實現車道線檢測
阿新 • • 發佈:2022-05-11
當今計算機視覺在我們的日常生活中運用的十分廣泛,例如人臉識別、自動駕駛、等等
由於對自動駕駛十分感興趣,因此就花了一些時間實現了車道線檢測
環境
筆者的環境配置如下:
ubuntu 16.04
python3.7
opencv >=4.0
說明:這裡的系統以及python的版本都不是固定的,讀者使用win10 win7也是可以的
但是python的版本一定要是3.x的版本
第三方庫
這裡使用的第三方庫,是大家比較熟悉的opencv以及numpy
import cv2
import numpy as np
函式
def make_coordinate(image,line_parameters): slope,intercept=line_parameters # print(image.shape) y1=image.shape[0] y2=int(y1*(3/5)) x1=int((y1-intercept)/slope) x2 = int((y2 - intercept) / slope) return np.array([x1,y1,x2,y2]) def average_slope_intercept(image,lines): left_fit=[] right_fit=[] for line in lines: x1,y1,x2,y2=line.reshape(4) paraneters=np.polyfit((x1,x2),(y1,y2),1) slope=paraneters[0] intercept=paraneters[1] if slope<0: left_fit.append((slope,intercept)) else: right_fit.append((slope,intercept)) left_fit_average=np.average(left_fit,axis=0) right_fit_average=np.average(right_fit,axis=0) left_line=make_coordinate(image,left_fit_average) right_line=make_coordinate(image,right_fit_average) return np.array([left_line,right_line]) def canny(image): gray=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY) blur=cv2.GaussianBlur(gray,(5,5),0) canny=cv2.Canny(blur,50,150) return canny def display_lines(image,lines): line_image=np.zeros_like(image) if lines is not None: for x1,y1,x2,y2 in lines: # x1,y1,x2,y2=line.reshape(4) cv2.line(line_image,(x1,y1),(x2,y2),(0,255,0),10) return line_image def region_of_interest(image): height=image.shape[0] polygons=np.array([ [(200,height),(1100,height),(550,250)] ]) mask=np.zeros_like(image) cv2.fillPoly(mask,polygons,255) masked_image=cv2.bitwise_and(image,mask) return masked_image
測試(圖片)
image = cv2.imread("test_image.jpg") lane_image = np.copy(image) canny_image=canny(lane_image) cropped_image=region_of_interest(canny_image) lines=cv2.HoughLinesP(cropped_image,2,np.pi/180,100,np.array([]),minLineLength=40,maxLineGap=5) averaged_lines=average_slope_intercept(lane_image,lines) line_image=display_lines(lane_image,averaged_lines) combo_image=cv2.addWeighted(lane_image,0.8,line_image,1,1) cv2.imshow("result",combo_image) cv2.waitKey(0)
最終的效果如下圖所示:
測試(視訊)
cap=cv2.VideoCapture("test2.mp4") while(cap.isOpened()): _,frame=cap.read() canny_image = canny(frame) cropped_image = region_of_interest(canny_image) lines = cv2.HoughLinesP(cropped_image, 2, np.pi / 180, 100, np.array([]), minLineLength=40, maxLineGap=5) averaged_lines = average_slope_intercept(frame, lines) line_image = display_lines(frame, averaged_lines) combo_image = cv2.addWeighted(frame, 0.8, line_image, 1, 1) cv2.imshow("result", combo_image) if cv2.waitKey(1) & 0xFF==ord('q'): break cap.release() cv2.destroyAllWindows()
效果如下圖所示:
由於筆者能力有限,如有描述不準確的地方還請諒解。
希望大家多動手實踐,共同進步。