python harris角点检测源代码

import c<a href="https://www.knrjk.com/tag/1479" target="_blank">v</a>2 as cv
import matplotlib.pyplot as plt
import numpy as np
# 1读取图像，并转换成灰度图像
img = cv.imread('./image/chess.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 2角点检测
# 2.1输入图像必须是float32
gray = np.float32(gray)
# 2.2最后一个参数在0.04到0.05之间
dst = cv.cornerHarris(gray, 2, 3, 0.04)
# 3设置阈值，将角点绘制出来，阈值根据图像进行选择
img[dst > 0.001 * dst.max(0)] = [0, 0, 255]
# 4图像显示
plt.rc("font", family='Microsoft YaHei')
plt.figure(figsize=(10, 8), dpi=100)
plt.imshow(img[:, :, ::-1]), plt.title('Harris角点检测')
plt.xticks([]), plt.yticks([])
plt.show()
import c<a href="https://www.knrjk.com/tag/1479" target="_blank">v</a>2 as cv
import matplotlib.pyplot as plt
import numpy as np

# 1读取图像，并转换成灰度图像
img = cv.imread('./image/chess.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 2角点检测
# 2.1输入图像必须是float32
gray = np.float32(gray)
# 2.2最后一个参数在0.04到0.05之间
dst = cv.cornerHarris(gray, 2, 3, 0.04)
# 3设置阈值，将角点绘制出来，阈值根据图像进行选择
img[dst > 0.001 * dst.max(0)] = [0, 0, 255]
# 4图像显示
plt.rc("font", family='Microsoft YaHei')
plt.figure(figsize=(10, 8), dpi=100)
plt.imshow(img[:, :, ::-1]), plt.title('Harris角点检测')
plt.xticks([]), plt.yticks([])
plt.show()
import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np

# 1读取图像，并转换成灰度图像
img = cv.imread('./image/chess.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# 2角点检测
# 2.1输入图像必须是float32
gray = np.float32(gray)
# 2.2最后一个参数在0.04到0.05之间
dst = cv.cornerHarris(gray, 2, 3, 0.04)
# 3设置阈值，将角点绘制出来，阈值根据图像进行选择
img[dst > 0.001 * dst.max(0)] = [0, 0, 255]
# 4图像显示
plt.rc("font", family='Microsoft YaHei')
plt.figure(figsize=(10, 8), dpi=100)
plt.imshow(img[:, :, ::-1]), plt.title('Harris角点检测')
plt.xticks([]), plt.yticks([])
plt.show()