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Get the number of calibration object pose parameters in the optimization vector
SYNOPSIS
m = mrcal.cameramodel('xxx.cameramodel')
optimization_inputs = m.optimization_inputs()
b = mrcal.optimizer_callback(**optimization_inputs)[0]
mrcal.unpack_state(b, **optimization_inputs)
i_state0 = mrcal.state_index_frames(0, **optimization_inputs)
Nstates = mrcal.num_states_frames ( **optimization_inputs)
frames_rt_toref_all = b[i_state0:i_state0+Nstates]
The optimization algorithm sees its world described in one, big vector of state.
The optimizer doesn't know or care about the meaning of each element of this
vector, but for later analysis, it is useful to know what's what. The
mrcal.num_states_...() functions report how many variables in the optimization
vector are taken up by each particular kind of measurement.
THIS function reports how many variables are used to represent ALL the frame
poses. Here a "frame" is a pose of the observed calibration object at some
instant in time. The frames are stored contiguously as an "rt transformation": a
3-element rotation represented as a Rodrigues vector followed by a 3-element
translation. These transform points represented in the internal calibration
object coordinate system to the reference coordinate system.
In order to determine the variable mapping, we need quite a bit of context. If
we have the full set of inputs to the optimization function, we can pass in
those (as shown in the example above). Or we can pass the individual arguments
that are needed (see ARGUMENTS section for the full list). If the optimization
inputs and explicitly-given arguments conflict about the size of some array, the
explicit arguments take precedence. If any array size is not specified, it is
assumed to be 0. Thus most arguments are optional.
ARGUMENTS
- **kwargs: if the optimization inputs are available, they can be passed-in as
kwargs. These inputs contain everything this function needs to operate. If we
don't have these, then the rest of the variables will need to be given
- lensmodel: string specifying the lensmodel we're using (this is always
'LENSMODEL_...'). The full list of valid models is returned by
mrcal.supported_lensmodels(). This is required if we're not passing in the
optimization inputs
- do_optimize_intrinsics_core
do_optimize_intrinsics_distortions
do_optimize_extrinsics
do_optimize_calobject_warp
do_optimize_frames
optional booleans; default to True. These specify what we're optimizing. See
the documentation for mrcal.optimize() for details
- Ncameras_intrinsics
Ncameras_extrinsics
Nframes
Npoints
Npoints_fixed
optional integers; default to 0. These specify the sizes of various arrays in
the optimization. See the documentation for mrcal.optimize() for details
RETURNED VALUE
The integer reporting the variable count of frames in the state vector
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