我是OpenCV的新手。我正在使用anaconda spyder控制台来编写Python代码。我在这里使用了代码表单(https://www.pyimagesearch.com/2014/08/25/4-point-opencv-getperspective-transform-example/) 代码是我被击中的是:
# USAGE
# python transform_example.py --image images/example_01.png --coords "[(73, 239), (356, 117), (475, 265), (187, 443)]"
# python transform_example.py --image images/example_02.png --coords "[(101, 185), (393, 151), (479, 323), (187, 441)]"
# python transform_example.py --image images/example_03.png --coords "[(63, 242), (291, 110), (361, 252), (78, 386)]"
# import the necessary packages
from pyimagesearch.transform import four_point_transform
import numpy as np
import argparse
import cv2
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", help = "path to the image file")
ap.add_argument("-c", "--coords",
help = "comma seperated list of source points")
args = vars(ap.parse_args())
# load the image and grab the source coordinates (i.e. the list of
# of (x, y) points)
# NOTE: using the 'eval' function is bad form, but for this example
# let's just roll with it -- in future posts I'll show you how to
# automatically determine the coordinates without pre-supplying them
image = cv2.imread(args["image"])
pts = np.array(eval(args["coords"]), dtype = "float32")
# apply the four point tranform to obtain a "birds eye view" of
# the image
warped = four_point_transform(image, pts)
# show the original and warped images
cv2.imshow("Original", image)
cv2.imshow("Warped", warped)
cv2.waitKey(0)
在第号行。 13 - 17可以有人确切地说出发生了什么。我知道我需要获取图像,获取纸张坐标(这些行是为此目的)但我无法获取图像文件。
答案 0 :(得分:2)
在提供的链接中,使用可选参数解析参数,即参数必须以add_argument()
中提到的字符串开头。
所以在你的情况下你有:
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", help = "path to the image file")
ap.add_argument("-c", "--coords", help = "comma seperated list of source points")
args = vars(ap.parse_args())
注意"--image"
和"--coords"
。这些是可选参数,在终端中执行代码之前必须提到这些字符串。
所以在终端上输入:
python transform_example.py --image images/example_01.png --coords "[(73, 239), (356, 117), (475, 265), (187, 443)]"
有关参数解析及其各种方式的更多详细信息,请参阅THIS PAGE。