I have 3 Bitmap point .
Bitmap* totalCanvas = new Bitmap(400, 300, PixelFormat32bppARGB); // final canvas
Bitmap* bottomLayer = new Bitmap(400, 300,PixelFormat32bppARGB); // background
Bitmap* topLayer = new Bitmap(XXX); // always changed.
I will draw complex background on bottomLayer. I don't want to redraw complex background on totalCanvas again and again, so I stored it in bottomLayer.
TopLayer changed frequently.
I want to draw bottomLayer to totalCanvas. Which is the fastest way?
Graphics canvas(totalCanvas);
canvas.DrawImage(bottomLayer, 0, 0); step1
canvas.DrawImage(topLayer ,XXXXX); step2
I want step1 to be as fast as possible. Can anyone give me some sample?
Thanks very much!
Thanks for unwind's answer. I write the following code:
Graphics canvas(totalCanvas);
for (int i = 0; i < 100; ++i)
{
canvas.DrawImage(bottomLayer, 0,0);
}
this part takes 968ms... it is too slow...
Almost all GDI+ operations should be implemented by the driver to run as much as possible on the GPU. This should mean that a simple 2D bitmap copy operation is going to be "fast enough", for even quite large values of "enough".
My recommendation is the obvious one: don't sweat it by spending time hunting for a "fastest" way of doing this. You have formulated the problem very clearly, so just try implementing it that clearly, by doing it as you've outlined in the question. Then you can of course go ahead and benchmark it and decide to continue the hunt.
A simple illustration:
A 32 bpp 400x300 bitmap is about 469 KB in size. According to this handy table, an Nvidia GeForce 4 MX from 2002 has a theoretical memory bandwidth of 2.6 GB/s. Assuming the copy is done in pure "overwrite" mode, i.e. no blending of the existing surface (which sounds right, as your copy is basically a way of "clearing" the frame to the copy's source data), and an overhead factor of four just to be safe, we get:
(2.6 * 2^30 / (4 * 469 * 2^10)) = 1453
This means your copy should run at 1453 FPS, which I happily assume to be "good enough".
If at all possible (and it looks like it from your code), using DrawImageUnscaled will be significgantly faster than DrawImage. Or if you are using the same image over and over again, create a TextureBrush and use that.
The problem with GDI+, is that for the most part, it is unaccelerated. To get the lightening fast drawing speeds you really need GDI and BitBlt, which is a serious pain in the but to use with GDI+, especially if you are in Managed code (hard to tell if you are using managed C++ or straight C++).
See this post for more information about graphics quickly in .net.
Related
I am suddenly in a recursive language class (sml) and recursion is not yet physically sensible for me. I'm thinking about the way a floor of square tiles is sometimes a model or metaphor for integer multiplication, or Cuisenaire Rods are a model or analogue for addition and subtraction. Does anyone have any such models you could share?
Imagine you're a real life magician, and can make a copy of yourself. You create your double a step closer to the goal and give him (or her) the same orders as you were given.
Your double does the same to his copy. He's a magician too, you see.
When the final copy finds itself created at the goal, it has nowhere more to go, so it reports back to its creator. Which does the same.
Eventually, you get your answer back – without having moved an inch – and can now create the final result from it, easily. You get to pretend not knowing about all those doubles doing the actual hard work for you. "Hmm," you're saying to yourself, "what if I were one step closer to the goal and already knew the result? Wouldn't it be easy to find the final answer then ?" (*)
Of course, if you were a double, you'd have to report your findings to your creator.
More here.
(also, I think I saw this "doubles" creation chain event here, though I'm not entirely sure).
(*) and that is the essence of the recursion method of problem solving.
How do I know my procedure is right? If my simple little combination step produces a valid solution, under assumption it produced the correct solution for the smaller case, all I need is to make sure it works for the smallest case – the base case – and then by induction the validity is proven!
Another possibility is divide-and-conquer, where we split our problem in two halves, so will get to the base case much much faster. As long as the combination step is simple (and preserves validity of solution of course), it works. In our magician metaphor, I get to create two copies of myself, and combine their two answers into one when they are finished. Each of them creates two copies of themselves as well, so this creates a branching tree of magicians, instead of a simple line as before.
A good example is the Sierpinski triangle which is a figure that is built from three quarter-sized Sierpinski triangles simply, by stacking them up at their corners.
Each of the three component triangles is built according to the same recipe.
Although it doesn't have the base case, and so the recursion is unbounded (bottomless; infinite), any finite representation of S.T. will presumably draw just a dot in place of the S.T. which is too small (serving as the base case, stopping the recursion).
There's a nice picture of it in the linked Wikipedia article.
Recursively drawing an S.T. without the size limit will never draw anything on screen! For mathematicians recursion may be great, engineers though should be more cautious about it. :)
Switching to corecursion ⁄ iteration (see the linked answer for that), we would first draw the outlines, and the interiors after that; so even without the size limit the picture would appear pretty quickly. The program would then be busy without any noticeable effect, but that's better than the empty screen.
I came across this piece from Edsger W. Dijkstra; he tells how his child grabbed recursions:
A few years later a five-year old son would show me how smoothly the idea of recursion comes to the unspoilt mind. Walking with me in the middle of town he suddenly remarked to me, Daddy, not every boat has a lifeboat, has it? I said How come? Well, the lifeboat could have a smaller lifeboat, but then that would be without one.
I love this question and couldn't resist to add an answer...
Recursion is the russian doll of programming. The first example that come to my mind is closer to an example of mutual recursion :
Mutual recursion everyday example
Mutual recursion is a particular case of recursion (but sometimes it's easier to understand from a particular case than from a generic one) when we have two function A and B defined like A calls B and B calls A. You can experiment this very easily using a webcam (it also works with 2 mirrors):
display the webcam output on your screen with VLC, or any software that can do it.
Point your webcam to the screen.
The screen will progressively display an infinite "vortex" of screen.
What happens ?
The webcam (A) capture the screen (B)
The screen display the image captured by the webcam (the screen itself).
The webcam capture the screen with a screen displayed on it.
The screen display that image (now there are two screens displayed)
And so on.
You finally end up with such an image (yes, my webcam is total crap):
"Simple" recursion is more or less the same except that there is only one actor (function) that calls itself (A calls A)
"Simple" Recursion
That's more or less the same answer as #WillNess but with a little code and some interactivity (using the js snippets of SO)
Let's say you are a very motivated gold-miner looking for gold, with a very tiny mine, so tiny that you can only look for gold vertically. And so you dig, and you check for gold. If you find some, you don't have to dig anymore, just take the gold and go. But if you don't, that means you have to dig deeper. So there are only two things that can stop you:
Finding some gold nugget.
The Earth's boiling kernel of melted iron.
So if you want to write this programmatically -using recursion-, that could be something like this :
// This function only generates a probability of 1/10
function checkForGold() {
let rnd = Math.round(Math.random() * 10);
return rnd === 1;
}
function digUntilYouFind() {
if (checkForGold()) {
return 1; // he found something, no need to dig deeper
}
// gold not found, digging deeper
return digUntilYouFind();
}
let gold = digUntilYouFind();
console.log(`${gold} nugget found`);
Or with a little more interactivity :
// This function only generates a probability of 1/10
function checkForGold() {
console.log("checking...");
let rnd = Math.round(Math.random() * 10);
return rnd === 1;
}
function digUntilYouFind() {
if (checkForGold()) {
console.log("OMG, I found something !")
return 1;
}
try {
console.log("digging...");
return digUntilYouFind();
} finally {
console.log("climbing back...");
}
}
let gold = digUntilYouFind();
console.log(`${gold} nugget found`);
If we don't find some gold, the digUntilYouFind function calls itself. When the miner "climbs back" from his mine it's actually the deepest child call to the function returning the gold nugget through all its parents (the call stack) until the value can be assigned to the gold variable.
Here the probability is high enough to avoid the miner to dig to the earth kernel. The earth kernel is to the miner what the stack size is to a program. When the miner comes to the kernel he dies in terrible pain, when the program exceed the stack size (causes a stack overflow), it crashes.
There are optimization that can be made by the compiler/interpreter to allow infinite level of recursion like tail-call optimization.
Take fractals as being recursive: the same pattern get applied each time, yet each figure differs from another.
As natural phenomena with fractal features, Wikipedia presents:
Moutain ranges
Frost crystals
DNA
and, even, proteins.
This is odd, and not quite a physical example except insofar as dance-movement is physical. It occurred to me the other morning. I call it "Written in Latin, solved in Hebrew." Huh? Surely you are saying "Huh?"
By it I mean that encoding a recursion is usually done left-to-right, in the Latin alphabet style: "Def fac(n) = n*(fac(n-1))." The movement style is "outermost case to base case."
But (please check me on this) at least in this simple case, it seems the easiest way to evaluate it is right-to-left, in the Hebrew alphabet style: Start from the base case and move outward to the outermost case:
(fac(0) = 1)
(fac(1) = 1)*(fac(0) = 1)
(fac(2))*(fac(1) = 1)*(fac(0) = 1)
(fac(n)*(fac(n-1)*...*(fac(2))*(fac(1) = 1)*(fac(0) = 1)
(* Easier order to calculate <<<<<<<<<<< is leftwards,
base outwards to outermost case;
more difficult order to calculate >>>>>> is rightwards,
outermost case to base *)
Then you do not have to suspend items on the left while awaiting the results of calculations further right. "Dance Leftwards" instead of "Dance rightwards"?
I've been working on speeding up some image processing code written in OpenCL, and I've found that for my kernel, buffers (cl_mem) are significantly faster than images (cl_image).
So I want to process my images as cl_mem, but unfortunately I'm stuck with an API that only spits out cl_images. I'm using a OS X API clCreateImageFromIOSurface2DAPPLE that creates an image for me.
Is there any way to take a cl_image and treat it as a cl_mem? When I've tried to do that I get an error when running my kernel.
I've tried copying the image to a buffer using clEnqueueCopyImageToBuffer but that's also too slow. Any ideas? Thanks in advance
PS: I believe my kernel operating on a buffer is much faster because I can do a vload4 and load 4 pixels at a time, vs read_imagei which does just one.
You cannot treat an OpenCL image as memory. The memory layout of an image is private to the implementation and should be considered unknown.
If your code creates the image, however, you could create a buffer and then use cl_khr_image2d_from_buffer. Otherwise write a kernel that copies the data from image to buffer and see if it is faster than clEnqueueCopyImageToBuffer (unlikely).
I have an OpenCL buffer containing an 2D image.
This image have stride bigger than its width.
I need to make OpenCL image from this buffer.
The problem is that function clEnqueueCopyImageToBuffer does not contain stride as an input parameter.
Is it possible to make OpenCL image from OpenCL buffer(with stride bigger than width), with only one copying or faster?
The one way to solve this problem is to write own kernel, but maybe there are much more neat solutions?
Unfortunately, there is no method in the OpenCL specification which allows you to directly create an image from a buffer when the buffer data has a stride not equal to the image width. The most efficient solution would probably be to write your own kernel to do this.
The simplest solution that doesn't involve writing your own kernel would be to copy one line at a time with clEnqueueCopyBufferToImage. If your image is big enough, it might be that the performance of this technique would be reasonably comparable to the hand-written kernel, but you would have to try it out to see.
I didn't include the clEnqueueCopyBufferRect approach in my original answer because my first instinct was that the extra copy would kill performance. However, the comments above got me thinking about it further, and I was interested enough to implement all three approaches to see what the performance was actually like.
As I suspected, the fastest approach was to implement a kernel to do this directly. However, copying the data over line-by-line was significantly slower than I had anticipated. Copying the buffer into an intermediate buffer with clEnqueueCopyBufferRect is actually a pretty good compromise of performance and simplicity, although is still a couple of times slower than the kernel implementation.
The source code for this little experiment can be found here. I was copying a 1020x1020 image with a stride of 1024, and the timings are averaged over 8 runs.
I'm very interested in Kick.js. To convince my professor to use this framework, I want to develop an application which I can load/code custom 3D model using kick.js and should be able to add more objects. I should also able to print FPS to check the variations in FPS as I add more 3D objects on canvas. I'm new to graphic programming, I neither have knowledge on shader programming nor openGL. Being a newbie, how can I start diving into this framework?
The following steps I wanted to implement (Suggest me if I go wrong):
Develop simple demo using kick.js loading single cube or sphere or teapot on canvas.
Able to see the fps as I change the camera angles.
Later I should be able to add more triangles(Models) on the canvas of same type (ex: Teapot) and able to compare the fps with single teapot one.
Am i approaching the right way or please suggestions needed. The provided tutorials neither of them having FPS demo. Please someone HELP ME. I really liked the features stated on homepage but I don't know how can I implement them in my demo.
Assuming that Kick.js has a "render" callback or something similar that's invoked for each frame you want to render (and you know the time between frames, or the absolute time since program start), it's fairly simple to calculate your frame rate.
The method I've used before is: pick a sample rate (I like 250ms so it updates 4 times a second), and count how many frames have executed every 250ms. When you hit 250ms, update the on-screen frame rate counter variable and start counting again.
timeSinceLastFPSUpdate += millisecondsSinceLastFrame;
framesSinceLastFPSUpdate++;
if timeSinceLastFPSUpdate > 250:
timeSinceLastFPSUpdate = 0
fps = framesSinceLastFPSUpdate * (1000 / 250); // convert "frames per 250ms" to "frames per 1s"
framesSinceLastFPSUpdate = 0;
print fps to screen;
You can play around with different sample rates or use a different frame rate calculation method to get the timer to be more "accurate" (to better find frame rate dips) but it sounds like you're looking for something that's less accurate and is just giving you a reasonable idea of the overall complexity of rendering rather than frame to frame dips.
I am building an ASP.NET web site where the users may upload photos of themselves. There could be thousands of photos uploaded every day. One thing my boss has asked a few time is if there is any way we could detect if any of the photos are showing too much 'skin' and automatically move flag these as 'Adults Only' before the editors make the final decision.
Your best bet is to deal with the image in the HSV colour space (see here for rgb - hsv conversion). The colour of skin is pretty much the same between all races, its just the saturation that changes. By dealing with the image in HSV you can simply search for the colour of skin.
You might do this by simply counting the number of pixel within a colour range, or you could perform region growing around pixel to calculate the size of the areas the colour.
Edit: for dealing with grainy images, you might want to perform a median filter on the image first, and then reduce the number of colours to segment the image first, you will have to play around with the settings on a large set of pre-classifed (adult or not) images and see how the values behave to get a satisfactory level of detection.
EDIT: Heres some code that should do a simple count (not tested it, its a quick mashup of some code from here and rgb to hsl here)
Bitmap b = new Bitmap(_image);
BitmapData bData = b.LockBits(new Rectangle(0, 0, _image.Width, _image.Height), ImageLockMode.ReadWrite, b.PixelFormat);
byte bitsPerPixel = GetBitsPerPixel(bData.PixelFormat);
byte* scan0 = (byte*)bData.Scan0.ToPointer();
int count;
for (int i = 0; i < bData.Height; ++i)
{
for (int j = 0; j < bData.Width; ++j)
{
byte* data = scan0 + i * bData.Stride + j * bitsPerPixel / 8;
byte r = data[2];
byte g = data[1];
byte b = data[0];
byte max = (byte)Math.Max(r, Math.Max(g, b));
byte min = (byte)Math.Min(r, Math.Min(g, b));
int h;
if(max == min)
h = 0;
else if(r > g && r > b)
h = (60 * ((g - b) / (max - min))) % 360;
else if (g > r && g > b)
h = 60 * ((b - r)/max - min) + 120;
else if (b > r && b > g)
h = 60 * ((r - g) / max - min) + 240;
if(h > _lowerThresh && h < _upperThresh)
count++;
}
}
b.UnlockBits(bData);
Of course, this will fail for the first user who posts a close-up of someone's face (or hand, or foot, or whatnot). Ultimately, all these forms of automated censorship will fail until there's a real paradigm-shift in the way computers do object recognition.
I'm not saying that you shouldn't attempt it nontheless; but I want to point to these problems. Do not expect a perfect (or even good) solution. It doesn't exist.
I doubt that there exists any off-the-shelf software that can determine if the user uploads a naughty picture. Your best bet is to let users flag images as 'Adults Only' with a button next to the picture. (Clarification: I mean users other than the one who uploaded the picture--similar to how posts can be marked offensive here on StackOverflow.)
Also, consider this review of an attempt to do the same thing in a dedicated product: http://www.dansdata.com/pornsweeper.htm.
Link stolen from today's StackOverflow podcast, of course :).
We can't even write filters that detect dirty words accurately in blog posts, and your boss is asking for a porno detector? CLBUTTIC!
I would say your answer lies in crowdsourcing the task. This almost always works and tends to scale very well.
It doesn't have to involve making some users into "admins" and coming up with different permissions - it can be as simple as to enable an "inappropriate" link near each image and keeping a count.
See the seminal paper "Finding Naked People" by Fleck/Forsyth published in ECCV. (Advanced).
http://www.cs.hmc.edu/~fleck/naked.html
Interesting question from a theoretical / algorithmic standppoint. One approach to the problem would be to flag images that contain large skin-colored regions (as explained by Trull).
However, the amount of skin shown is not a determinant of an offesive image, it's rather the location of the skin shown. Perhaps you can use face detection (search for algorithms) to refine the results -- determine how large the skin regions are relative to the face, and if they belong to the face (perhaps how far below it they are).
I know either Flickr or Picasa has implemented this. I believe the routine was called FleshFinder.
A tip on the architecture of doing this:
Run this as a windows service separate from the ASP.NET Pipeline, instead of analyzing images in real time, create a queue of new images that are uploaded for the service to work through.
You can use the normal System.Drawing stuff if you want, but if you really need to process a lot of images, it would be better to use native code and a high performance graphics library and P/invoke the routine from your service.
As resources are available, process images in the background and flag ones that are suspicious for editors review, this should prune down the number of images to review significantly, while not annoying people who upload pictures of skin colored houses.
I would approach the problem from a statistical standpoint. Get a bunch of pictures that you consider safe, and a bunch that you don't (that will make for a fun day of research), and see what they have in common. Analyze them all for color range and saturation to see if you can pick out characteristics that all of the naughty photos, and few of the safe ones have.
Perhaps the Porn Breath Test would be helpful - as reported on Slashdot.
Rigan Ap-apid presented a paper at WorldComp '08 on just this problem space. The paper is allegedly here, but the server was timing out for me. I attended the presentation of the paper and he covered comparable systems and their effectiveness as well as his own approach. You might contact him directly.
I'm afraid I can't help point you in the right direction, but I do remember reading about this being done before. It was in the context of people complaining about baby pictures being caught and flagged mistakenly. If nothing else, I can give you the hope that you don't have to invent the wheel all by yourself... Someone else has been down this road!
CrowdSifter by Dolores Labs might do the trick for you. I read their blog all the time as they seem to love statistics and crowdsourcing and like to talk about it. They use amazon's mechanical turk for a lot of their processing and know how to process the results to get the right answers out of things. Check out their blog at the very least to see some cool statistical experiments.
As mentioned above by Bill (and Craig's google quote) statistical methods can be highly effective.
Two approaches you might want to look into are:
Neural Networks
Multi Variate Analysis (MVA)
The MVA approach would be to get a "representative sample" of acceptable pictures and of unacceptable pictures. The X data would be an array of bytes from each picture, the Y would be assigned by you as a 1 for unacceptable and a 0 for acceptable. Create a PLS model using this data. Run new data against the model and see how well it predicts the Y.
Rather than this binary approach you could have multiple Y's (e.g. 0=acceptable, 1=swimsuit/underwear, 2=pornographic)
To build the model you can look at open source software or there are a number of commercial packages available (although they are typically not cheap)
Because even the best statistical approaches are not perfect the idea of also including user feedback would probably be a good idea.
Good luck (and worst case you get to spend time collecting naughty pictures as an approved and paid activity!)