小编Chr*_*ice的帖子

我正在完成此处找到的 Python 和 OpenCV 头部姿势估计教程：

https://www.learnopencv.com/head-pose-estimation-using-opencv-and-dlib/

我能够准确地将 3D 点投影到 2D 图像上。但是，我无法理解我使用计算的欧拉角（偏航、俯仰、滚转）的实际含义cv2.decomposeProjectionMatrix

我需要知道这些值是否对应于 (yaw, pitch, roll) 或 (roll, pitch, yaw) 等。此外，我需要了解所使用的轴方向，以便我知道旋转度数在哪里从测量。

输出图像：https : //www.learnopencv.com/wp-content/uploads/2016/09/head-pose-example-1024x576.jpg

输出角度：[[-179.30011146], [ 53.77756583], [-176.6277211 ]]

这是我的代码

# --- Imports ---
import cv2
import numpy as np
# --- Main ---
if __name__ == "__main__":

    # Read Image
    im = cv2.imread("headPose.jpg");
    size = im.shape

    #2D image points. If you change the image, you need to change vector
    image_points = np.array([
                                (359, 391),     # …

我已经在互联网上搜索了几个小时，了解一些有关如何理解返回的欧拉角的文档cv2.decomposeProjectionMatrix。

我的问题看起来很简单，我有一张飞机的二维图像。 我希望能够从该图像中得出飞机相对于相机的方向。最终，我正在寻找外观和凹陷（即方位角和仰角）。我有与图像中选择的 2D 特征相对应的 3D 坐标 - 在我的代码中列出如下。

# --- Imports ---
import os
import cv2
import numpy as np

# --- Main ---
if __name__ == "__main__":

    # Load image and resize
    THIS_DIR = os.path.abspath(os.path.dirname(__file__))
    im = cv2.imread(os.path.abspath(os.path.join(THIS_DIR, "raptor.jpg")))
    im = cv2.resize(im, (im.shape[1]//2, im.shape[0]//2))
    size = im.shape

    # 2D image points
    image_points = np.array([
                    (230, 410),     # Nose
                    (55, 215),      # right forward wingtip
                    (227, 170),     # right aft outboard horizontal
                    (257, …

我试图从Zillow收集数据是不成功的.

例:

url = https://www.zillow.com/homes/for_sale/Los-Angeles-CA_rb/?fromHomePage=true&shouldFireSellPageImplicitClaimGA=false&fromHomePageTab=buy

我想从洛杉矶的所有家庭中提取地址,价格,zestimates,地点等信息.

我已经尝试使用像BeautifulSoup这样的包进行HTML抓取.我也尝试过使用json.我几乎肯定Zillow的API没有帮助.我的理解是,API最适合收集特定属性的信息.

我已经能够从其他站点获取信息,但似乎Zillow使用动态ID(更改每次刷新)使得访问该信息变得更加困难.

更新: 尝试使用以下代码,但仍然没有产生任何结果

import requests
from bs4 import BeautifulSoup

url = 'https://www.zillow.com/homes/for_sale/Los-Angeles-CA_rb/?fromHomePage=true&shouldFireSellPageImplicitClaimGA=false&fromHomePageTab=buy'

page = requests.get(url)
data = page.content

soup = BeautifulSoup(data, 'html.parser')

for li in soup.find_all('div', {'class': 'zsg-photo-card-caption'}):
    try:
        #There is sponsored links in the list. You might need to take care 
        #of that
        #Better check for null values which we are not doing in here
        print(li.find('span', {'class': 'zsg-photo-card-price'}).text)
        print(li.find('span', {'class': 'zsg-photo-card-info'}).text)
        print(li.find('span', {'class': 'zsg-photo-card-address'}).text)
        print(li.find('span', {'class': 'zsg-photo-card-broker-name'}).text)
    except :
        print('An error occured')