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import cv2 as cv
import os
import numpy as np
# 遍历文件夹函数
def getFileList(dir, Filelist, ext=None):
"""
获取文件夹及其子文件夹中文件列表
输入 dir:文件夹根目录
输入 ext: 扩展名
返回: 文件路径列表
"""
newDir = dir
if os.path.isfile(dir):
if ext is None:
Filelist.append(dir)
else:
if ext in dir[-3:]:
Filelist.append(dir)
elif os.path.isdir(dir):
for s in os.listdir(dir):
newDir = os.path.join(dir, s)
getFileList(newDir, Filelist, ext)
return Filelist
def mid(follow, mask):
crossroads = False
halfWidth = follow.shape[1] // 2
half = halfWidth # 从下往上扫描赛道,最下端取图片中线为分割线
for y in range(follow.shape[0] - 1, -1, -1):
# V2改动:加入分割线左右各半张图片的宽度作为约束,减小邻近赛道的干扰
if (mask[y][max(0, half - halfWidth):half] == np.zeros_like(
mask[y][max(0, half - halfWidth):half])).all(): # 分割线左端无赛道
left = max(0, half - halfWidth) # 取图片左边界
else:
left = np.average(np.where(mask[y][0:half] == 255)) # 计算分割线左端平均位置
if (mask[y][half:min(follow.shape[1], half + halfWidth)] == np.zeros_like(
mask[y][half:min(follow.shape[1], half + halfWidth)])).all(): # 分割线右端无赛道
right = min(follow.shape[1], half + halfWidth) # 取图片右边界
else:
right = np.average(np.where(mask[y][half:follow.shape[1]] == 255)) + half # 计算分割线右端平均位置
mid = (left + right) // 2 # 计算拟合中点
vibra = abs(mid - half) # 振荡偏差
# V3改动:检测到异常振荡则判定为十字路口,并保持直行
if vibra > 30 and y < 479:
crossroads = True
mid = int(mid)
half = mid # 递归,从下往上确定分割线
follow[y, mid] = 255 # 画出拟合中线
if y == 360: # 设置指定提取中点的纵轴位置
mid_output = mid
if crossroads:
print("crossroads!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
mid_output = halfWidth
cv.circle(follow, (mid_output, 360), 5, 255, -1) # opencv为(x,y),画出指定提取中点
error = follow.shape[1] // 2 - mid_output # 计算图片中点与指定提取中点的误差
return follow, error # error为正数右转,为负数左转
n = -1
# 存放图片的文件夹路径
path = "./phone"
imglist = getFileList(path, [])
for imgpath in imglist:
n += 1
if n < 0:
continue
img = cv.imread(imgpath)
img = cv.resize(img, (640, 480))
# HSV阈值分割
img_hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)
mask = cv.inRange(img_hsv, np.array([43, 60, 90]), np.array([62, 255, 255]))
follow = mask.copy()
follow, error = mid(follow, mask)
print(n, f"error:{error}")
cv.imshow("img", img)
cv.imshow("mask", mask)
cv.imshow("follow", follow)
cv.waitKey(0)
cv.destroyAllWindows()
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