在不使用浏览器的情况下使用 Python 捕获嵌入的谷歌地图图像 [英] Capture embedded google map image with Python without using a browser

问题描述

我注意到，从 Google 地图页面，您可以获得一个嵌入"链接，将其放入 iframe 并在浏览器中加载地图.(这里没有消息)

I have noticed that, from Google Maps page, you can get an "embed" link to put inside an iframe and load the map in a browser. (no news here)

图像大小可以调整得非常大，所以我对将一些大图像作为单个 .PNG 文件感兴趣.

The image size can be adjusted to be very large, so I am interested in getting som big images as single .PNGs.

更具体地说，我想从边界框(右上和左下坐标)定义一个矩形区域，并使用适当的缩放因子获取相应的图像.

More specifically, I would like to define a rectangular area from a bounding box (upper-right and lower-left coordinates), and get the corresponding image, with an appropriate zoom factor.

但我的问题是:如何使用 Python 将这张地图的像素内容"作为图像对象获取?

But my question is: How can I use Python to get the "pixel content" of this map as an image object?

(我的理由是:如果浏览器可以获取并渲染这样的图像内容，那么 Python 也应该能够做到).

(My rationale is: if the browser can get and render such image content, then Python should be capable of doing it, too).

这是显示我的示例地图的 HTML 文件的内容:

this is the content of the HTML file that shows my sample map:

<iframe 
    width="2000"
    height="1500"
    frameborder="0"
    scrolling="yes"
    marginheight="0"
    marginwidth="0"
    src="http://maps.google.com.br/maps?hl=pt-BR&amp;ll=-30.027489,-51.229248&amp;spn=1.783415,2.745209&amp;z=10&amp;output=embed"/>

我按照 Ned Batchelder 的建议做了，并使用从上面的 iframe 中获取的 src 地址读取了 urllib.urlopen() 调用的内容.结果是大量的 javascript 代码，我认为这与 Google Maps JavaScript API 有关.所以，问题仍然存在:我怎样才能从 Python 中的所有这些东西中做一些有用的东西来获取地图图像?

I did as suggested by Ned Batchelder, and read the content of an urllib.urlopen() call using the src address taken from the iframe above. The result was a lot of javascript code, which I think has to do with the Google Maps JavaScript API. So, the question lingers: how could I do some useful stuff from all this stuff in Python in order to get the map image?

此链接似乎包含有关 Google 地图如何平铺地图的一些非常相关的信息:http://www.codeproject.com/KB/scrapbook/googlemap.aspx

this link appears to contain some pretty relevant info on how Google Maps tiles their maps: http://www.codeproject.com/KB/scrapbook/googlemap.aspx

还有:http://econym.org.uk/gmap/howitworks.htm

推荐答案

感谢所有的回答.我最终以另一种方式解决了这个问题，使用 Google Maps Static API 和一些公式将坐标空间转换为像素空间，这样我就可以获得可以很好地缝合"在一起的精确图像.

I thank for all the answers. I ended up solving the problem another way, using Google Maps Static API and some formulas to convert from Coordinate space to Pixel space, so that I can get precise images that "stitch" nicely together.

对于任何感兴趣的人，这是代码.如果对某人有帮助，请评论！

For anyone interested, here is the code. If it helps someone, please comment!

==============================

=============================

import Image, urllib, StringIO
from math import log, exp, tan, atan, pi, ceil

EARTH_RADIUS = 6378137
EQUATOR_CIRCUMFERENCE = 2 * pi * EARTH_RADIUS
INITIAL_RESOLUTION = EQUATOR_CIRCUMFERENCE / 256.0
ORIGIN_SHIFT = EQUATOR_CIRCUMFERENCE / 2.0

def latlontopixels(lat, lon, zoom):
    mx = (lon * ORIGIN_SHIFT) / 180.0
    my = log(tan((90 + lat) * pi/360.0))/(pi/180.0)
    my = (my * ORIGIN_SHIFT) /180.0
    res = INITIAL_RESOLUTION / (2**zoom)
    px = (mx + ORIGIN_SHIFT) / res
    py = (my + ORIGIN_SHIFT) / res
    return px, py

def pixelstolatlon(px, py, zoom):
    res = INITIAL_RESOLUTION / (2**zoom)
    mx = px * res - ORIGIN_SHIFT
    my = py * res - ORIGIN_SHIFT
    lat = (my / ORIGIN_SHIFT) * 180.0
    lat = 180 / pi * (2*atan(exp(lat*pi/180.0)) - pi/2.0)
    lon = (mx / ORIGIN_SHIFT) * 180.0
    return lat, lon

############################################

# a neighbourhood in Lajeado, Brazil:

upperleft =  '-29.44,-52.0'  
lowerright = '-29.45,-51.98'

zoom = 18   # be careful not to get too many images!

############################################

ullat, ullon = map(float, upperleft.split(','))
lrlat, lrlon = map(float, lowerright.split(','))

# Set some important parameters
scale = 1
maxsize = 640

# convert all these coordinates to pixels
ulx, uly = latlontopixels(ullat, ullon, zoom)
lrx, lry = latlontopixels(lrlat, lrlon, zoom)

# calculate total pixel dimensions of final image
dx, dy = lrx - ulx, uly - lry

# calculate rows and columns
cols, rows = int(ceil(dx/maxsize)), int(ceil(dy/maxsize))

# calculate pixel dimensions of each small image
bottom = 120
largura = int(ceil(dx/cols))
altura = int(ceil(dy/rows))
alturaplus = altura + bottom


final = Image.new("RGB", (int(dx), int(dy)))
for x in range(cols):
    for y in range(rows):
        dxn = largura * (0.5 + x)
        dyn = altura * (0.5 + y)
        latn, lonn = pixelstolatlon(ulx + dxn, uly - dyn - bottom/2, zoom)
        position = ','.join((str(latn), str(lonn)))
        print x, y, position
        urlparams = urllib.urlencode({'center': position,
                                      'zoom': str(zoom),
                                      'size': '%dx%d' % (largura, alturaplus),
                                      'maptype': 'satellite',
                                      'sensor': 'false',
                                      'scale': scale})
        url = 'http://maps.google.com/maps/api/staticmap?' + urlparams
        f=urllib.urlopen(url)
        im=Image.open(StringIO.StringIO(f.read()))
        final.paste(im, (int(x*largura), int(y*altura)))
final.show()

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