Configuration Reference

AlignmentConfig Class Reference

Class Signature

@dataclass
class AlignmentConfig:
    method: int = 5
    search_area: int = 0
    subpixel: bool = True
    interpolation: int = cv2.INTER_LINEAR

Fields

method (int): OpenCV template matching method (0–5)
- 0: TM_SQDIFF
- 1: TM_SQDIFF_NORMED
- 2: TM_CCORR
- 3: TM_CCORR_NORMED
- 4: TM_CCOEFF
- 5: TM_CCOEFF_NORMED (default, recommended)
search_area (int): Number of pixels around the ROI to search for matches. 0 means search the entire image (default).
subpixel (bool): Enable sub-pixel registration using Gaussian fitting (default: True).
interpolation (int): OpenCV interpolation method for image warping (default: cv2.INTER_LINEAR).

Methods

`__post_init__()`

Validates configuration parameters after initialization. - Raises: - ValueError: If method is not in 0–5 or search_area is negative.

Example

from templatematchingpy.core.config import AlignmentConfig
config = AlignmentConfig(method=5, search_area=10, subpixel=True)

Constants

`MATCHING_METHODS`

A dictionary mapping method indices to OpenCV constants:

MATCHING_METHODS = {
    0: cv2.TM_SQDIFF,
    1: cv2.TM_SQDIFF_NORMED,
    2: cv2.TM_CCORR,
    3: cv2.TM_CCORR_NORMED,
    4: cv2.TM_CCOEFF,
    5: cv2.TM_CCOEFF_NORMED,
}

Use the method field in AlignmentConfig to select the matching method.

`MIN_VALUE_METHODS`

A set of method indices for which the minimum value in the correlation map indicates the best match (i.e., methods 0 and 1):

MIN_VALUE_METHODS = {0, 1}

For these methods, the best match is found by minimizing the score; for others, by maximizing.

`EPS`

A small constant to avoid division by zero or log of zero in calculations:

EPS = 1e-10

Used in sub-pixel Gaussian fitting and normalization steps.