PhotonVision’s “Input” tab contains settings that affect the image captured by the currently selected camera. This includes camera exposure and brightness, as well as resolution and orientation.


Resolution changes the resolution of the image captured. While higher resolutions are often more accurate than lower resolutions, they also run at a slower update rate.

When using the reflective/colored shape pipeline, detection should be run as low of a resolution as possible as you are only trying to detect simple contours (essentially colored blobs).

When using the AprilTag pipeline, you should try to use as high of a resolution as you can while still maintaining a reasonable FPS measurement. This is because higher resolution allows you to detect tags with higher accuracy and from larger distances.

Exposure and brightness

Camera exposure and brightness control how bright the captured image will be, although they function differently. Camera exposure changes how long the camera shutter lets in light, which changes the overall brightness of the captured image. This is in contrast to brightness, which is a post-processing effect that boosts the overall brightness of the image at the cost of desaturating colors (making colors look less distinct).


For all pipelines, exposure time should be set as low as possible while still allowing for the target to be reliably tracked. This allows for faster processing as decreasing exposure will increase your camera FPS.

For reflective pipelines, after adjusting exposure and brightness, the target should be lit green (or the color of the vision tracking LEDs used). The more distinct the color of the target, the more likely it will be tracked reliably.


Unlike with retroreflective tape, fiducial tracking is not very dependent on lighting consistency. If you have trouble detecting tags due to low light, you may want to try increasing exposure, but this will likely decrease your achievable framerate.

AprilTags and Motion Blur

For AprilTag pipelines, your goal is to reduce the “motion blur” as much as possible. Motion blur is the visual streaking/smearing on the camera stream as a result of movement of the camera or object of focus. You want to mitigate this as much as possible because your robot is constantly moving and you want to be able to read as many tags as you possibly can. The possible solutions to this include:

  1. Cranking your exposure as low as it goes and increasing your gain/brightness. This will decrease the effects of motion blur and increase FPS.

  2. Using a global shutter (as opposed to rolling shutter) camera. This should eliminate most, if not all motion blur.

  3. Only rely on tags when not moving.



Orientation can be used to rotate the image prior to vision processing. This can be useful for cases where the camera is not oriented parallel to the ground. Do note that this operation can in some cases significantly reduce FPS.

Stream Resolution

This changes the resolution which is used to stream frames from PhotonVision. This does not change the resolution used to perform vision processing. This is useful to reduce bandwidth consumption on the field. In some high-resolution cases, decreasing stream resolution can increase processing FPS.