I am very new to the HM HEVC (and the JEM) reference software, and I am currently trying to understand the source code. I want to add some lines to display for each component: name of Algo (i.e. inter/intra Algos) + length of the bitstream+ position in output bin file.
To know which component cost more bits to code and how codec is working. I want to do same thing for the JEM also after that.
my problem first is that I am unable of understanding a lot of function there, the comment is not sufficient, so is there any references to understand the code??!! (I already read the Manuel ,doesn’t help).
2nd I don’t know where & how exactly to add these lines; is it in TEncGOP, TEncSlice or TEncCU. Ps: I don’t think in TEncGOP.compressGOP so maybe in the 2 other classes.
(I put the answer to comment that #Mourad put four hours ago here, becuase it will be long)
I assume that you could manage to find where the actual encoding after the RDO loop is implemented. As you correctly mentioned, xEncodeCU is the function you need to refer to make sure you are not still in the RDO.
Now you need to find the exact function in xEncodeCU that is responsible for your target codec tool.
For instance, if you want to count the number of bits for coefficient coding, you should be looking into the m_pcEntropyCoder->encodeCoeff() (It's a JEM function and may have different name in the HM). Once you find this line in the xEncodeCU, you may do this and get the number of bits written inside encodeCoeff() function:
UInt b_before = m_pcEntropyCoder->getNumberOfWrittenBits();
m_pcEntropyCoder->encodeCoeff( ... );
UInt b_after = m_pcEntropyCoder->getNumberOfWrittenBits();
UInt writtenBitsCoeff = b_after - b_before;
One important point: as you cas see, the function getNumberOfWrittenBits() gives you integer rates, which is obtained by rounding sum of fractional rates corresponding to all syntax elements coded inside the function encodeCoeff. This error might or might not be acceptable, depending on your problem. For example, if instead of coefficient coding rate, you wanted to know the rate of CBF, then this error would not be acceptable at all. Because, CBF rate is mostly less than one bit. If this is your case, then you would need to calculate the fractional bits one-by-one. It would be totally different and relatively more complicated than this.
Point 1: There is one rule of tumb that logging coding decisions (e.g. pred mode, MV, IPM, block size) is much easier at the decoder side than encoder. This is because of the fact that you have super complicated RDO process at the encoder side that can easily make you get lost in the loops. But at the decoder side, everything appears only once. However, if you insist on doing it at the encoder side, you may find some tips here: Get some information from HEVC reference software
Point 2: Unlike coding decisions, logging rate (i.e. number of written bits for different syntax elements) is more complicated at the decoder side than encoder. This is particularly true for fractional bits associated to anything that is encoded in non-EP mode (i.e. with CABAC contexts). So you may do this part at the ecoder side. But I am afraid it is not easy.
Point 3: I think the best way to understand the code is to read it line-by-line. It's very time-consuming but if you theoritically know the standard(s), you will probably be able to distiguish important parts and ignore the rest.
PS: I think there are too many questions, mostly too general, in your post. It makes it a bit difficult for me to answer them all together. So you I'll wait for you to take your next step and ask more precise questions.
I have an assigment to do a tron game with AI. Me an my team almost made it but we're trying to find a good heuristic. We taught about Voronoi, but it's kinda slow :
for yloop = 0 to height-1
for xloop = 0 to width-1
// Generate maximal value
closest_distance = width * height
for point = 0 to number_of_points-1
// calls function to calc distance
point_distance = distance(point, xloop, yloop)
if point_distance < closest_distance
closest_point = point
end if
next
// place result in array of point types
points[xloop, yloop] = point
next
next
We have 5 seconds to make a move and this algorithm doesn`t sound too good ! I don't need code ... we just need an ideea !
Thank you !
Later edit : Should we try Delaunay Triangulations ?
Have a look at the postmortem of Google's AI Challenge about this.
well i am considering redesigning my old Wurmeler game (AI including) so i stumped on your question while searching for new ideas so here is my insight from my old AI
Wurmeler is similar to tron but much slover and worms turn smoothly
game space is 2D bitmap
each AI is very simple ... stupid,...
but navigate better than me
unless they are closed by other player
or crush into local min/max
but still they are fun
OK now the AI algorithm in every decision move:
create few rays from Worm
one in movement direction
few turned to the left by some angle (5 degree step is fine)
few turned to the right
evaluate the ray length
from worm until it hit border
or another worm path curve
use the max rule to change heading
This old AI maintain only navigation but I want to implement more (this is not yet done):
divide map to square sections
each section will have the average density of already filled space
so if possible AI will choose less filled area
add strategies
navigate (already done)
flee (go away from near player if too close and behind)
attack (if on relative parallel course and too close and in the front)
may be conversion from raster to vector
should speed up the ray traceing and colision detection
but with growing length may be slower ... have to try it and see
possible use of field algorithms
I want to arrange an AI contest between some friends.
Lets say tic tac toe,
each player program a method which get the board and a symbol(X\O) and return the place which he want to play at his turn.
Now my problem its how to "connect" two AI's in another program so I can test all users and see who has the best code.
The only way I think of is to communicate with a text file - all the AI's have thread running on background and check changes on the text file,the engine summary the game details(which turn,the board,score,players) to the text file.
How can this can be done better?
And one more little thing, this is common to have a time frame for each turn in AI contests?
(Because the AI program will run in different times on different computers)
It isn't clear from your question whether this has to be performed online or not.
If you're after finding "the best Tic Tac Toe algorithm", you could simply:
(This may slightly differ, depending on the programming language)
Define an interface (e.g: ITicTacToeSolver)
Have all your friends implement it in their own way and send you a DLL with their solution.
Create the game which will dynamically load these DLLs, and test them (play 1,000,000 games with the algorithm that is loaded).
Keep track of game statistics to see which algorithm is best.
If the AI programs are competing in a game like tic tac toe, typically every program would have limited total "thinking" time (e.g. 5 minutes), and a program that exceeds its time allotment would lose.
Typically often the programs are connected over some sort of a simple protocol, not through text files. The protocol can run on standard I/O or through TCP/IP sockets.
To normalize CPU usage, you can request that for tournament games, all the programs are compiled to work on a reference platform and then you provide two identical PCs, both running one of the active contestants. It then becomes a requirement of your tournament that the programs can be executed on this reference platform.
Use an interface and a standard programming language - so you can forget about text files and bollocks like that.
Figure out a simple SOAP protocol. You can simply create a WSDL interface - easy to create using windows communication foundatoin (WCF) or JMS.
Easiest would be to have a centralized server to serve as a referee and keep track of time. Each player could be assigned an ID.
Then you could have a the following interface (use WCF or JMS to create a WSDL SOAP protocol)
function int requestGame(int opponentID, int color)
- if called with color = -1, randomly assigns a color and returns it (0=white, 1=black).
- otherwise you can request a color, and returns it if accepted, -1 if not accepted.
- could use -1 to request random opponent.
function int getRemainingTime(int color)
- returns the time remaining on clock for color
function bool play(int color, int i, int j)
where color = 0 - white - 1 black,
i, j are board coordinates,
- returns true if it is a legal move
function bool won(int color)
- returns true if color has won the game.
Not having a centralized server would be more complex since they would have to negotiate over agreed wins, time, etc.
I would suggest to have each of the AI be executable files, communicating by using standard input and output. The game engine (the referee) would send the complete state of the world to AI_one as input, then wait for a move from standard output. It would then perform the move (if legal) and repeat the process for AI_two, then alternate between the two until the game is over. As a failsafe the referee can make one side lose if it takes too long to make a move.
This method is used by Google AI challenge.
One very big advantage to this approach is that people can write their AI in different languages, as long as they follow the agreed standard for how to make a move.
If your goal is to have an AI programming competition amongst friends, I'd suggest that you don't waste time designing and implementing the framework for holding the competition. Use something that already exists for that purpose. You can skip all the pain and heartache of fixing bugs in your framework and get right to the fun part: developing AI.
A good framework is the Robocode game. Watching your robots kill each other will be a lot more fun than watching them play tic-tac-toe.
You should take a look at this question:
What is the best Battleship AI?
In it he creates a battleship AI contest / challenge. It was very high rated and a lot of fun to code for and watch.
He used the Tournament API http://tournaments.codeplex.com/ to run the competition.
Also, it's important to allow the submissions to compete multiple times.. ie 1000 times each. This removes alot of the randomness and luck from the competitors.
I found a lot of references to the AI of the ghosts in Pacman, but none of them mentioned how the eyes find their way back to the central ghost hole after a ghost is eaten by Pacman.
In my implementation I implemented a simple but awful solution. I just hard coded on every corner which direction should be taken.
Are there any better/or the best solution? Maybe a generic one that works with different level designs?
Actually, I'd say your approach is a pretty awesome solution, with almost zero-run time cost compared to any sort of pathfinding.
If you need it to generalise to arbitrary maps, you could use any pathfinding algorithm - breadth-first search is simple to implement, for example - and use that to calculate which directions to encode at each of the corners, before the game is run.
EDIT (11th August 2010): I was just referred to a very detailed page on the Pacman system: The Pac-Man Dossier, and since I have the accepted answer here, I felt I should update it. The article doesn't seem to cover the act of returning to the monster house explicitly but it states that the direct pathfinding in Pac-Man is a case of the following:
continue moving towards the next intersection (although this is essentially a special case of 'when given a choice, choose the direction that doesn't involve reversing your direction, as seen in the next step);
at the intersection, look at the adjacent exit squares, except the one you just came from;
picking one which is nearest the goal. If more than one is equally near the goal, pick the first valid direction in this order: up, left, down, right.
I've solved this problem for generic levels that way: Before the level starts, I do some kind of "flood fill" from the monster hole; every tile of the maze that isn't a wall gets a number that says how far it is away from the hole. So when the eyes are on a tile with a distance of 68, they look which of the neighbouring tiles has a distance of 67; that's the way to go then.
For an alternative to more traditional pathfinding algorithms, you could take a look at the (appropriately-named!) Pac-Man Scent Antiobject pattern.
You could diffuse monster-hole-scent around the maze at startup and have the eyes follow it home.
Once the smell is set up, runtime cost is very low.
Edit: sadly the wikipedia article has been deleted, so WayBack Machine to the rescue...
You should take a look a pathfindings algorithm, like Dijsktra's Algorithm or A* algorithm. This is what your problem is : a graph/path problem.
Any simple solution that works is maintainable, reliable and performs well enough is a good solution. It sounds to me like you have already found a good solution ...
An path-finding solution is likely to be more complicated than your current solution, and hence more likely to require debugging. It will probably also be slower.
IMO, if it ain't broken, don't fix it.
EDIT
IMO, if the maze is fixed then your current solution is good / elegant code. Don't make the mistake of equating "good" or "elegant" with "clever". Simple code can also be "good" and "elegant".
If you have configurable maze levels, then maybe you should just do the pathfinding when you initially configure the mazes. Simplest would be to get the maze designer to do it by hand. I'd only bother automating this if you have a bazillion mazes ... or users can design them.
(Aside: if the routes are configured by hand, the maze designer could make a level more interesting by using suboptimal routes ... )
In the original Pacman the Ghost found the yellow pill eater by his "smell" he would leave a trace on the map, the ghost would wander around randomly until they found the smell, then they would simply follow the smell path which lead them directly to the player. Each time Pacman moved, the "smell values" would get decreased by 1.
Now, a simple way to reverse the whole process would be to have a "pyramid of ghost smell", which has its highest point at the center of the map, then the ghost just move in the direction of this smell.
Assuming you already have the logic required for chasing pacman why not reuse that? Just change the target. Seems like it would be a lot less work than trying to create a whole new routine using the exact same logic.
It's a pathfinding problem. For a popular algorithm, see http://wiki.gamedev.net/index.php/A*.
How about each square having a value of distance to the center? This way for each given square you can get values of immediate neighbor squares in all possible directions. You pick the square with the lowest value and move to that square.
Values would be pre-calculated using any available algorithm.
This was the best source that I could find on how it actually worked.
http://gameai.com/wiki/index.php?title=Pac-Man#Respawn
When the ghosts are killed, their disembodied eyes return to their starting location. This is simply accomplished by setting the ghost's target tile to that location. The navigation uses the same rules.
It actually makes sense. Maybe not the most efficient in the world but a pretty nice way to not have to worry about another state or anything along those lines you are just changing the target.
Side note: I did not realize how awesome those pac-man programmers were they basically made an entire message system in a very small space with very limited memory ... that is amazing.
I think your solution is right for the problem, simpler than that, is to make a new version more "realistic" where ghost eyes can go through walls =)
Here's an analog and pseudocode to ammoQ's flood fill idea.
queue q
enqueue q, ghost_origin
set visited
while q has squares
p <= dequeue q
for each square s adjacent to p
if ( s not in visited ) then
add s to visited
s.returndirection <= direction from s to p
enqueue q, s
end if
next
next
The idea is that it's a breadth-first search, so each time you encounter a new adjacent square s, the best path is through p. It's O(N) I do believe.
I don't know much on how you implemented your game but, you could do the following:
Determine the eyes location relative position to the gate. i.e. Is it left above? Right below?
Then move the eyes opposite one of the two directions (such as make it move left if it is right of the gate, and below the gate) and check if there are and walls preventing you from doing so.
If there are walls preventing you from doing so then make it move opposite the other direction (for example, if the coordinates of the eyes relative to the pin is right north and it was currently moving left but there is a wall in the way make it move south.
Remember to keep checking each time to move to keep checking where the eyes are in relative to the gate and check to see when there is no latitudinal coordinate. i.e. it is only above the gate.
In the case it is only above the gate move down if there is a wall, move either left or right and keep doing this number 1 - 4 until the eyes are in the den.
I've never seen a dead end in Pacman this code will not account for dead ends.
Also, I have included a solution to when the eyes would "wobble" between a wall that spans across the origin in my pseudocode.
Some pseudocode:
x = getRelativeOppositeLatitudinalCoord()
y
origX = x
while(eyesNotInPen())
x = getRelativeOppositeLatitudinalCoordofGate()
y = getRelativeOppositeLongitudinalCoordofGate()
if (getRelativeOppositeLatitudinalCoordofGate() == 0 && move(y) == false/*assume zero is neither left or right of the the gate and false means wall is in the way */)
while (move(y) == false)
move(origX)
x = getRelativeOppositeLatitudinalCoordofGate()
else if (move(x) == false) {
move(y)
endWhile
dtb23's suggestion of just picking a random direction at each corner, and eventually you'll find the monster-hole sounds horribly ineficient.
However you could make use of its inefficient return-to-home algorithm to make the game more fun by introducing more variation in the game difficulty. You'd do this by applying one of the above approaches such as your waypoints or the flood fill, but doing so non-deterministically. So at every corner, you could generate a random number to decide whether to take the optimal way, or a random direction.
As the player progresses levels, you reduce the likelihood that a random direction is taken. This would add another lever on the overall difficulty level in addition to the level speed, ghost speed, pill-eating pause (etc). You've got more time to relax while the ghosts are just harmless eyes, but that time becomes shorter and shorter as you progress.
Short answer, not very well. :) If you alter the Pac-man maze the eyes won't necessarily come back. Some of the hacks floating around have that problem. So it's dependent on having a cooperative maze.
I would propose that the ghost stores the path he has taken from the hole to the Pacman. So as soon as the ghost dies, he can follow this stored path in the reverse direction.
Knowing that pacman paths are non-random (ie, each specific level 0-255, inky, blinky, pinky, and clyde will work the exact same path for that level).
I would take this and then guess there are a few master paths that wraps around the entire
maze as a "return path" that an eyeball object takes pending where it is when pac man ate the ghost.
The ghosts in pacman follow more or less predictable patterns in terms of trying to match on X or Y first until the goal was met. I always assumed that this was exactly the same for eyes finding their way back.
Before the game begins save the nodes (intersections) in the map
When the monster dies take the point (coordinates) and find the
nearest node in your node list
Calculate all the paths beginning from that node to the hole
Take the shortest path by length
Add the length of the space between the point and the nearest node
Draw and move on the path
Enjoy!
My approach is a little memory intensive (from the perspective of Pacman era), but you only need to compute once and it works for any level design (including jumps).
Label Nodes Once
When you first load a level, label all the monster lair nodes 0 (representing the distance from the lair). Proceed outward labelling connected nodes 1, nodes connected to them 2, and so on, until all nodes are labelled. (note: this even works if the lair has multiple entrances)
I'm assuming you already have objects representing each node and connections to their neighbours. Pseudo code might look something like this:
public void fillMap(List<Node> nodes) { // call passing lairNodes
int i = 0;
while(nodes.count > 0) {
// Label with distance from lair
nodes.labelAll(i++);
// Find connected unlabelled nodes
nodes = nodes
.flatMap(n -> n.neighbours)
.filter(!n.isDistanceAssigned());
}
}
Eyes Move to Neighbour with Lowest Distance Label
Once all the nodes are labelled, routing the eyes is trivial... just pick the neighbouring node with the lowest distance label (note: if multiple nodes have equal distance, it doesn't matter which is picked). Pseudo code:
public Node moveEyes(final Node current) {
return current.neighbours.min((n1, n2) -> n1.distance - n2.distance);
}
Fully Labelled Example
For my PacMan game I made a somewhat "shortest multiple path home" algorithm which works for what ever labyrinth I provide it with (within my set of rules). It also works across them tunnels.
When the level is loaded, all the path home data in every crossroad is empty (default) and once the ghosts start to explore the labyrinth, them crossroad path home information keeps getting updated every time they run into a "new" crossroad or from a different path stumble again upon their known crossroad.
The original pac-man didn't use path-finding or fancy AI. It just made gamers believe there is more depth to it than it actually was, but in fact it was random. As stated in Artificial Intelligence for Games/Ian Millington, John Funge.
Not sure if it's true or not, but it makes a lot of sense to me. Honestly, I don't see these behaviors that people are talking about. Red/Blinky for ex is not following the player at all times, as they say. Nobody seems to be consistently following the player, on purpose. The chance that they will follow you looks random to me. And it's just very tempting to see behavior in randomness, especially when the chances of getting chased are very high, with 4 enemies and very limited turning options, in a small space. At least in its initial implementation, the game was extremely simple. Check out the book, it's in one of the first chapters.