opencv 进行任意形状目标识别，供大家参考，具体内容如下
工作中有一次需要在简单的图上进行目标识别，目标的形状不固定，并且存在一定程度上的噪声影响，但是噪声影响不确定。这是一个简单的事情，因为图像并不复杂，现在将代码公布如下：
import cv2
def otsu_seg(img):
ret_th, bin_img = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
return ret_th, bin_img
def find_pole(bin_img):
img, contours, hierarchy = cv2.findContours(bin_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
area = 0
for i in range(len(contours)):
area += cv2.contourArea(contours[i])
area_mean = area / len(contours)
mark = []
for i in range(len(contours)):
if cv2.contourArea(contours[i]) < area_mean:
mark.append(i)
return img, contours, hierarchy, mark
def draw_box(img,contours):
img = cv2.rectangle(img,
(contours[0][0], contours[0][1]),
(contours[1][0], contours[1][1]),
(255,255,255),
3)
return img
def main(img):
ret, th = otsu_seg(img)
img_new, contours, hierarchy, mark = find_pole(th)
for i in range(len(contours)):
if i not in mark:
left_point = contours[i].min(axis=1).min(axis=0)
right_point = contours[i].max(axis=1).max(axis=0)
img = draw_box(img, (left_point, right_point))
return img
if __name__ =="__main__":
img = cv2.imread('G:/test.png')
img = main(img)
cv2.imwrite('G:/test_d.png', img)
结果图如下：
