Mastering Computer Vision with TensorFlow 2.x

The HOG detector

The Histogram of Oriented Gradients (HOG) is a useful feature that can be used to determine the localized image intensity of an image. This technique can be used to find objects within an image. The localized image gradient information can be used to find similar images. In this example, we will use scikit-image to import the HOG and use it to plot the HOG of our image. You may have to install scikit-image, if it's not already installed, using pip install scikit-image:

from skimage.feature import hogfrom skimage import data, exposurefruit, hog_image = hog(img, orientations=8, pixels_per_cell=(16, 16),cells_per_block=(1, 1), visualize=True, multichannel=True)hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, ...