Question

我尝试了各种各样的方法，但我仍然得到apx 2-3 fps。

import cv2

将numpy导入为np

＆＃13;

import cv2
import numpy as np

##cap = cv2.imread('C:\\Users\\efeongan\\Desktop\\PYTHOn_OPENCV\\linetest.mp4')
cap = cv2.VideoCapture('C:\\Users\\efeongan\\Desktop\\PYTHOn_OPENCV\\linetest.mp4')
while True:
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    lowbg = np.array([0,0,0])
    highbg = np.array([50, 50, 50])
    kernel = np.ones([10, 10], np.uint8)
    mask = cv2.inRange(frame, lowbg, highbg)
    res = cv2.bitwise_and(gray, gray, mask = mask)
    dilation = cv2.dilate(res, kernel, iterations = 1)
    lines = cv2.HoughLinesP(dilation,rho=0.02,theta=np.pi/500, threshold=100,lines=np.array([]), minLineLength= 0)
    a,b,c = lines.shape
    if lines[1][0][0] > 240:
        diff = lines[1][0][0] - 240
        print(diff)
    if lines[1][0][0] < 240:
        diff = 220 - lines[1][0][0]
        print(diff)
    for i in range(a):
        cv2.line(dilation, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (255, 255, 255), 3, cv2.LINE_AA)
    cv2.line(frame, (240, 800), (240 + diff, 800), (255,0,0),10)
    cv2.putText(frame,str(diff),(240 + diff,800), cv2.FONT_HERSHEY_SIMPLEX, 1, 255)
    print("x", lines[1][0][0], cnts)
    cv2.imshow('raw', frame)
    k = cv2.waitKey(1)
    if k == 27:
        brak
cv2.desrtroyAllWindows()

＆＃13;

Answer 1

尝试使用较低的帧分辨率。您可以尝试使用较小的分辨率，并查看准确度如何随着分辨率的降低而降低，并找到折衷方案。

另一种可能性是仅处理每个帧的选定区域。假设您在图像的一个区域中找到要遵循的线条。您可以假设线的位置在下一帧中没有太大变化，只处理该线周围的区域。

代码低FPS的OpenCV Python Line

1 个答案: