使用OpenCV實現攝像頭測距 [Find distance from camera to object/marker using Python and OpenCV] (GOOGLE:OPENCV 測距)

https://zhuanlan.zhihu.com/p/63149294
https://www.pyimagesearch.com/2015/01/19/find-distance-camera-objectmarker-using-python-opencv/

https://github.com/zxdefying/OpenCV_project/tree/master/distance_to_camera

GITHUB:https://github.com/jash-git/Find-distance-from-camera-to-object-using-Python-and-OpenCV

假設物體的寬度為W，將其放到離相機距離為D 的位置，然後對物體進行拍照。在照片上量出物體的像素寬度P，於是可以得出計算相機焦距F 的公式：

F =（P x D）/ W

比如我在相機前24 英寸距離（D=24 inches）的位置橫著放了一張8.5 x 11 英寸（W=11 inches）的紙，拍照後通過圖像處理得出照片上紙的像素寬度P=248 pixels。

F =（248px x 24in）/ 11in = 543.45

此時移動相機離物體更近或者更遠，我們可以應用相似三角形得到計算物體到相機的距離的公式：

D’=（寬x F）/ P

PDF

Code:

```from imutils import paths
import numpy as np
import imutils
import cv2

# initialize the known distance from the camera to the object, which
# in this case is 24 inches
KNOWN_DISTANCE = 24.0

# initialize the known object width, which in this case, the piece of
# paper is 12 inches wide
KNOWN_WIDTH = 11.0

def get_focalLength():
# load the furst image that contains an object that is KNOWN TO BE 2 feet
# from our camera, then find the paper marker in the image, and initialize
# the focal length
marker = find_marker(image)
focalLength = (marker[1][0] * KNOWN_DISTANCE) / KNOWN_WIDTH

return focalLength

def find_marker(image):
# convert the image to grayscale, blur it, and detect edges
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(gray, 35, 125)

# the contour of paper is not closed, so apply close operation(dilate and erode)
kernel = np.ones((3, 3), np.uint8)
close = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel)

# find the contours in the edged image and keep the largest one;
# we'll assume that this is our piece of paper in the image
cnts = cv2.findContours(close.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
c = max(cnts, key = cv2.contourArea)

# compute the bounding box of the of the paper region and return it
return cv2.minAreaRect(c)

def distance_to_camera(knownWidth, focalLength, perWidth):
# compute and return the distance from the maker to the camera
return (knownWidth * focalLength) / perWidth

if __name__ == "__main__":

focalLength = get_focalLength()

# loop over the images
for imagePath in sorted(paths.list_images("images")):
# load the image, find the marker in the image, then compute the
# distance to the marker from the camera
marker = find_marker(image)
inches = distance_to_camera(KNOWN_WIDTH, focalLength, marker[1][0])

# draw a bounding box around the image and display it
box = cv2.cv.BoxPoints(marker) if imutils.is_cv2() else cv2.boxPoints(marker)
box = np.int0(box)
cv2.drawContours(image, [box], -1, (0, 255, 0), 2)
cv2.putText(image, "%.2fft" % (inches / 12),
(image.shape[1] - 200, image.shape[0] - 20), cv2.FONT_HERSHEY_SIMPLEX,
2.0, (0, 255, 0), 3)
cv2.imshow(imagePath.split('/')[-1], image)

if cv2.waitKey(0) & 0xFF == ord('q'):
cv2.destroyAllWindows()```

One thought on “使用OpenCV實現攝像頭測距 [Find distance from camera to object/marker using Python and OpenCV] (GOOGLE:OPENCV 測距)”

1. jash.liao@qq.com 說：

公式推導:

已知焦距公式
F(像素)=P(像素)*D(公分)/W(公分)
其中
P :畫面中物體的像素寬度
W:物體實際寬度(事先取得)
D:相機與物體的實際距離(可用測距工具取得)

=> D’=F*W/P=W*F/P