best practices in the following articles:

• Cameras
• Lenses (Optics)
• Lighting
• Curate High Quality Datasets

What Cameras, Lenses, and Lighting Should I Use?

Implementing a camera, lens, and lighting setup is important to ensure that all images yield consistent and accurate results. There is generally no one-size-fits-all solution, and different use cases require application-specific imaging geometries consisting of a camera, lens, and lighting.

Check out the rest of the article for more details, but to ensure that you get the right camera, lens, and lighting system for your specific use case, we recommend working with one of our LandingLens Certified Partners. Their area of expertise is developing these types of solutions, and they can offer their real-world experience to help you implement the hardware that's right for you. 

All partners have gone through our rigorous vetting program and are industry-trusted experts. To learn more about our partners, go here.

How Having the Hardware Sets You Up for Success

The guiding principle in developing your camera, lens, and lighting system is that it should lead to reliable and repeatable results. Good data in leads to good data out.

The goal when selecting imaging hardware is to create visible contrast between the object and the background with a defined geometry. This is achieved by:

• Defining a camera's field of view (area of inspection),
• Identifying the working distance from the front of the lens to the object, and 
• Selecting an appropriate lighting technique that creates contrast.