Image Pre-Processing

To get optimal predictions from computer vision models, it’s important that the object or region of interest is clearly visible in your images. In some cases, pre-processing your images before uploading them to LandingLens can help models detect key features more effectively.

Below are some common pre-processing techniques to consider. These tips won’t apply to every use case, but they can make a meaningful difference in how well the model detects objects of interest in your images.

Be sure to apply any pre-processing steps consistently across your entire dataset—including both your training images and the ones you use for inference.

Resize Images

LandingLens automatically resizes images during training based on the project type (for Fast Training) or based on your settings (for Custom Training). This helps standardize inputs and speeds up training. For detailed information, go to Images Are Resized During Model Training.

If the object of interest is small or the image has a noisy background, the automatic resize might shrink the object too much, which can make it harder for the model to "see" what it should learn. In this situation, consider resizing and/or cropping images before uploading them to LandingLens to make objects of interest more prominent.

Crop Images

If your images include a lot of background, and the object of interest is consistently in the same location, consider cropping the images to bring more focus to that object.

Cropping reduces background noise and can help the model better understand what it should be learning.

Convert to a Different Color Space

Sometimes, changing the color space—like converting from RGB to HSV—can make your object of interest stand out more. Experimenting with color space can highlight features that might otherwise get lost.

Normalization

If your dataset includes images taken under very different lighting conditions, normalization can help. This process adjusts the brightness levels across images so that they are more consistent.

Adjust Contrast

If the object of interest blends into the background, increase the contrast to separate it visually. This makes it easier for the model to detect edges and boundaries.

Apply Filters

Use filters to enhance regions of interest in the image. For example:

• High-pass filters can enhance edges and fine details—useful when the object is defined by its outline.
• Low-pass filters can smooth out noise and highlight broader shapes—helpful in cluttered scenes.