Node.js 获取一个图像在另一个图像中的位置
我有一个显示网站的浏览器截图。 现在我想找出网站(视口)的位置(相对于整个屏幕截图)。如图中黑色边框的矩形所示: 在开始图像处理之前,我有可能在网站的DOM中添加任何内容 我已经尝试生成二维码,将其添加到视口的左上角和右下角,然后使用imagemagick确定二维码在较大图像中的位置:Node.js 获取一个图像在另一个图像中的位置,node.js,image,image-processing,imagemagick,frontend,Node.js,Image,Image Processing,Imagemagick,Frontend,我有一个显示网站的浏览器截图。 现在我想找出网站(视口)的位置(相对于整个屏幕截图)。如图中黑色边框的矩形所示: 在开始图像处理之前,我有可能在网站的DOM中添加任何内容 我已经尝试生成二维码,将其添加到视口的左上角和右下角,然后使用imagemagick确定二维码在较大图像中的位置: compare-度量“rmse”-子图像搜索-相异度阈值“0.1”-虚拟像素“edge”“haystack.png”“needle.png”“results.png” 然而,这需要很长时间。事实上,我在40分
compare-度量“rmse”-子图像搜索-相异度阈值“0.1”-虚拟像素“edge”“haystack.png”“needle.png”“results.png”
然而,这需要很长时间。事实上,我在40分钟后就退出了
我使用了二维码,因为通过使用时间戳,我可以非常确定这张图片不会在网站上的任何其他地方找到
另外,截图中二维码的大小是原始二维码的两倍,但我想这是因为我的mac屏幕有144dpi
我使用的是node.js,所以我需要一些可以通过命令行执行的东西(比如imagemagick),这样我就可以从节点或直接节点模块执行它
我有一个优势,我可以选择什么图像,我想在更大的图像搜索。我想知道什么是被发现的是一个有用的信息来加速这个过程(但是我不知道如何使用这些信息)。 < P>我有一些建议,如果你发现子图像搜索太慢,你可以考虑加快搜索速度。p> 1。减小图像大小 我做了一个小实验来测试在不同大小的干草堆中寻找不同大小的针,如下所示:
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
Haystack:200x200, needle:10x10, time:2
Haystack:200x200, needle:20x20, time:2
Haystack:200x200, needle:40x40, time:2
Haystack:400x400, needle:10x10, time:8
Haystack:400x400, needle:20x20, time:8
Haystack:400x400, needle:40x40, time:10
Haystack:800x800, needle:10x10, time:33
Haystack:800x800, needle:20x20, time:36
Haystack:800x800, needle:40x40, time:47
并发现大小如何影响搜索时间,如下所示:
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
Haystack:200x200, needle:10x10, time:2
Haystack:200x200, needle:20x20, time:2
Haystack:200x200, needle:40x40, time:2
Haystack:400x400, needle:10x10, time:8
Haystack:400x400, needle:20x20, time:8
Haystack:400x400, needle:40x40, time:10
Haystack:800x800, needle:10x10, time:33
Haystack:800x800, needle:20x20, time:36
Haystack:800x800, needle:40x40, time:47
正如你所看到的,图像的大小有很大的不同
以下是三个大小不等的干草堆,每个干草堆包含两个白色“针”:
以下是ImageMagick认为“针”所在的“结果”图像:
2。尽快停止
如果添加参数-similarity threshold
并将其设置为合理的值,则可以在找到第一个良好匹配项后立即停止搜索,如grep-m 1
这样设置将使其在第一次完美匹配时停止(相似性差为零):
或者这样设置会使它在第一次“非常好的匹配”时停止
默认设置为1.0
,该设置从不匹配,从而导致搜索在整个图像上继续
现在我知道您想要查找视口的顶部和底部,这是两个匹配项,而且快速查找第一个匹配项似乎没有用。但是孔子,他说“旋转你的形象”:-)
因此,找到您的第一个(即顶部)匹配,然后将图像(和针)旋转180度并再次搜索,但这次您是从底部搜索,可以再次在第一个匹配处停止。(也旋转您的结果。)
3。使用所有这些可爱的内核,你的付费并行化强>
你可以将图像分割成几个部分,然后并行搜索,以利用你花了这么多钱买的那些可爱的英特尔内核。你需要小心一点,重叠一点,这样你的针就不会跨过你切割的边界,但是你所需要的只是在一条长条上加上你的针到搜索区域的宽度。。。像这样
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
((a=h/2))
((b=h/2))
((c=a+n))
((d=b+n))
((e=a-n))
((f=b-n))
# Measure time for parallel search, including dividing up image
start=$SECONDS
convert haystack.png -crop ${c}x${d}+0+0 +repage h1.png
convert haystack.png -crop ${a}x${b}+${a}+0 +repage h2.png
convert haystack.png -crop ${a}x${b}+0+${b} +repage h3.png
convert haystack.png -crop ${c}x${d}+${e}+${f} +repage h4.png
for p in 1 2 3 4; do
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search h${p}.png needle.png null: > /dev/null 2>&1 &
done
wait
end=$SECONDS
((elapsed=end-start))
echo Parallel Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
您可以看到并行时间比单线程时间快了近4倍:
Haystack:200x200, needle:10x10, time:2
Parallel Haystack:200x200, needle:10x10, time:0
Haystack:200x200, needle:20x20, time:2
Parallel Haystack:200x200, needle:20x20, time:1
Haystack:200x200, needle:40x40, time:2
Parallel Haystack:200x200, needle:40x40, time:1
Haystack:400x400, needle:10x10, time:8
Parallel Haystack:400x400, needle:10x10, time:2
Haystack:400x400, needle:20x20, time:8
Parallel Haystack:400x400, needle:20x20, time:3
Haystack:400x400, needle:40x40, time:10
Parallel Haystack:400x400, needle:40x40, time:4
Haystack:800x800, needle:10x10, time:33
Parallel Haystack:800x800, needle:10x10, time:10
Haystack:800x800, needle:20x20, time:36
Parallel Haystack:800x800, needle:20x20, time:11
Haystack:800x800, needle:40x40, time:47
Parallel Haystack:800x800, needle:40x40, time:14
我有一些建议,如果你发现子图像搜索速度太慢,你可能会考虑加快搜索速度。p> 1。减小图像大小 我做了一个小实验来测试在不同大小的干草堆中寻找不同大小的针,如下所示:
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
Haystack:200x200, needle:10x10, time:2
Haystack:200x200, needle:20x20, time:2
Haystack:200x200, needle:40x40, time:2
Haystack:400x400, needle:10x10, time:8
Haystack:400x400, needle:20x20, time:8
Haystack:400x400, needle:40x40, time:10
Haystack:800x800, needle:10x10, time:33
Haystack:800x800, needle:20x20, time:36
Haystack:800x800, needle:40x40, time:47
并发现大小如何影响搜索时间,如下所示:
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
Haystack:200x200, needle:10x10, time:2
Haystack:200x200, needle:20x20, time:2
Haystack:200x200, needle:40x40, time:2
Haystack:400x400, needle:10x10, time:8
Haystack:400x400, needle:20x20, time:8
Haystack:400x400, needle:40x40, time:10
Haystack:800x800, needle:10x10, time:33
Haystack:800x800, needle:20x20, time:36
Haystack:800x800, needle:40x40, time:47
正如你所看到的,图像的大小有很大的不同
以下是三个大小不等的干草堆,每个干草堆包含两个白色“针”:
以下是ImageMagick认为“针”所在的“结果”图像:
2。尽快停止
如果添加参数-similarity threshold
并将其设置为合理的值,则可以在找到第一个良好匹配项后立即停止搜索,如grep-m 1
这样设置将使其在第一次完美匹配时停止(相似性差为零):
或者这样设置会使它在第一次“非常好的匹配”时停止
默认设置为1.0
,该设置从不匹配,从而导致搜索在整个图像上继续
现在我知道您想要查找视口的顶部和底部,这是两个匹配项,而且快速查找第一个匹配项似乎没有用。但是孔子,他说“旋转你的形象”:-)
因此,找到您的第一个(即顶部)匹配,然后将图像(和针)旋转180度并再次搜索,但这次您是从底部搜索,可以再次在第一个匹配处停止。(也旋转您的结果。)
3。使用所有这些可爱的内核,你的付费并行化强>
你可以将图像分割成几个部分,然后并行搜索,以利用你花了这么多钱买的那些可爱的英特尔内核。你需要小心一点,重叠一点,这样你的针就不会跨过你切割的边界,但是你所需要的只是在一条长条上加上你的针到搜索区域的宽度。。。像这样
#!/bin/bash
# Create a range of haystack sizes
for h in 200 400 800; do
# And a range of needle sizes
for n in 10 20 40; do
# Create haystack to search in, containing two needles
convert -size ${h}x${h}! gradient:red-black -fill white \
-draw "rectangle 100,100 139,139" \
-draw "rectangle 150,150 189,189" \
haystack.png
# Create a needle this size to search for
convert -size ${n}x${n}! xc:white needle.png
cp haystack.png haystack_${h}x${h}.png
cp needle.png needle${n}x${n}.png
# Search, measuring the time
start=$SECONDS
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search haystack.png needle.png null: > /dev/null 2>&1
end=$SECONDS
((elapsed=end-start))
echo Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
((a=h/2))
((b=h/2))
((c=a+n))
((d=b+n))
((e=a-n))
((f=b-n))
# Measure time for parallel search, including dividing up image
start=$SECONDS
convert haystack.png -crop ${c}x${d}+0+0 +repage h1.png
convert haystack.png -crop ${a}x${b}+${a}+0 +repage h2.png
convert haystack.png -crop ${a}x${b}+0+${b} +repage h3.png
convert haystack.png -crop ${c}x${d}+${e}+${f} +repage h4.png
for p in 1 2 3 4; do
compare -dissimilarity-threshold 1.0 -metric rmse -subimage-search h${p}.png needle.png null: > /dev/null 2>&1 &
done
wait
end=$SECONDS
((elapsed=end-start))
echo Parallel Haystack:${h}x${h}, needle:${n}x${n}, time:$elapsed
done
done
您可以看到并行时间比单线程时间快了近4倍:
Haystack:200x200, needle:10x10, time:2
Parallel Haystack:200x200, needle:10x10, time:0
Haystack:200x200, needle:20x20, time:2
Parallel Haystack:200x200, needle:20x20, time:1
Haystack:200x200, needle:40x40, time:2
Parallel Haystack:200x200, needle:40x40, time:1
Haystack:400x400, needle:10x10, time:8
Parallel Haystack:400x400, needle:10x10, time:2
Haystack:400x400, needle:20x20, time:8
Parallel Haystack:400x400, needle:20x20, time:3
Haystack:400x400, needle:40x40, time:10
Parallel Haystack:400x400, needle:40x40, time:4
Haystack:800x800, needle:10x10, time:33
Parallel Haystack:800x800, needle:10x10, time:10
Haystack:800x800, needle:20x20, time:36
Parallel Haystack:800x800, needle:20x20, time:11
Haystack:800x800, needle:40x40, time:47
Parallel Haystack:800x800, needle:40x40, time:14
我真的不懂