So upon seeing images from Godus I was wondering how to generate a simple, non-interactive, 2D image with different colors for different heights or layers of heights like on the picture below.
I was just thinking in terms of generating the basic layers of colors for the topography without the houses, trees objects and units. I wasn't thinking in terms of creating a graphics engine that would solve this, but a simple way to generate a flat image on the screen.
The question is two-fold:
1, What kind of data could be used for this sort of generation? I was thinking maybe ASCII art which is kind of easy to create and modify to quickly change the topography, but would be difficult to provide height information.
2, What existing frameworks, classes, methods or methodologies could be used for solving the generation after having the data ready.
Godus:
ASCII art (northern europe with ! for Norway, # for Sweden, $ for Finland and % for Russia:
(Taken from the MapBox docs: http://mapbox.com/developers/utfgrid/#map_data_as_ascii_art)
If you want to create a simple 2D, contoured image, I would try the following:
Create some height data. I'd just use a grey-scale image for that, rather than ascii. You can author basic height-maps in MS Paint, or anything similar.
Smooth the data. For example, apply a blur, or increase the resolution using a smooth filter.
Consider clamping all height data below a certain point - this represents a water level, if you want that.
Quantise the data. The more you quantise, the fewer but more obvious the contours.
Apply a false colouring, via a palette lookup. For example a : low lying areas blue, for water, then yellow, for sand, green for grass, brown for earth, grey for rock, and white for snow.
The important parts are the enlarging/smoothing filter, which creates more interesting shapes to your contours, and the quantisation which actually creates the contours themselves.
You can play with the stages of this. For example you could introduce some noise to the terrain, to make it look more natural if your source data is very clean. Or you could increase the smoothing if you want everything very rounded.
If you want to use ascii, you could just generate a bitmap directly from that, which wouldn't be tricky. The ascii you use as an example though is split up by country rather than terrain, so the false-colouring and contouring would probably do the wrong thing. You could probably use it as input to a simple terrain generator, perhaps just having a couple of chars to denote where you want land, sea, mountains, etc.
Here's a very basic example I knocked up, it's just an application of the technique I suggested. I didn't use any frameworks or libs, just a few simple image processing functions, and an height-map of Europe I found:
Related
I mean, the basics..
1) I have seen in the Online videos, that they are modelling a character (or anything) through one object only, they are extruding, loop cut, scaling, etc and model a character, why don't they design different objects separately (like hands separately, legs separately, body separate and then join them together and make one object)..??????
2) Like What the texturing department has to see so that they should not return the model back to the modelling department. I mean like the meshes(polygons) over the model face must be quad, etc not triangle. while modelling a character..
what type of basics i should know , means is there any check list or is there any basics which i should see before modelling a character..
Please correct me if i am wrong , and answer my both questions.. Thanks
It may be common but it definitely isn't mandatory to have a model as one solid mesh. Some models will have parts of the body underneath clothing removed to reduce the poly count. How the model is to be used will be a big factor to how you model it, that is a for a single image it is easy to get away with multiple parts, while a character that will be animated in a cartoony animation could be stretched and distorted in ways that could show holes in a model with multiple pieces. When working in a team, there may be rules in place determining whether a solid or multi-part model is considered acceptable.
An example of an animated model made from multiple parts is Sintel, the main character in the Sintel short animation.
There is nothing stopping you from making a library of separate body parts and joining them together when you make your model. Be aware that this can bring complications, if you model an arm with 12 verts and then you make your hand with 15, then you have to fiddle around to merge them together.
You will also find some extra freedom to work with multiple body parts during the sculpting phase as you are creating a high density mesh that is used as a template to model a clean mesh over. This step is called retopology.
It is more likely that the rigging department will send a model back for fixing than the texturing department. When adding a rig and deforming the mesh in different ways, any parts that deform badly will be revealed and need fixing.
[...] (like hands separately, legs separately, body separate and then
join them together and make one object) [...]
Some modelers I know do precisely this and they do it in a way where they block in the design using broad primitive shapes, start slicing some edge loops and add broad details, then merge everything together, then sculpt it a bit further with high-res sculpting tools, and finally retopologize everything.
The main modelers I know who do this, however, model in a way that tries to adhere as close as possible to the concept artist's illustration. They're not creating their own models from scratch but are instead given top/front/back/side illustrations of a character, for example, and are just trying to match it as closely as possible.
When you start modeling everything in small pieces, it helps to have that concept illustration since you can get lost in the topology otherwise and fusing organic meshes together can be difficult to do in a clean way.
[...] why don't they design different objects separately? [...]
Again they sometimes do, but one of the appeals of creating organic meshes by keeping it seamless the entire time is that you can start to focus on how edge loops propagate across the entire model. It helps to know that the base of a finger is a hexagon, for example, in figuring out how to cleanly propagate and terminate the edge loops for a hand, and likewise have a strategy for the hand to cleanly propagate and terminate edge loops as it joins into the forearm.
It can be hard to get the topology to match up cleanly if you designed everything in small pieces and then had to figure out how to merge it all together. Polygonal modeling is very topology-oriented. It tends to require as much thinking about the wireframe and edge flows as it does the shape of the model, since it needs to be a certain way for everything to subdivide cleanly and smoothly and animate predictably with subdivision surfaces.
I used to work with developers who took one glance at the topology-dominated workflow of polygonal modeling and immediately wanted to jump to seeking alternatives, like voxel sculpting. With voxels you could be able to potentially model everything in pieces and foose it all together in a nice and smooth organic way without thinking about topology whatsoever.
However, that loses sight of the key appeal of polygonal meshes. Their wire flow forms a control lattice with a very finite number of control points for the artist to animate and move around to predictably control the shape of their model. You immediately lose that with a voxel representation -- so while voxels free the artist of thinking about how the topology works and how the wireframe flows through the model, it also loses all those control benefits of having that. So often if people use voxel sculpting, they end up meticulously retopologizing everything at the end anyway to gain back that level of coarse and predictable control they have with polygonal meshes.
I mean like the
meshes(polygons) over the model face must be quad, etc not triangle.
while modelling a character..
This is all in the context of subdivision surfaces: the most popular of which are variants of catmull-clark. That favors quads to get the most predictable subdivision. It's much easier for the artist to predict how everything will look like and deform if they favor, as much as possible, uniform grids of quadrangles wrapped around their model with 4-valence vertices and every polygon having 4 points. Then only in the case where they kind of need to "join" these quad grids together, they might create some funky topology: a 5-valence vertex here, a 3-valence vertex there, a 5-sided polygon here, a triangle there -- but those cases tend to deform a bit unpredictably (at least unintuitively), so artists tend to try to avoid these as much as possible.
Because when artists model polygonal meshes in this way, they are not just trying to create a statue with a nice shape. If that's all they wanted to do, they'd save themselves a lot of grief avoiding dealing with things in terms of individual vertices/edges/polygons in the first place and using something like Sculptris. Instead they are designing not only shapes but also designing a control lattice, a wire flow and a set of control points they can easily move around in the future to get predictable behavior out of their control cage. They're basically designing controls or an "interactive GUI/rig" almost for themselves with how they design the topology.
2) Like What the texturing department has to see so that they should
not return the model back to the modelling department.
Generally how a mesh is modeled in a direct sense shouldn't affect the texture department's work much at all if they're working with UV maps and painting textures over them (at that point it doesn't really matter if a model has clean wire flows or not, since all the texture artists do is pain images over the 2D UV map or directly onto the 3D model).
However, if the modeler does the UV mapping, then regardless of whether he uses quad meshes and clean wire flows or not, if the UV mapping is poor, then the resulting texture images will look all distorted. So the UV maps need to be made well with minimal distortion, though that's usually easy to do automatically these days.
The other exception is if the department doesn't use UV maps and instead uses, say, PTex from Disney. PTex really favors quads. In the original paper at least, it only worked with quads.
I am trying to create an algorithm that can take a set of objects and organize them in a given area such that a box bounding all of the shapes is optimized (either by area used, or by maximizing the span along one of the dimensions, etc.). All of the shapes are closed and bounded.
The purpose of this is to try and minimize material waste from using a laser cutter. The shapes are generated in CAD and can read into this algorithm. The algorithm will then take arguments for the working area (effective laser cutting area) as well as the minimum separation between any two objects, then attempt to organize the objects within the specified dimensions while trying to minimize the area usage. Alternatively, the algorithm can also try to maximize the object locations along one axis while minimizing the span along the other dimension. This would be akin to cutting off a smaller workpiece to cut from.
Ideally, the algorithm would be able to make translations AND rotations, but rotations aren't necessary.
For example, this Picture depicts the required transformation.
It should work with an arbitrary, but small (<25) number of objects.
Lastly, I don't expect anyone to solve this for me, but I would appreciate help toward either finding an algorithm that can do this, or developing my own. Thank you.
I dont know to what extent you want to create said algorithm or how you want to implement it, But i know of a program called OptiNest that can do what you ask. It organizes geometric shapes to optimize the layout and minimize waste on a plane, i think in an autocad format.
I have SVG abirtrary paths which i need to pack as efficiently as possible within a given rectangle(as less waste of space as possible). After some research i found the bin packing algorithms which seems to be dealing with boxes and not curved random shapes(my SVG shapes are quite complex and include beziers etc.).
AFAIK, there is no deterministic algorithm for actually packing abstract shapes.
I wish to be proven wrong here which would be ideal(having a mathematical deterministic method for packing them). In case I am right however and there is not, what would be the best approach to this problem
The subject name is Shape Nesting, Nesting Problem or Nesting Process.
In Shape Nesting there is no single/uniform algorithm or mathematical method for nesting shapes and getting the least space waste possible.
The 1st method is the packing algorithm(creates an imaginary bounding
box for each shape and uses a rectangular 2D algorithm to pack the
bounding boxes).
This method is fast but the least efficient in regards to space
waste.
The 2nd method is some kind of incremental rotation. The algorithm
rotates the shape at incremental steps and checks if it fits in the
space. This is better than the packing method in regards to space
waste but it is painstakingly slow,
What are some other classroom examples for achieving a solution to this problem?
[Edit1] new answer
as mentioned before bin-packing is NP complete (hard) so forget about algebraic solution
known approaches are:
generate and test
either you test all possibility of the problem and remember the best solution or incrementally add items (not all at once) one by one with the same way. It is basically what you are doing now without proper heuristic is unusably slow. But has the best space efficiency (the first one is much better but much slower) O(N!)
take advantage of sorting items by size
something like this it is much faster almost O(N.log(N)) (according to used sorting algorithm). Space efficiency strongly depends on the items size range and count. For rectangular shapes is this the best approach (fastest and usable even for N>1000). For complex shapes is this not a good way but look at it anyway maybe you get some idea ...
use of Neural network
This is extremly vague approach without any warrant of solution but possible best space efficiency/runtime ratio
I think there could be some field approach out there
I sow a few for generating graph layouts. All items create fields (booth attractive and repulsive) so they are moving to semi-stable state.
At first all items are at random locations
When the movement stop remember best solution and shake all items a little or randomize their position again.
Cycle this few times
This approach is much faster then genere and test and can provide very close solution to it but it can hang in local min/max or oscillate if the fields are not optimally choosed. For example all items can have constant attractive force to each other and repulsive force getting stronger only when the items are very close. You have to prevent overlapping of items (either by stronger repulsion or by collision tests). You have also to create some rotation moment for example with that repulsive force. It differs on any vertex so it creates a rotation moment (that can automatically align similar sides closer together). Also you can have semi-stable state with big distances between items and after finding best solution just turn off repulsion fields so they stick together. Sometimes it can have better results some times not ... here is nice example for graph layout computation
Logic to strategically place items in a container with minimum overlapping connections
Demo from the same QA
And here solver for placing sliders in 2D:
How to implement a constraint solver for 2-D geometry?
[Edit0] old answer before reformulating the question
I am not clear what you want to achieve.
have SVG picture and want to separate its parts to rectangular regions
as filled as can be
least empty space in them
no shape change in picture
have svg picture and want to change its shapes according to some purpose
if this is the case some additional info is needed
[solution for 1]
create a list of points for whole SVG in global SVG space (all points are transformed)
for line you need add 2 points
for rectangles 4 points
circle/elipse/bezier/eliptic arc 8 points
find local centres of mass
use classical approach
or can speed things up by computing the average density of points per x,y axis separately and after that just check all combinations of found positions of local max of densities if they really are sub cluster center or not.
all sub cluster center is the center of your region
now find the most far points which are still part of your cluster (the are close enough to neighbour points)
create rectangular area that cover all points from sub cluster.
you also can remove all used points from list
repeat fro all valid sub clusters
until all points are used
another not precise but simpler approach is:
find SVG size
create planar map of svg with some precision for example int map[256][256].
size of map can be constant or with the same aspect as SVG
clear map with 0
for any point of SVG set related map point to 1 (or inc or whatever)
now just segmentate map and you will have find your objects
after segmentation you have position and size of all objects
so finding of bounding boxes should be easy
You can start with a variant of the rectangle bin-packing algorithm and add rotation. There is a method "Guillotine bin packer" and you can download a paper and a library at github.
Currently I'm working on a little project just for a bit of fun. It is a C++, WinAPI application using OpenGL.
I hope it will turn into a RTS Game played on a hexagon grid and when I get the basic game engine done, I have plans to expand it further.
At the moment my application consists of a VBO that holds vertex and heightmap information. The heightmap is generated using a midpoint displacement algorithm (diamond-square).
In order to implement a hexagon grid I went with the idea explained here. It shifts down odd rows of a normal grid to allow relatively easy rendering of hexagons without too many further complications (I hope).
After a few days it is beginning to come together and I've added mouse picking, which is implemented by rendering each hex in the grid in a unique colour, and then sampling a given mouse position within this FBO to identify the ID of the selected cell (visible in the top right of the screenshot below).
In the next stage of my project I would like to look at generating more 'playable' terrains. To me this means that the shape of each hexagon should be more regular than those seen in the image above.
So finally coming to my point, is there:
A way of smoothing or adjusting the vertices in my current method
that would bring all point of a hexagon onto one plane (coplanar).
EDIT:
For anyone looking for information on how to make points coplanar here is a great explination.
A better approach to procedural terrain generation that would allow
for better control of this sort of thing.
A way to represent my vertex information in a different way that allows for this.
To be clear, I am not trying to achieve a flat hex grid with raised edges or platforms (as seen below).
)
I would like all the geometry to join and lead into the next bit.
I'm hope to achieve something similar to what I have now (relatively nice undulating hills & terrain) but with more controllable plateaus. This gives me the flexibility of cording off areas (unplayable tiles) later on, where I can add higher detail meshes if needed.
Any feedback is welcome, I'm using this as a learning exercise so please - all comments welcome!
It depends on what you actually want and what you mean by "more controlled".
Do you want to be able to say "there will be a mountain on coordinates [11, -127] with radius 20"? Complexity of this this depends on how far you want to go. If you want just mountains, then radial gradients are enough (just add the gradient values to the noise values). But if you want some more complex shapes, you are in for a treat.
I explore this idea to great depth in my project (please consider that the published version is just a prototype, which is currently undergoing major redesign, it is completely usable a map generator though).
Another way is to make the generation much more procedural - you just specify a sequence of mathematical functions, which you apply on the terrain. Even a simple value transformation can get you very far.
All of these methods should work just fine for hex grid. If artefacts occur because of the odd-row shift, then you could interpolate the odd rows instead (just calculate the height value for the vertex from the two vertices between which it is located with simple linear interpolation formula).
Consider a function, which maps the purple line into the blue curve - it emphasizes lower located heights as well as very high located heights, but makes the transition between them steeper (this example is just a cosine function, making the curve less smooth would make the transformation more prominent).
You could also only use bottom half of the curve, making peaks sharper and lower located areas flatter (thus more playable).
"sharpness" of the curve can be easily modulated with power (making the effect much more dramatic) or square root (decreasing the effect).
Implementation of this is actually extremely simple (especially if you use the cosine function) - just apply the function on each pixel in the map. If the function isn't so mathematically trivial, lookup tables work just fine (with cubic interpolation between the table values, linear interpolation creates artefacts).
Several more simple methods of "gamification" of random noise terrain can be found in this paper: "Realtime Synthesis of Eroded Fractal Terrain for Use in Computer Games".
Good luck with your project
Im trying to transform a path along an arc.
My project is running on osX 10.8.2 and the painting is done via CoreAnimation in CALayers.
There is a waveform in my project which will be painted by a path. There are about 200 sample points which are mirrored to the bottom side. These are painted 60 times per second and updated to a song postion.
Please ignore the white line, it is just a rotation indicator.
What i am trying to achieve is drawing a waveform along an arc. "Up" should point to the middle. It does not need to go all the way around. The waveform should be painted along the green circle. Please take a look at the sketch provided below.
Im not sure how to achieve this in a performant manner. There are many points per second that need coordinate correction.
I tried coming up with some ideas of my own:
1) There is the possibility to add linear transformations to paths, which, i think, will not help me here. The only thing i can think of is adding a point, rotating the path with a transformation, adding another point, rotating and so on. But this would be very slow i think
2) Drawing the path into an image and bending it would surely lead to image-artifacts.
3) Maybe the best idea would be to precompute sample points on an arc, then save save a vector to the center. Taking the y-coordinates of the waveform, placing them on the sample points and moving them along the vector to the center.
But maybe i am just not seeing some kind of easy solution to this problem. Help is really appreciated and fresh ideas very welcome. Thank you in advance!
IMHO, the most efficient way to go (in terms of CPU usage) would be to use some form of pre-computed approach that would take into account the resolution of the display.
Cleverly precomputed values
I would go for the mathematical transformation (from linear to polar) and combine two facts:
There is no need to perform expansive mathematical computation
There is no need to render two points that are too close from each other
I have no ready-made algorithm for you, but you could use a pre-computed sin or cos table, and match the data range to the display size in order to work with integers.
For instance imagine we have some data ranging from 0 to 1E6 and we need to display the sin value of each point in a 100 pix height rectangle. We can use a pre-computed sin table and work with integers. This way displaying the sin value of a point would be much quicker. This concept can be refined to get a nicer result.
Also, there are some ways to retain only significant points of a curve so that the displayed curve actually looks like the original (see the Ramer–Douglas–Peucker algorithm on wikipedia). But I found it to be inefficient for quickly displaying ever-changing data.
Using multicore rendering
You could compute different areas of the curve using multiple cores (can be tricky)
Or you could use pre-computing using several cores, and one core to do finish the job.