def extract_line_position(image): # 提取坐标,存在bug,会重复提取x的值
list_y = []
list_x = [] # 存储值为0的行号和列号
for i in range(len(image)):
for j in range(len(image[i])):
if image[i][j] == 0:
list_x.append(j)
list_y.append(len(image) - i)
return list_x, list_y
def get_line_position(image):
list_x = []
list_y = []
# y_len = len(image)
# print(y_len)
for i in range(len(image[0])): # 遍历列数
for j in range(len(image)): # 遍历行数
if image[j][i] == 0:
list_x.append(i)
list_y.append(len(image)-j)
break
return list_x,list_y
def get_lineMedium_position(image):
image = np.delete(image, 0, axis=0) # 删除第一行
image = np.delete(image, 0, axis=1) # 删除第一列
list_x = []
list_y = []
start_index = 0
end_index = 0
for i in range(len(image[0])): # 遍历列数
for j in range(len(image)-1): # 遍历行数
if image[j][i] == 255 and image[j+1][i] == 0:
start_index = j
continue
if image[j][i] == 0 and image[j+1][i] == 255:
end_index = j
y_position = (start_index + end_index)/2
list_x.append(i)
list_y.append(len(image) - y_position)
start_index = 0
end_index = 0
break
return list_x, list_y
这里就不上图了,效果挺不错的,不用对曲线进行细化,节省时间,但是要根据实际情况使用。
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei'] # 显示中文
plt.rcParams['axes.unicode_minus'] = False # 正常显示负号
"""
December 16, 2022,LuoNicus
获取曲线分割后的图像点坐标类
用不同的方法获取坐标
只可提取像素 0 or 255,提取其它自行修改
正常提取,上边缘提取,中值提取,各有优缺,根据实际情况使用
"""
""" 图像像素示意
[[255,255, 255, 0, 0]
[0, 0, 255, 0, 0]
[0, 0, 255, 0, 0]
[0, 0, 255, 255,255]]
"""
class Get_Line_Positon:
def __init__(self, image):
self.image = image
self.list_x = []
self.list_y = []
print("已获取图像信息,准备提取二值图像位置坐标")
def by_allline_point(self): # 提取坐标,存在bug,会重复提取x的值
# 细化算法存在bug,第一行和第一列为0黑色,不合理,因此首先去掉
print("warn:常规算法提取,容易出现多个x为相同值")
self.image = np.delete(self.image, 0, axis=0) # 删除第一行
self.image = np.delete(self.image, 0, axis=1) # 删除第一列
for i in range(len(self.image)):
for j in range(len(self.image[i])):
if self.image[i][j] == 0:
# print(mask[i][j],j,i)
self.list_x.append(j)
self.list_y.append(len(self.image) - i)
return self.list_x, self.list_y
def by_upline_point(self): # 提取直线坐标,提取曲线的边缘坐标,避免出现x的重复值
print("提取曲线上边缘的值")
self.image = np.delete(self.image, 0, axis=0) # 删除第一行
self.image = np.delete(self.image, 0, axis=1) # 删除第一列
# y_len = len(self.image)
# print(y_len)
for i in range(len(self.image[0])): # 遍历列数
for j in range(len(self.image)): # 遍历行数
if self.image[j][i] == 0:
self.list_x.append(i)
self.list_y.append(len(self.image) - j)
break
return self.list_x, self.list_y
def by_lineMedium_point(self): # 提取像素上下值的中位数坐标,该方法不用对函数进行细化
print("提取曲线的中值")
self.image = np.delete(self.image, 0, axis=0) # 删除第一行
self.image = np.delete(self.image, 0, axis=1) # 删除第一列
start_index = 0
end_index = 0
for i in range(len(self.image[0])): # 遍历列数
for j in range(len(self.image) - 1): # 遍历行数
if self.image[j][i] == 255 and self.image[j + 1][i] == 0:
start_index = j
continue
if self.image[j][i] == 0 and self.image[j + 1][i] == 255:
end_index = j
y_position = (start_index + end_index) / 2
self.list_x.append(i)
self.list_y.append(len(self.image) - y_position)
start_index = 0
end_index = 0
break
return self.list_x, self.list_y