hollis_f wrote in post #15649234
FoCal will always give a more accurate result, because it uses all of the different MFA values it records to decide of the optimum. DotTune, OTOH, uses just two data points - the lowest MFA value where the confirmation light comes on and the highest value before it goes off.
However, the difference is, in most cases, going to be minimal. And the sheer ease of use of DotTune when implemented by ML means I've got to try it out.
Agree. The DotTune method looks like the best free approach available, but you sure need to nail the focus in live view to start the process off.
FoCal is a great product but it fails when there isn't enough light of if the light changes a bit (clouds partially obscurring the sun). If you don't have a studio or some other source of nice bright, consistent lighting then DotTune is probably a better approach.