The function implements different single-image inpainting algorithms

dst = cv.inpaint2(src, mask)
dst = cv.inpaint2(src, mask, 'OptionName', optionValue, ...)

Input

• src source image, it could be of any type (8/16/32-bit integers or 32/64-bit floating points) and any number of channels from 1 to 4. In case of 3- and 4-channels images the function expect them in CIELab colorspace or similar one, where first color component shows intensity, while second and third shows colors. Nonetheless you can try any colorspaces.
• mask mask (8-bit 1-channel of same size as src), where non-zero pixels indicate valid image area, while zero pixels indicate area to be inpainted.

Output

• dst Output image with the same size and type as src.

Options

• Method Inpainting algorithms, one of:
  • ShiftMap (default) This algorithm searches for dominant correspondences (transformations) of image patches and tries to seamlessly fill-in the area to be inpainted using this transformations.

The function reconstructs the selected image area from known area. See the original paper [He2012] for details.

References

[He2012]:

Kaiming He, Jian Sun. "Statistics of patch offsets for image completion". In Computer Vision-ECCV 2012, pages 16-29. Springer, 2012.