使用OpenCV对车道进行实时检测的实现示例代码

import os
import re
import cv2
import numpy as np
from tqdm import notebook
import matplotlib.pyplot as plt

# 获取帧的文件名
col_frames = os.listdir('frames/') # 读取 frames 文件夹下的所有图片
col_frames.sort(key=lambda f: int(re.sub('\D', '', f))) # 按名称对图片进行排序

# 加载帧
col_images=[]
for i in notebook.tqdm(col_frames):
  img = cv2.imread('frames/'+i)
  col_images.append(img) # 将所有图片添加进 col_images 列表

# 指定一个索引
idx = 457

# plot frame
plt.figure(figsize=(10,10))
plt.imshow(col_images[idx][:,:,0], cmap= "gray")
plt.show()

# 创建0矩阵
stencil = np.zeros_like(col_images[idx][:,:,0])

# 指定多边形的坐标
polygon = np.array([[50,270], [220,160], [360,160], [480,270]])

# 用1填充多边形
cv2.fillConvexPoly(stencil, polygon, 1)

# 画出多边形
plt.figure(figsize=(10,10))
plt.imshow(stencil, cmap= "gray")
plt.show()

# 应用该多边形作为掩码
img = cv2.bitwise_and(col_images[idx][:,:,0], col_images[idx][:,:,0], mask=stencil)

# 画出掩码后的图片
plt.figure(figsize=(10,10))
plt.imshow(img, cmap= "gray")
plt.show()

# 应用图像阈值化
ret, thresh = cv2.threshold(img, 130, 145, cv2.THRESH_BINARY)

# 画出图像
plt.figure(figsize=(10,10))
plt.imshow(thresh, cmap= "gray")
plt.show()

lines = cv2.HoughLinesP(thresh, 1.0, np.pi/180, 30, maxLineGap=200)

# 创建原始帧的副本
dmy = col_images[idx][:,:,0].copy()

# 霍夫线
for line in lines:
  x1, y1, x2, y2 = line[0] # 提取出霍夫线的坐标
  cv2.line(dmy, (x1, y1), (x2, y2), (255, 0, 0), 3) # 将霍夫线画在帧上

# 画出帧
plt.figure(figsize=(10,10))
plt.imshow(dmy, cmap= "gray")
plt.show()

# 输出视频路径
pathOut = 'roads_v2.mp4'

# 视频每秒的帧数
fps = 30.0

# 视频中每一帧的尺寸
height, width = img.shape
size = (width,height)

# 写入视频
out = cv2.VideoWriter(pathOut,cv2.VideoWriter_fourcc(*'DIVX'), fps, size)

for img in notebook.tqdm(col_images):

  # 应用帧掩码
  masked = cv2.bitwise_and(img[:,:,0], img[:,:,0], mask=stencil)

  # 应用图像阈值化
  ret, thresh = cv2.threshold(masked, 130, 145, cv2.THRESH_BINARY)

  # 应用霍夫线变换
  lines = cv2.HoughLinesP(thresh, 1, np.pi/180, 30, maxLineGap=200)
  dmy = img.copy()

  #画出检测到的线
  try:
    for line in lines:
      x1, y1, x2, y2 = line[0]
      cv2.line(dmy, (x1, y1), (x2, y2), (255, 0, 0), 3)

    out.write(dmy)

  except TypeError: 
    out.write(img)

out.release()

import os
import re
import cv2
import numpy as np
from tqdm import notebook
import matplotlib.pyplot as plt

col_frames = os.listdir('frames/')
col_frames.sort(key=lambda f: int(re.sub('\D', '', f)))

col_images=[]
for i in notebook.tqdm(col_frames):
  img = cv2.imread('frames/'+i)
  col_images.append(img)

stencil = np.zeros_like(col_images[0][:,:,0])
polygon = np.array([[50,270], [220,160], [360,160], [480,270]])
cv2.fillConvexPoly(stencil, polygon, 1)

pathOut = 'roads_v2.mp4'

fps = 30.0

height, width = img.shape
size = (width,height)

out = cv2.VideoWriter(pathOut,cv2.VideoWriter_fourcc(*'DIVX'), fps, size)

for img in notebook.tqdm(col_images):

  masked = cv2.bitwise_and(img[:,:,0], img[:,:,0], mask=stencil)

  ret, thresh = cv2.threshold(masked, 130, 145, cv2.THRESH_BINARY)

  lines = cv2.HoughLinesP(thresh, 1, np.pi/180, 30, maxLineGap=200)
  dmy = img.copy()

  try:
    for line in lines:
      x1, y1, x2, y2 = line[0]
      cv2.line(dmy, (x1, y1), (x2, y2), (255, 0, 0), 3)

    out.write(dmy)

  except TypeError: 
    out.write(img)

out.release()