inpaint

Computational photographyfunctionOpenCV 5.0.0

import { inpaint } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Explore visually: Image inpainting →

Fill a masked region by propagating nearby image structure and colour into it.

VISUAL WALKTHROUGHPhotography

REFERENCE INPUTA masked strip in the image

The highlighted region is the part to reconstruct.

→

RESULTFill the missing strip

The smooth field illustrates continuation into a hole. Texture and larger missing structures are not recovered simply by extending a gradient.

Illustrative example. The stages explain the method; they are not a live OpenCV execution.

Restores the selected region in an image using the region neighborhood.

Note: - An example using the inpainting technique can be found at opencv_source_code/samples/cpp/inpaint.cpp

• (Python) An example using the inpainting technique can be found at opencv_source_code/samples/python/inpaint.py

inpaint(src: Mat, inpaintMask: Mat, dst: Mat, inpaintRadius: number, flags: number): void;

src

Input 8-bit, 16-bit unsigned or 32-bit float 1-channel or 8-bit 3-channel image.

inpaintMask

Inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted.

dst

Output destination, filled by the native operation. Output image with the same size and type as src .

inpaintRadius

Radius of a circular neighborhood of each point inpainted that is considered by the algorithm.

flags

Inpainting method that could be cv::INPAINT_NS or cv::INPAINT_TELEA

The function reconstructs the selected image area from the pixel near the area boundary. The function may be used to remove dust and scratches from a scanned photo, or to remove undesirable objects from still images or video. See http://en.wikipedia.org/wiki/Inpainting for more details.

Upstream declaration ↗

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.