Memory

pytme is aware of the memory required for template matching operations. This enables us to map template matching problems to the available hardware and compute a splitting strategy ahead of time.

Memory usage helpers

estimate_ram_usage(shape1, shape2, ...[, ...])

Estimate the RAM usage for a given convolution operation based on input shapes, matching_method, and number of cores.

Abstract Base

MatchingMemoryUsage(fast_shape, ft_shape, ...)

Class specification for estimating the memory requirements of template matching.

Memory usage classes

MatchingMemoryUsage(fast_shape, ft_shape, ...)	Class specification for estimating the memory requirements of template matching.
CCMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for CC scoring.
LCCMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for LCC scoring.
CORRMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for CORR scoring.
CAMMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for CAM scoring.
FLCSphericalMaskMemoryUsage(fast_shape, ...)	Memory usage estimation for FLCMSphericalMask scoring.
FLCMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for FLC scoring.
MCCMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for MCC scoring.
MaxScoreOverRotationsMemoryUsage(fast_shape, ...)	Memory usage estimation MaxScoreOverRotations Analyzer.
PeakCallerMaximumFilterMemoryUsage(...)	Memory usage estimation MaxScoreOverRotations Analyzer.
CupyBackendMemoryUsage(fast_shape, ft_shape, ...)	Memory usage estimation for CupyBackend.