OpenCV 中的 FAST 算法在哪里？答案

【问题标题】：Where is the FAST algorithm in OpenCV?OpenCV 中的 FAST 算法在哪里？
【发布时间】：2016-09-09 10:03:21
【问题描述】：

我无法在 Python OpenCV 模块中找到 FAST 角点检测器，我试过这个this，就像link中描述的那样。我的 OpenCV 版本是 3.1.0。

我知道 SIFT 和 SURF 等特征描述算法已转移到 cv2.xfeatures2d，但 FAST 算法不在此处。

【问题讨论】：

【解决方案1】：

我认为 opencv-3.1.0 文档中的示例代码没有更新。提供的代码将不起作用。

试试这个：

    # Ref: https://github.com/jagracar/OpenCV-python-tests/blob/master/OpenCV-tutorials/featureDetection/fast.py
import numpy as np
import cv2
from matplotlib import pyplot as plt

img = cv2.imread('simple.jpg',0)

# Initiate FAST object with default values
fast = cv2.FastFeatureDetector_create(threshold=25)

# find and draw the keypoints
kp = fast.detect(img,None)
img2 = cv2.drawKeypoints(img, kp, None,color=(255,0,0))

print("Threshold: ", fast.getThreshold())
print("nonmaxSuppression: ", fast.getNonmaxSuppression())
print("neighborhood: ", fast.getType())
print("Total Keypoints with nonmaxSuppression: ", len(kp))

cv2.imwrite('fast_true.png',img2)

# Disable nonmaxSuppression
fast.setNonmaxSuppression(0)
kp = fast.detect(img,None)

print "Total Keypoints without nonmaxSuppression: ", len(kp)

img3 = cv2.drawKeypoints(img, kp, None, color=(255,0,0))

cv2.imwrite('fast_false.png',img3)

【讨论】：

【解决方案2】：

根据opencv-3.1.0 documentation你可以这样在python中运行FAST：

import numpy as np
import cv2
from matplotlib import pyplot as plt

img = cv2.imread('simple.jpg',0)

# Initiate FAST object with default values
fast = cv2.FastFeatureDetector_create()

# find and draw the keypoints
kp = fast.detect(img,None)
img2 = cv2.drawKeypoints(img, kp, color=(255,0,0))

# Print all default params
print "Threshold: ", fast.getInt('threshold')
print "nonmaxSuppression: ", fast.getBool('nonmaxSuppression')
print "neighborhood: ", fast.getInt('type')
print "Total Keypoints with nonmaxSuppression: ", len(kp)

cv2.imwrite('fast_true.png',img2)

# Disable nonmaxSuppression
fast.setBool('nonmaxSuppression',0)
kp = fast.detect(img,None)

print "Total Keypoints without nonmaxSuppression: ", len(kp)

img3 = cv2.drawKeypoints(img, kp, color=(255,0,0))

cv2.imwrite('fast_false.png',img3)

【讨论】：

这段代码对我不起作用，但是 Yahya 的解决方案对我有用。

【解决方案3】：

此代码作为官方文档代码仅与特定版本的opencv兼容，之后不再更新

from __future__ import print_function
import cv2

img = cv2.imread('simple.jpg',0)
img = cv2.imread(f,0)

# Initiate FAST object with default values
fast = cv2.FastFeatureDetector_create(threshold=25)

# find and draw the keypoints
kp = fast.detect(img,None)
img2 = cv2.drawKeypoints(img, kp, None,color=(255,0,0))

print("Threshold: ", fast.getThreshold())
print("nonmaxSuppression: ", fast.getNonmaxSuppression())
print("neighborhood: ", fast.getType())
print("Total Keypoints with nonmaxSuppression: ", len(kp))

img2_vis = cv2.resize(img2, (1600, 1000))
cv2.imshow('fast_true',img2_vis),cv2.waitKey()

# Disable nonmaxSuppression
fast.setNonmaxSuppression(0)
kp = fast.detect(img,None)

print("Total Keypoints without nonmaxSuppression: ", len(kp))

img3 = cv2.drawKeypoints(img, kp, None, color=(255,0,0))

img3_vis = cv2.resize(img3, (1600, 1000))
cv2.imshow('fast_false',img3_vis),cv2.waitKey()

【讨论】：