opencv find_shape_model

The `find_shape_model` function in OpenCV is used for finding a shape model from a set of training images. It is part of the Shape Matching module in OpenCV, which provides tools for matching shapes based on their contour and other features.

The `find_shape_model` function takes as input a set of training images, which are typically binary images with the object of interest represented as a white shape on a black background. The function then computes a shape model based on the contours of the objects in the training images.

The shape model can be used for shape matching, which involves finding the best match between a given image and the shape model. This can be useful for object recognition and tracking.

To use the `find_shape_model` function, you first need to create a ShapeContextDistanceExtractor object, which defines the distance metric used for shape matching. You then call the `find_shape_model` function, passing in the training images and the ShapeContextDistanceExtractor object.

Here's an example of how to use the `find_shape_model` function:

import cv2

# Load training images
img1 = cv2.imread("train1.png", cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread("train2.png", cv2.IMREAD_GRAYSCALE)
img3 = cv2.imread("train3.png", cv2.IMREAD_GRAYSCALE)

# Create ShapeContextDistanceExtractor object
sc_extractor = cv2.createShapeContextDistanceExtractor()

# Find shape model from training images
shape_model = cv2.findShapeModel([img1, img2, img3], sc_extractor)

In this example, we load three training images and create a ShapeContextDistanceExtractor object. We then call the `findShapeModel` function, passing in the three training images and the ShapeContextDistanceExtractor object. The function returns a shape model, which can be used for shape matching.