My Mac's hard drive failed and I had a replacement drive installed. All R related programs were installed as if my computer was brand new.
Prior to the failure, if I inserted a graphic into a RMardown document, the rendered size of the graphic was consistent and directly related to the actual size of the screen shot image.
Now, relatively small screen captures render large in size. I attempt to add a pic to show the problem. Not certain what I need to do to fix this situation. This is a book that will soon go to publication. As is stands, the publication is delayed unless I am able to somehow return to 'normal.' A Time Machine restore is out of the question for reasons I cannot go into, even though that was attempted. Several Apple senior advisors with whom I spoke do not recommend the 'Time Machine' restore option. As such, I seek another solution - hopefully not individually resizing 1,200+ text images. pic of mis-sizing
I have a single 8-bit channel buffer whose contents I would like to see in the middle of a debugging session. Using whatever might be available under Xcode/LLDB, can this be done? A solution that uses a separate window (or even dumping to an external file) is fine.
What changes about the answer if the image is 8-bit planar RGBA?
I think you are asking about:
https://developer.apple.com/library/ios/documentation/IDEs/Conceptual/CustomClassDisplay_in_QuickLook/Introduction/Introduction.html
This was answered here in:
How can I Quick Look custom objects with Xcode 5 visual debugger?
You have to be able to convert your image to a UIImage or some other type that the QuickLook system natively understands.
I'm programming on Visual Studio c++ using OpenCV library for a project in Windows 7. I'm dealing with a lot of matrices of different types: uchar, float, double, Vec3d, Vec3b etc.
When I want to print out a value of an image, I stop the run, write the following line, cout << (int)mat.at<Veb3b>(i,j)[k];, and run from the beginning which is quite time consuming. In debug mode, I don't see the values of matrices, maybe the first index depending on the type. In Matlab, you can see the values, play with them on run time. (I'm fine with just seeing the values inside a matrix)
I'm wondering if there is a way to see the values on runtime using some external tool maybe. Many genius people have been working on OpenCV, some of them should have thought of it.
So, does anybody know about such a tool? I couldn't find anything related.
I'd recommend the Image Watch extension from Microsoft (link).
It has built-in support for OpenCV datatypes. Better for image data, though using it for regular matrices works well too. Can break at any point and view data in global or local variables and can even do some simple filtering on the data displayed. You can zoom in to view individual elements. Also supports exporting directly from the debugger.
I want to check whether the images is downloaded completely. Is there any library to use?
The images I want to verify including various formats such jpeg, png, bmp etc.
The standard go-to library for that kind of thing in Python is the Python Imaging Library (PIL).
I have used Pyhton Pillow module (PIL) and Imagemagick wrapper wand (for psd, xcf formats) in order to detect broken images, the original answer with code snippets is here.
I also implemented this solution in my Python script here on GitHub.
I also verified that damaged files (jpg) frequently are not 'broken' images i.e, a damaged picture file sometimes remains a legit picture file, the original image is lost or altered but you are still able to load it.
I quote the full answer for completeness:
You can use Python Pillow(PIL) module, with most image formats, to check if a file is a valid and intact image file.
In the case you aim at detecting also broken images, #Nadia Alramli correctly suggests the im.verify() method, but this does not detect all the possible image defects, e.g., im.verify does not detect truncated images (that most viewers often load with a greyed area).
Pillow is able to detect these type of defects too, but you have to apply image manipulation or image decode/recode in or to trigger the check. Finally I suggest to use this code:
try:
im = Image.load(filename)
im.verify() #I perform also verify, don't know if he sees other types o defects
im.close() #reload is necessary in my case
im = Image.load(filename)
im.transpose(PIL.Image.FLIP_LEFT_RIGHT)
im.close()
except:
#manage excetions here
In case of image defects this code will raise an exception.
Please consider that im.verify is about 100 times faster than performing the image manipulation (and I think that flip is one of the cheaper transformations).
With this code you are going to verify a set of images at about 10 MBytes/sec (modern 2.5Ghz x86_64 CPU).
For the other formats psd,xcf,.. you can use Imagemagick wrapper Wand, the code is as follows:
im = wand.image.Image(filename=filename)
temp = im.flip;
im.close()
But, from my experiments Wand does not detect truncated images, I think it loads lacking parts as greyed area without prompting.
I red that Imagemagick has an external command identify that could make the job, but I have not found a way to invoke that function programmatically and I have not tested this route.
I suggest to always perform a preliminary check, check the filesize to not be zero (or very small), is a very cheap idea:
statfile = os.stat(filename)
filesize = statfile.st_size
if filesize == 0:
#manage here the 'faulty image' case
You can guess by attempting to load the image into memory (using PIL or somesuch), but it's possible that some images could be loaded ok without being complete - for example an animated GIF might load fine if you have the header and the first frame of the animation, and you won't notice that later frames of the animation were missing.
A more reliable approach would probably be to use some out-of-band communication, like rather than watching a folder and processing new files as soon as they exist, find some way of hooking into the downloader process and getting it to give you a signal when it decides it is ready.
Last night before going to bed, I browsed through the Scalar Data section of Learning Perl again and came across the following sentence:
the ability to have any character in a string means you can create, scan, and manipulate raw binary data as strings.
An idea immediately hit me that I could actually let Perl scan the pictures that I have stored on my hard disk to check if they contain the string Adobe. It seems by doing so, I can tell which of them have been photoshopped. So I tried to implement the idea and came up with the following code:
#!perl
use autodie;
use strict;
use warnings;
{
local $/="\n\n";
my $dir = 'f:/TestPix/';
my #pix = glob "$dir/*";
foreach my $file (#pix) {
open my $pic,'<', "$file";
while(<$pic>) {
if (/Adobe/) {
print "$file\n";
}
}
}
}
Excitingly, the code seems to be really working and it does the job of filtering out the pictures that have been photoshopped. But problem is many pictures are edited by other utilities. I think I'm kind of stuck there. Do we have some simple but universal method to tell if a digital picture has been edited or not, something like
if (!= /the origianl format/) {...}
Or do we simply have to add more conditions? like
if (/Adobe/|/ACDSee/|/some other picture editors/)
Any ideas on this? Or am I oversimplifying due to my miserably limited programming knowledge?
Thanks, as always, for any guidance.
Your best bet in Perl is probably ExifTool. This gives you access to whatever non-image information is embedded into the image. However, as other people said, it's possible to strip this information out, of course.
I'm not going to say there is absolutely no way to detect alterations in an image, but the problem is extremely difficult.
The only person I know of who claims to have an answer is Dr. Neal Krawetz, who claims that digitally altered parts of an image will have different compression error rates from the original portions. He claims that re-saving a JPEG at different quality levels will highlight these differences.
I have not found this to be the case, in my investigations, but perhaps you might have better results.
No. There is no functional distinction between a perfectly edited image, and one which was the way it is from the start - it's all just a bag of pixels in the end, after all, and any other metadata you can remove or forge all you want.
The name of the graphics program used to edit the image is not part of the image data itself but of something called meta data - which may be stored in the image file but, as others have noted, is neither required (so some programs may not store it, some may allow you an option of not storing it) nor reliable - if you forged an image, you might have forged the meta data as well.
So the answer to your question is "no, there's no way to universally tell if the pic was edited or not, although some image editing software may write its signature into the image file and it'll be left there by carelessness of the editing person.
If you're inclined to learn more about image processing in Perl, you could take a look at some of the excellent modules CPAN has to offer:
Image::Magick - read, manipulate and write of a large number of image file formats
GD - create colour drawings using a large number of graphics primitives, and emit the drawings in various formats.
GD::Graph - create charts
GD::Graph3d - create 3D Graphs with GD and GD::Graph
However, there are other utilities available for identifying various image formats. It's more of a question for Super User, but for various unix distros you can use file to identify many different types of files, and for MacOSX, Graphic Converter has never let me down. (It was even able to open the bizarre multi-file X-ray of my cat's shattered pelvis that I got on a disc from the vet.)
How would you know what the original format was? I'm pretty sure there's no guaranteed way to tell if an image has been modified.
I can just open the file (with my favourite programming language and filesystem API) and just write whatever I want into that file willy-nilly. As long as I don't screw something up with the file format, you'd never know it happened.
Heck, I could print the image out and then scan it back in; how would you tell it from an original?
As other's have stated, there is no way to know if the image was doctored. I'm guessing what you basically want to know is the difference between a realistic photograph and one that has been enhanced or modified.
There's always the option of running some extremely complex image recognition algorithm that would analyze every pixel in your image and do some very complicated stuff to determine if the image was doctored or not. This solution would probably involve AI which would examine millions of photos that are both doctored and those that are not and learn from them. However, this is more of a theoretical solution and isn't very practical... you would probably only see it in movies. It would be extremely complex to develop and probably take years. And even if you did get something like this to work, it probably still wouldn't be 100% correct all the time. I'm guessing AI technology still isn't at that level and could take a while until it is.
A not-commonly-known feature of exiftool allows you to recognize the originating software through an analysis of the JPEG quantization tables (not relying on image metadata). It recognizes tables written by many applications. Note that some cameras may use the same quantization tables as some applications, so this isn't a 100% solution, but it is worth looking into. Here is an example of exiftool run on two images, the first was edited by photoshop.
> exiftool -jpegdigest a.jpg b.jpg
======== a.jpg
JPEG Digest : Adobe Photoshop, Quality 10
======== b.jpg
JPEG Digest : Canon EOS 30D/40D/50D/300D, Normal
2 image files read
This will work even if the metadata has been removed.
There is existing software out there which uses various techniques (compression artifacting, comparison to signature profiles in a database of cameras, etc.) to analyze the actual image data for evidence of alteration. If you have access to such software and the software available to you provides an API for external access to these analysis functions, then there's a decent chance that a Perl module exists which will interface with that API and, if no such module exists, it could probably be created rather quickly.
In theory, it would also be possible to implement the image analysis code directly in native Perl, but I'm not aware of anyone having done so and I expect that you'd be better off writing something that low-level and processor-intensive in a fully-compiled language (e.g., C/C++) rather than in Perl.
http://www.impulseadventure.com/photo/jpeg-snoop.html
is a tool that does the job almost good
If there has been any cloning , there is a variation in the pixel density..or concentration which sometimes shows up.. upon manual inspection
a Photoshop cloned area will have even pixel density(my meaning is variation of Pixels wrt a scanned image)