We want to clip the image into a circle and stamp another image (a frame/shadow) on top of it.
Right now we're running imagemagick to do this on our own server, I'm wondering if I can offload that operation to TransloadIt somehow to be more scalable. It looks like TransLoadIt is running ImageMagick itself to do operations but not all ImageMagick capabilities are available.
Is this something we could possibly do using TransLoadIt?
I think it should be possible to first stamp a watermark on it that contains an opaque background with a transparent circle. Then in a second step, you could set the opaque color to be transparent.
Related
I have a large number of PSD files which contain semi-transparent layers. These layers are not getting flattened correctly regardless of what flags I use via convert or mogrify
The simplest form looks as follows:
convert -background transparent source.psd -flatten output.png
Here is what the source image looks like in Photoshop. Note that this is a drop shadow layer and not a layer effect:
Here is how it comes out:
This may not be obvious from the photoshop background, so here it is in laid over a grey background:
Source:
Output:
EDIT:
I dug a bit into what is happening in the numbers. For the initial source image, the shadow is completely black and the alpha fades in. For the output image, the alpha is not as high, but it compensates by inaccurately lightening the image in a somewhat bumpy fashion. Its almost as if its pre-multiplied, but its taking the background as white?
Here is a strait RGB render without alpha multiplied in:
Source:
Output:
In other words, the RBG values are not at all being preserved. Alpha is being dimmed, but not distorted as theses values are. My guess would be some sort of rounding error based on trying to extrapolate the color from the alpha as though it is trying to "unpre-multiply" the values. Any help is appreciated.
Short answer is it is fixed in V7 of the software (I think). I run mac and the installer for V7 doesn't work well at all and it appears unstable. After running it on an Ubuntu VM, it works good. I have also confirmed with another user that V6 has this problem and V7 does not on Windows
I have few thousands of images from our vendors. They are models wearing fashion clothing. I need to take only the clothes part of the images and discard the rest and make them transparent background. All the images has one color background but they are in different colors. Currently we perform the following steps manually and I need suggestion and help if there is a way to do this automatically or is there a way to do the manual process faster. We used Gimps and script-fu for automating some part of this process (see below steps), but still the remaining manual part is very time consuming. Is there any tool or any programming language or script that can make this process faster?
This is the way we are doing now:
We use Gimps script-fu run in batch to make all images background transparent.
Load one by one each image into Gimps manually
Via Free select took, we mark around the clothes
Remove everything outside the marked clothes area
Export and save image into png format.
Run script-fu in batch to auto crop all the image
I haven't figure out a way (code or script) to do the step 3 automatically. Does anyone know if that even possible? If it is not, is there any tool that could combine step 4-6 into one control key so reduce the key strokes and any faster way to finish these images?
Thank you for your suggestions. This is what I am thinking to do for making my step 3 and 4 automated. Do you think if this approach would work. Is there better way to handle it?
All the images will have transparent background via our batch job. So the idea is to remove the body part now.
Auto crop all the images, so the head and feet to be the topmost and bottommost of the image.
Code a PHP program to detect the skin colors from list of database colors for skin.
Then go to each pixel of image and detect where the skin color starts.
Start from topmost of image, the first pixel has skin color must be the head or neck part. I remove everything above the starting first pixel, so I will be able to get rid of hairs if the image has model with full head. Anything below could be the face and neck, I will just replace the color with transparent background. I still don't know how to get rid of hair in right and left side of the face.
Searching from bottom of image pixels by pixel until match to skin color. I remove everything from that pixel to bottom of the page. This way I can get rid of shoes parts as well.
6.Replace remaining skin part with transparent background.
The problem is the hand sometimes cover the clothes and I am not sure how to handle that. Perhaps if the adjacent pixel is not transparent background then leave that part alone.
I also don't know how to handle the the clothes(dress or blouse) that may have the same color as skin?
Step 3 can be semi-automated. That is, done in such a way that it requires far less human interaction than you are currently using. I get the impression from your question, that you are not a programmer. So, I'll point you to a specific off the shelf tool called Power Stroke. It plugs into non-free tools. There may be a GIMP equivalent. I don't know.
I am new to Matlab, I am working on a project which will take input an image like this
as we can see it has a plain background (blue), and system will generate it's passport size image with given ratios, first I am working to separate background and person, the approach I searched is like if there is a blue in combinations of rgb matrices of image, then it is background, and rest is a person, but I am little bit confused that if this approach is correct or not, if it is correct then how can I find that current pixel is blue or not, how can I do it with matlab function find. Any help would be appreciated.
If you want to crop your image based on person's face, then there is no need in separating the background from the foreground. Nowadays you will easily find ready implementations of face detection, so, unless you want to implement your own method because the ready one fails, this should be a non-issue. See:
Show[img,
Graphics[{EdgeForm[{Yellow, Thick}], Opacity[0],
Rectangle ###
FindFaces[img = Import["http://i.stack.imgur.com/cSwzj.jpg"]]}]]
Supposing the face is detected correctly, you can expand/retract its bounding box to match the size you are after.
I am working on some batch routines to manage large libraries of jpg files. I have a nice routine that will quickly downsize 4mb+ files down to 40kb+. Using CCR.Exif, I can determine if an image needs to be rotated. My problem is that I can't find any code to rotate the image before I save it. I really need to be able to do this without incurring the overhead of bringing the image to screen.
I'm using the built-in jpeg.pas; I found another library by Gabriel Corneanu at CodeCentral, but it hasn't been updated for DXE2. All I need to do is a 90° rotation.
Any help will be greatly appreciated!
JPGs are compressed and must be rendered before you can work with the image data. Even if it is a non-visible canvas, they still need to be loaded into a component that renders them. Then you can use Windows API calls to rotate the image by directly accessing the canvas. I haven't rotated the image before, but I have manipulated it in other ways by accessing the canvas.
GR32 and EFG are both good sites with several components and algorithms. Here is one example on EFG's site that rotates an image. The code is Delphi 3, but it should still work fine for image manipulation.
EFG Example with Source
TImage32 has a method to rotate the image 90 degrees as well. See TImage32.Bitmap.Rotate90. TImage32 is part of the GR32 library and has been updated for Delphi-XE2.
svn co https://graphics32.svn.sourceforge.net/svnroot/graphics32/trunk graphics32
Also see: GR32 Homepage
If you need to rotate JPEG in steps by 90 degree, then look for lossless transformations.
For example irfanview.com has a special plugin DLL for it, though it does not have public API, but maybe you can ask Irfan Author for it or reverse-engineer it with debugger and cff explorer.
a lot of discussion might by just googled, including discussion how it is implemented.
https://www.google.ru/search?client=opera&q=lossless+jpeg+rotation
Component catalogues have that like
http://www.torry.net/quicksearchd.php?String=jpeg+lossless&Title=No
That will not work with rotation finer than 90 degree steps, but for orthogonal turns keep searchign for lossless jpeg transformations.
The fastest way to rotate a JPEG image would be to write a new / alternate pixel pump for the JPEG decoder that reads and decodes the JPEG pixels left to right (x,y), and writes them to bitmap memory as (y,x) - that is, writing one pixel per scanline at the same offset, instead of the normal mode of writing one pixel per column on the same scanline.
Anything else will be making multiple passes over the bitmap data.
I need to remove the blur this image:
Image source: http://www.flickr.com/photos/63036721#N02/5733034767/
Any Ideas?
Although previous answers are right when they say that you can't recover lost information, you could investigate a little and make a few guesses.
I downloaded your image in what seems to be the original size (75x75) and you can see here a zoomed segment (one little square = one pixel)
It seems a pretty linear grayscale! Let's verify it by plotting the intensities of the central row. In Mathematica:
ListLinePlot[First /# ImageData[i][[38]][[1 ;; 15]]]
So, it is effectively linear, starting at zero and ending at one.
So you may guess it was originally a B&W image, linearly blurred.
The easiest way to deblur that (not always giving good results, but enough in your case) is to binarize the image with a 0.5 threshold. Like this:
And this is a possible way. Just remember we are guessing a lot here!
HTH!
You cannot generally retrieve missing information.
If you know what it is an image of, in this case a Gaussian or Airy profile then it's probably an out of focus image of a point source - you can determine the characteristics of the point.
Another technique is to try and determine the character tics of the blurring - especially if you have many images form the same blurred system. Then iteratively create a possible source image, blur it by that convolution and compare it to the blurred image.
This is the general technique used to make radio astronomy source maps (images) and was used for the flawed Hubble Space Telescope images
When working with images one of the most common things is to use a convolution filter. There is a "sharpen" filter that does what it can to remove blur from an image. An example of a sharpen filter can be found here:
http://www.panoramafactory.com/sharpness/sharpness.html
Some programs like matlab make convolution really easy: conv2(A,B)
And most nice photo editing have the filters under some name or another (sharpen usually).
But keep in mind that filters can only do so much. In theory, the actual information has been lost by the blurring process and it is impossible to perfectly reconstruct the initial image (no matter what TV will lead you to believe).
In this case it seems like you have a very simple image with only black and white. Knowing this about your image you could always use a simple threshold. Set everything above a certain threshold to white, and everything below to black. Once again most photo editing software makes this really easy.
You cannot retrieve missing information, but under certain assumptions you can sharpen.
Try unsharp masking.