[PYTHON/SKIMAGE] ORB(Oriented FAST and Rotated BRIEF) 분류기 사용하기

■ ORB(Oriented FAST and Rotated BRIEF) 분류기를 사용하는 방법을 보여준다.

▶ 예제 코드 (PY)


import matplotlib
import matplotlib.pyplot as pp
import skimage.color as color
import skimage.data as data
import skimage.feature as feature
import skimage.io as io
import skimage.transform as transform

matplotlib.use("TkAgg")

io.use_plugin("matplotlib")

imageNDArray          = data.astronaut()
grayscaleImageNDArray = color.rgb2gray(imageNDArray)
rotateImageNDArray    = transform.rotate(grayscaleImageNDArray, 180)
affineTransform       = transform.AffineTransform(scale=(1.3, 1.1), rotation = 0.5, translation = (0, -200))
transformImageNDArray = transform.warp(grayscaleImageNDArray, affineTransform)

orb = feature.ORB(n_keypoints = 200)

orb.detect_and_extract(grayscaleImageNDArray)

grayscaleKeypointNDArray   = orb.keypoints
grayscaleDescriptorNDArray = orb.descriptors

orb.detect_and_extract(rotateImageNDArray)

rotateKeypointNDArray   = orb.keypoints
rotateDescriptorNDArray = orb.descriptors

orb.detect_and_extract(transformImageNDArray)

transformKeyPointNDArray   = orb.keypoints
transformDescriptorNDArray = orb.descriptors

grayscaleRotateMatchNDArray    = feature.match_descriptors(grayscaleDescriptorNDArray, rotateDescriptorNDArray   , cross_check = True)
grayscaleTransformMatchNDArray = feature.match_descriptors(grayscaleDescriptorNDArray, transformDescriptorNDArray, cross_check = True)

figure, axesNDArray = pp.subplots(nrows = 2, ncols = 1)

pp.gray()

feature.plot_matches(axesNDArray[0], grayscaleImageNDArray, rotateImageNDArray, grayscaleKeypointNDArray, rotateKeypointNDArray, grayscaleRotateMatchNDArray)

axesNDArray[0].axis("off")
axesNDArray[0].set_title("Original Image vs. Transformed Image")

feature.plot_matches(axesNDArray[1], grayscaleImageNDArray, transformImageNDArray, grayscaleKeypointNDArray, transformKeyPointNDArray, grayscaleTransformMatchNDArray)

axesNDArray[1].axis("off")
axesNDArray[1].set_title("Original Image vs. Transformed Image")

pp.show()

import matplotlib

import matplotlib.pyplot as pp

import skimage.color as color

import skimage.data as data

import skimage.feature as feature

import skimage.io as io

import skimage.transform as transform

matplotlib.use("TkAgg")

io.use_plugin("matplotlib")

imageNDArray = data.astronaut()

grayscaleImageNDArray = color.rgb2gray(imageNDArray)

rotateImageNDArray = transform.rotate(grayscaleImageNDArray, 180)

affineTransform = transform.AffineTransform(scale=(1.3, 1.1), rotation = 0.5, translation = (0, -200))

transformImageNDArray = transform.warp(grayscaleImageNDArray, affineTransform)

orb = feature.ORB(n_keypoints = 200)

orb.detect_and_extract(grayscaleImageNDArray)

grayscaleKeypointNDArray = orb.keypoints

grayscaleDescriptorNDArray = orb.descriptors

orb.detect_and_extract(rotateImageNDArray)

rotateKeypointNDArray = orb.keypoints

rotateDescriptorNDArray = orb.descriptors

orb.detect_and_extract(transformImageNDArray)

transformKeyPointNDArray = orb.keypoints

transformDescriptorNDArray = orb.descriptors

grayscaleRotateMatchNDArray = feature.match_descriptors(grayscaleDescriptorNDArray, rotateDescriptorNDArray , cross_check = True)

grayscaleTransformMatchNDArray = feature.match_descriptors(grayscaleDescriptorNDArray, transformDescriptorNDArray, cross_check = True)

figure, axesNDArray = pp.subplots(nrows = 2, ncols = 1)

pp.gray()

feature.plot_matches(axesNDArray[0], grayscaleImageNDArray, rotateImageNDArray, grayscaleKeypointNDArray, rotateKeypointNDArray, grayscaleRotateMatchNDArray)

axesNDArray[0].axis("off")

axesNDArray[0].set_title("Original Image vs. Transformed Image")

feature.plot_matches(axesNDArray[1], grayscaleImageNDArray, transformImageNDArray, grayscaleKeypointNDArray, transformKeyPointNDArray, grayscaleTransformMatchNDArray)

axesNDArray[1].axis("off")

axesNDArray[1].set_title("Original Image vs. Transformed Image")

pp.show()