java - Displaying texture in spritesheet based on ID's -


i've been trying display blocks on screen, each different textures. i've got spritesheet set code. can't manage specific coordinates in spritesheet, can't display else first image.

i've got render function set up:

public static void render(int texture, int blockid) {     float xpos = (float)blockid;     float ypos = 0;      while(xpos > 9) {         xpos -= 10;         ypos++;     }      glbindtexture(gl_texture_2d, texture);      glpushmatrix();         glbegin(gl_triangles);             gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(16, 0);             gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(0, 0);             gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(0, 16);              gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(0, 16);             gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(16, 16);             gltexcoord2f((8f / 160f) * xpos, (8f / 160f) * ypos); glvertex2i(16, 0);         glend();     glpopmatrix(); }

it decides texture take blockid, if blockid 1 takes second image spritesheet, if it's 2 takes third image, etc.

but don't know have multiply xpos , ypos variables gltexcoord2f. i've tried different ways like:

gltexcoord2f(xpos / 128f, 0f / 128f); glvertex2i(16, 0); gltexcoord2f(0f / 128f, ypos / 128f); glvertex2i(0, 16);

or

gltexcoord2f((0f / 128f) * xpos, 0f / 128f; glvertex2i(16, 0); gltexcoord2f(0f / 128f, (8f / 128f)) * ypos; glvertex2i(0, 16);

and even

gltexcoord2f(0f / 128f, 0f / 128f); glvertex2i(16 * xpos, 0); gltexcoord2f(0f / 128f, 8f / 128f); glvertex2i(0, 16 * ypos);

but none worked.

=== edit ===

i've managed working. odd blockid's. if blockid 1 displays first texture, if it's 2 displays brownish color (that isn't on spritesheet) , if blockid 3 displays second texture on sheet etc.

texture coordinates exist within range: 0.0f --> 1.0f

you need calculate how far along (in percentage) image sprite is, feed texcoord float.

i think should using:

   (8.0f / 128.0f) * xpos             (you should cache float once works)

if not work, ensure these 2 things:

  • hard coded values work (proving texture loaded , initialised fine)
  • the correct values being calculated within render method

alternatively, don't forget render triangles glcolor(1.0f, 1.0f, 1.0f) ensure rest of rendering in application works.


Comments

Post a Comment

Popular posts from this blog

python - How to create a legend for 3D bar in matplotlib? -

Image
given ax = plt.subplot() : ax.bar()[0] can passed plt.legend() . however, ax.bar3d() returns none . how create legend displayed bars? update: passing legend="stuff" ax.bar3d() , calling ax.legend() raises /usr/lib/python2.6/site-packages/matplotlib/axes.py:4368: userwarning: no labeled objects found. use label='...' kwarg on individual plots. warnings.warn("no labeled objects found. " you need use proxy artist legends not supported. this code: from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot plt import numpy np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x, y = np.random.rand(2, 100) * 4 hist, xedges, yedges = np.histogram2d(x, y, bins=4) elements = (len(xedges) - 1) * (len(yedges) - 1) xpos, ypos = np.meshgrid(xedges[:-1]+0.25, yedges[:-1]+0.25) xpos = xpos.flatten() ypos = ypos.flatten() zpos = np.zeros(elements) dx = 0.5 * np.ones_like(zpos) dy = dx.copy() dz = hist.flatten() ax...
Read more

java - Multi-Label Document Classification -

i have database in store data based upon following 3 fields: id, text, {labels}. note each text has been assigned more 1 label \ tag \ class. want build model (weka \ rapidminer \ mahout) able recommend \ classify bunch of labels \ tags \ classes given text. i have heard svm , naive bayes classifier, not sure whether support multi-label classification or not. guides me right direction more welcome! the basic multilabel classification method one-vs.-the-rest (ovr), called binary relevance (br). basic idea take off-the-shelf binary classifier, such naive bayes or svm, create k instances of solve k independent classification problems. in python-like pseudocode: for each class k: learner = svm(settings) # example labels = [class_of(x) == k x in samples] learner.learn(samples, labels) then @ prediction time, run each of binary classifiers on sample , collect labels predict positive. (both training , prediction can done in parallel, since problems assumed ...
Read more

php - Dynamic url re-writing using htaccess -

how can rewrite http://mydomain.com/test/master.php?catid=2&subcatid=8 http://mydomain.com/test/master.php/catname/subcat using .htaccess file. once rewritten, how can access these parameters in master.php? note: untested, let me know if doesn't work. rewriterule ^master.php/([a-za-z0-9_-]+)/([a-za-z0-9_-]+)$ /master.php?catid$1&subcatid=$2 [l]
Read more