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hemir17

how to use material in rendermokey?

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Hello! I'm trying to use material (.mtl file) in rendermonkey 1.81, but I didn't manage so far. Let me explain better what I'm trying to do: I have a .obj file wich has the data for draw a 3D giraffe: This giraffe.obj file calls the material file: # Object file generated from inside the onca program # The original obj file was f_0067_t65_a09.cm # Define a standard material library file # mtllib onca.mtl # v -0.289694 -8.065506 -9.263224 v -0.281216 -8.079160 -9.109410 v -0.274609 -7.924921 -9.051895 v -0.276662 -7.888772 -9.101552 ... Now, I need to use this onca.mtl file. It has the data related to the spots of the giraffe fur. Here is the file content: newmtl cellCmtl Ka 0.4078 0.2353 0.1176 Kd 0.4078 0.2353 0.1176 illum 1 newmtl cellDmtl Ka 0.9882 0.596 0.298 Kd 0.9882 0.596 0.298 illum 1 I don't have any idea how I should do that! I really would appreciate any info or tips! Thanks in advance!

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If redermonkey doesn't support .mtl files, is there any software I could use to generate a file format supported by redermonkey that include the data from the .mtl file merged with the data from .obj file?

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You need to write a plugin for rendermonkey. There is some document at ATI that explains the plugin making process.

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I got Maya 2009 and loaded the .obj with material file, so I've tried to export the file in a format supported by RenderMonkey: .dae (it is the only file format supported by both software - Maya and RenderMonkey)

However, the following error ocurred:

COLLADA Library: COLLADA_DOM Load Started.
COLLADA Library: Loading meshes...
COLLADA Loader: Error: Error: Model does not have Positional data.
COLLADA Loader: Error: Error: No faces have been defined in the model.
COLLADA Loader: Error: COLLADA Library: Error: Error: No face indices are present.
COLLADA Loader: Error: COLLADA Library: Error: Error: No faces are present.
COLLADA Loader: Error: COLLADA Library: Error: Error: Position Indices can not be found..
COLLADA Loader: Error: Error: Could not load face data. Done

Any tips or new information about that?

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