I have been doing a ton of searching but cant quite find the answer to this one.
I have a series of relatively simple SVG images. I have drawn SVG rectangles over key areas of the images that I am interested in and would now like to extract those areas as PNG images. I have no idea the best way to approach this problem.
Idea 1) Convert the whole SVG to PNG then use say PIL to crop the image down after somehow converting the SVG rect coordinates to PNG coordinates. I am starting to work towards this method now, but I am hoping there is a better, and/or easier way to do this!
I am using Python 3.7 for this.
Edit 1:
This is a screen shot of what I am looking at. The original image is SVG, I would like to extract the areas under the green rectangles as PNG images.
Edit 2:
Working from Idea 1, I have the following code that basically sets the viewBox on the SVG image to one of the green rectangles, then sets the width and height of it. From there I am using CairoSVG to export the SVG as PNG.
import cairosvg
import xml.etree.ElementTree as ET
...
with gzip.open(fileObj.filePath,'rb') as file:
svg=file.read()
svg=svg.decode('utf-8')
svgRoot=ET.fromstring(svg)
ET.register_namespace("","http://www.w3.org/2000/svg")
ET.register_namespace('xlink', "http://www.w3.org/1999/xlink")
annots = meta['annots']
for a in annots:
r = ET.fromstring(a['g'])
vb=" ".join([r.get('x'),r.get('y'),r.get('width'),r.get('height')])
svgRoot.set("viewBox",vb)
svgRoot.set("width",'128px')
svgRoot.set("height",'128px')
svg = ET.tostring(svgRoot, encoding="unicode")
cairosvg.svg2png(svg,write_to="/home/test.png")
Unfortunately it is EXTREMELY slow! On the order of more than a minute to extract two PNGs. The SVG files are quite large (2 - 3 mb zipped) and very detailed. I am not certain how CairoSVG works, but does it render everything in the SVG even if it isnt visible before saving the visible part to PNG?
Any advise on optimising or speeding this up would be a huge help.
This worked for me in the end, though it is quite slow on larger SVG images:
import gzip
import cairosvg
import xml.etree.ElementTree as ET
...
with gzip.open(fileObj.filePath,'rb') as file:
svg=file.read()
svg=svg.decode('utf-8')
svgRoot=ET.fromstring(svg)
ET.register_namespace("","http://www.w3.org/2000/svg")
ET.register_namespace('xlink', "http://www.w3.org/1999/xlink")
annots = meta['annots']
for a in annots:
r = ET.fromstring(a['g'])
vb=" ".join([r.get('x'),r.get('y'),r.get('width'),r.get('height')])
svgRoot.set("viewBox",vb)
svgRoot.set("width",'128px')
svgRoot.set("height",'128px')
svg = ET.tostring(svgRoot, encoding="unicode")
cairosvg.svg2png(svg,write_to="/home/test.png")
Related
Ok I will admit to being a noob with Gideros. I am trying to import an svg file. I followed the same procedure as you would do for a png file, that is create a texture using:
myTexture = Texture.new("orangeSquare.svg")
orangeSquare = Bitmap.new(myTexture)
stage:addChild(orangeSquare)
Unsurprisingly it doesn't work (output gives orangeSquare.svg: Error while reading image file. and program does not run) as it is not a bitmap file. Is there an alternative to import svg files? It is probably a very simple solution but I have been searching for some time without an answer. I am considering giving up on Gideros if I don't find an answer to what should be a simple problem.
You can not import the svg directly, you need to pass the svg data:
--Banana shape, SVG path format
local banana = "M8.64,223.948c0,0,143.468,3.431,185.777-181.808c2.673-11.702-1.23-20.154,1.316-33.146h16.287c0,0-3.14,17.248,1.095,30.848c21.392,68.692-4.179,242.343-204.227,196.59L8.64,223.948z"
p=Path2D.new()
p:setSvgPath(banana) --Set the path from a SVG path description
p:setLineThickness(5) -- Outline width
p:setFillColor(0xFFFF80,0.7) --Fill color
p:setLineColor(0x404000) --Line color
p:setAnchorPosition(100,100)
stage:addChild(p)
You can find more info on their wiki: https://wiki.giderosmobile.com/index.php?search=svg&title=Special%3ASearch&go=Go&fulltext=1
They also have it as a sample project when you open gideros studio.
I have an image where I want to detect aruco markers DICT_4X4_50. However, the image resolution seems to present itself as a major problem. But it is rather strange, since aruco detection function is able to detect markers on much difficult images, but not this one. Is there any way to detect them?
I already tried changing some parameter values of detector parameters, but it didn't help, and modifying values randomly does not seem to be the best option at all. This is the image:
This was my basic code:
import cv2
from cv2 import aruco
img = cv2.imread('image.png')
aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_50)
parameters = aruco.DetectorParameters_create()
# Detect the markers.
corners, ids, rejectedImgPoints = aruco.detectMarkers(img,aruco_dict,parameters=parameters)
out = aruco.drawDetectedMarkers(img, corners, ids)
cv2.imshow("out",out)
cv2.waitKey(0)
cv2.destroyAllWindows()
Thank you!
In you code you have not defined the detect markers code
cv2.detectMarkers()
Found the problem. Symbols are vertically rotated. If the image is flipped, it will be fine. :P No wonder Aruco could not solve that.
I'm trying to open a SAR image from sentinel-1. I can view the tiff file in QGIS, so I know the data is there, but when I go to open and view/show it in python, all of the modules I could use to open the data produce a NaN area, basically insinuating that there is no data in the image. Visualizing the image produces a completely black image, however the shape is correct.
Here is the code where I read in the image:
img = skimage.io.imread('NewData.tif', as_gray = True, plugin = 'tifffile')
with rio.open(r'NewData.tif') as src:
img2 = src.read()
imgMeta = src.profile
print(img)
skimage.io.imshow(img)
Any help would be appreciated.
thank you
The problem is not on the way rasterio or skimage is importing the image, but on the way it is displayed. I am assumign you are working with Calibrated SAR images that ARE NOT converted to the decibel dB scale. Here is the problem, the dynamic range of your data.
The issue here is that by default, the color ramp is not being strech according to the distribution of values in the raster histogram. In QGIS, SNAP or many other EO-related softwares, the color distribution matches the histogram to produce proper visualizations.
Solution: either you make that happen in your code or simply convert your backscatter values to decibel (which is a very common procedure when working with SAR data and produces an almost normal distrubution of the data). The conversion can be done in a EO software or more directly in your imported image with:
srcdB = 10*np.log10(src)
Once done, you can properly display your image:
import rasterio
from rasterio.plot import show
import numpy as np
with rio.open(r'/.../S1B_IW_GRDH_1SDV_20190319T161451_20190319T161520_015425_01CE3C_A401_Cal.tif') as src:
img2 = src.read()
imgMeta = src.profile
srcdB = 10*np.log10(src) # to decibel
show(srcdB, cmap='gray') # show using rasterio
I am trying to write images over each other. Ideally, what I want to do is to write every image in one folder over every image in another folder and output every unique image to another folder. So far, I am just working on having one image write over one image, but I can't seem to get that to work.
import numpy as np
import cv2
import matplotlib
def opencv_createsamples():
mask = ('resized_pos/2')
img = cv2.imread('neg/1')
new_img = img * (mask.astype(img.dtype))
cv2.imwrite('samp', new_img)
opencv_createsamples()
It would be helpful to have more information about your errors.
Something that stands out immediately is the lack of file type extensions. Your images are probably not being read correctly, to begin with. Also, image sizes would be a good thing to consider so you could resize as required.
If the goal is to blend images, considering the alpha channel is important. Here is a relevant question on StackOverflow:How to overlay images in python
Some other OpenCV docs that have helped me in the past: https://docs.opencv.org/trunk/d0/d86/tutorial_py_image_arithmetics.html
https://docs.opencv.org/3.1.0/d5/dc4/tutorial_adding_images.html
Hope this helps!
I've tried to convert a SVG file to PNG with antialiasing off in Magick++ but I wasn't successful. But I was able to convert the SVG file to PDF with another program and the use the ImageMagick convert command to convert the PDF file to PNG.
How can I use ImageMagick to do it? The command I use for converting PDF to PNG is this:
convert +antialias -interpolate Nearest -filter point -resize 1000x1000 "img.pdf" PNG24:"filter.png"
Is there any way to use Magick++ to do that or better, convert SVG to PNG directly with antialiasing off?
Thanks in advance.
Edit:
The answer given in this post doesn't work for me. Possible because I'm using a colored SVG instead of 1-bit alpha channel. Also I mentioned in my question that I'm also looking for a way to do this in Magick++.
Magick++ has the Magick::Image::textAntiAlias & Magick::Image::strokeAntiAlias methods available, but they would only be useful if your parsing the SVG and rebuilding the image (i.e. roll-your-own SVG engine) one SVG element at a time.
As #ccprog pointed out in the comments; once the decoder utility rasters the vectors, the damage is done & setting the flags would not have an effect on the resulting resize.
Without seeing the SVG, I can only speculate what the problem is. I would suggest setting the document size before reading the SVG content.
For example, read the image at a smaller size than resample up.
Magick::Image img;
img.size(Magick::Geometry(100, 100)); // Decode to a small context
img.read("input.svg");
img.interpolate(Magick::NearestInterpolatePixel);
img.filterType(Magick::PointFilter);
img.resize(Magick::Geometry(600, 600));
img.write("PNG24:output#100x100.png");
Or render at larger size then the finial image.
Magick::Image img;
img.size(Magick::Geometry(1000, 1000)); // Decode to a larger context
img.read("input.svg");
img.interpolate(Magick::NearestInterpolatePixel);
img.filterType(Magick::PointFilter);
img.resize(Magick::Geometry(600, 600));
img.write("PNG24:output#1000x1000.png");
Update from comments
For Postscript (PDF) & True-Type antialiasing, you would set Magick::Image::textAntiAlias (or Magick::Image::antiAlias if using IM6) to false. Just ensure that the density is set to allow any overhead.
Magick::Image img;
img.density(Magick::Point(300));
if (MagickLibVersion < 0x700) {
img.antiAlias(false);
} else {
img.textAntiAlias(false);
}
img.interpolate(Magick::NearestInterpolatePixel);
img.filterType(Magick::PointFilter);
img.read("input.pdf");
img.resize(Magick::Geometry(1000, 1000));
img.write("PNG24:output.png");