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height map for normal input sharp edges

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height map for normal input sharp edges


height map brings weird resultalternatives for operator's report() function?Get same bump from a photo to a modelheight map brings weird resultCreate height bitmap from meshGenerating height map of group of objectsHeight Map to Mesh conversion considering TransparencyIs there a way to “clip” or “clamp” the height of a normal, so that bumps go to a certain height and then abruptly flatten, as if chopped off?Bump map height still the sameHeight Map: how to deleted unwanted faces?Height Map Using Vertex World Height (Z) as RGB ValueIs it possible to use height maps from substance designer in Blender and how?













1












$begingroup$


So I have generated this simple height map to test my add on:
enter image description here



That's the node setup and the result that I am having in Blender:
enter image description here



What is happening here (basically, that's a theory, I did not analyze the actual pixel values programmatically): Blender Bump node is interpreting each slightest variation in the pixel value (say, 0.985 white and 0.99 white) as variation in height. What you have as a result are the ugly cutoffs. By the way, a similar question with the same problem, unsolved: height map brings weird result



Now, if I do converting in CrazyBump, I have the opportunity to ignore small details, and, if I convert with CrazyBump, the map is displayed correctly in blender. By their nature, any height map, even 16K will not be absolutely smooth because the set of possible heights is a set of discrete values, it will never be smooth. The task of an algo would be to produce smooth normals from this. And this is what Bump node obviously does not do. Any suggestions? (using other software does not work, I want to achieve it specifically in the node editor of Blender, for any BW map)



and just to prove the point: if I twick the small details all the way up in CrazyBump, I will get essentially what the BumpNode in Blender is doing: overexaggerating non-significant value variations:
enter image description here










share|improve this question











$endgroup$







  • 1




    $begingroup$
    It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
    $endgroup$
    – SerhiiPoklonskyi
    5 hours ago







  • 2




    $begingroup$
    32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago







  • 1




    $begingroup$
    will do it soon. Thank you again
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago















1












$begingroup$


So I have generated this simple height map to test my add on:
enter image description here



That's the node setup and the result that I am having in Blender:
enter image description here



What is happening here (basically, that's a theory, I did not analyze the actual pixel values programmatically): Blender Bump node is interpreting each slightest variation in the pixel value (say, 0.985 white and 0.99 white) as variation in height. What you have as a result are the ugly cutoffs. By the way, a similar question with the same problem, unsolved: height map brings weird result



Now, if I do converting in CrazyBump, I have the opportunity to ignore small details, and, if I convert with CrazyBump, the map is displayed correctly in blender. By their nature, any height map, even 16K will not be absolutely smooth because the set of possible heights is a set of discrete values, it will never be smooth. The task of an algo would be to produce smooth normals from this. And this is what Bump node obviously does not do. Any suggestions? (using other software does not work, I want to achieve it specifically in the node editor of Blender, for any BW map)



and just to prove the point: if I twick the small details all the way up in CrazyBump, I will get essentially what the BumpNode in Blender is doing: overexaggerating non-significant value variations:
enter image description here










share|improve this question











$endgroup$







  • 1




    $begingroup$
    It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
    $endgroup$
    – SerhiiPoklonskyi
    5 hours ago







  • 2




    $begingroup$
    32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago







  • 1




    $begingroup$
    will do it soon. Thank you again
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago













1












1








1





$begingroup$


So I have generated this simple height map to test my add on:
enter image description here



That's the node setup and the result that I am having in Blender:
enter image description here



What is happening here (basically, that's a theory, I did not analyze the actual pixel values programmatically): Blender Bump node is interpreting each slightest variation in the pixel value (say, 0.985 white and 0.99 white) as variation in height. What you have as a result are the ugly cutoffs. By the way, a similar question with the same problem, unsolved: height map brings weird result



Now, if I do converting in CrazyBump, I have the opportunity to ignore small details, and, if I convert with CrazyBump, the map is displayed correctly in blender. By their nature, any height map, even 16K will not be absolutely smooth because the set of possible heights is a set of discrete values, it will never be smooth. The task of an algo would be to produce smooth normals from this. And this is what Bump node obviously does not do. Any suggestions? (using other software does not work, I want to achieve it specifically in the node editor of Blender, for any BW map)



and just to prove the point: if I twick the small details all the way up in CrazyBump, I will get essentially what the BumpNode in Blender is doing: overexaggerating non-significant value variations:
enter image description here










share|improve this question











$endgroup$




So I have generated this simple height map to test my add on:
enter image description here



That's the node setup and the result that I am having in Blender:
enter image description here



What is happening here (basically, that's a theory, I did not analyze the actual pixel values programmatically): Blender Bump node is interpreting each slightest variation in the pixel value (say, 0.985 white and 0.99 white) as variation in height. What you have as a result are the ugly cutoffs. By the way, a similar question with the same problem, unsolved: height map brings weird result



Now, if I do converting in CrazyBump, I have the opportunity to ignore small details, and, if I convert with CrazyBump, the map is displayed correctly in blender. By their nature, any height map, even 16K will not be absolutely smooth because the set of possible heights is a set of discrete values, it will never be smooth. The task of an algo would be to produce smooth normals from this. And this is what Bump node obviously does not do. Any suggestions? (using other software does not work, I want to achieve it specifically in the node editor of Blender, for any BW map)



and just to prove the point: if I twick the small details all the way up in CrazyBump, I will get essentially what the BumpNode in Blender is doing: overexaggerating non-significant value variations:
enter image description here







height-map






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 5 hours ago







SerhiiPoklonskyi

















asked 5 hours ago









SerhiiPoklonskyiSerhiiPoklonskyi

464




464







  • 1




    $begingroup$
    It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
    $endgroup$
    – SerhiiPoklonskyi
    5 hours ago







  • 2




    $begingroup$
    32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago







  • 1




    $begingroup$
    will do it soon. Thank you again
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago












  • 1




    $begingroup$
    It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
    $endgroup$
    – SerhiiPoklonskyi
    5 hours ago







  • 2




    $begingroup$
    32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
    $endgroup$
    – cegaton
    5 hours ago











  • $begingroup$
    @cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago







  • 1




    $begingroup$
    will do it soon. Thank you again
    $endgroup$
    – SerhiiPoklonskyi
    4 hours ago







1




1




$begingroup$
It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
$endgroup$
– cegaton
5 hours ago





$begingroup$
It might have to do with the bit depth of the height map. 8 bit images are not enough to resolve subtle gradation. Try using images in a higher bit depth. Also, images used for bumps and normals should not be interpreted as color, but as Non-Color-Data (linear)
$endgroup$
– cegaton
5 hours ago













$begingroup$
@cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
$endgroup$
– SerhiiPoklonskyi
5 hours ago





$begingroup$
@cegaton thanks for responding. bpy.data.images['...'].depth tells me it's 32 bit depth (is this the right indicator?). Also, changing to non-color does not affect the result. take a look at the last illustration: CrazyBump can algorithmically ignore or exaggerate those cuttoffs by setting its degree of attention to fine details
$endgroup$
– SerhiiPoklonskyi
5 hours ago





2




2




$begingroup$
32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
$endgroup$
– cegaton
5 hours ago





$begingroup$
32 bit is 8bit per channel+Alpha (8 bit x 4). Try creating the image as a 16 bit per channel file. Non-color data should always be used for bump and height maps to avoid the distortion caused by the 2.2 gamma curve used in image encoded in sRGB. You might get better results using a displace modifer and subsurf than using displacement in the material or shader.
$endgroup$
– cegaton
5 hours ago













$begingroup$
@cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
$endgroup$
– SerhiiPoklonskyi
4 hours ago





$begingroup$
@cegaton holy Jesus! it has solved the problem! marry me, cegaton! I totally agree with you with regard to displacement but my idea was to combine individual alpha elements to produce reliefs and cravings easily. now it will work thanks to you. if you so wish, post an answer for others, probably with a bit of explanation on depth and how it affects the result
$endgroup$
– SerhiiPoklonskyi
4 hours ago





1




1




$begingroup$
will do it soon. Thank you again
$endgroup$
– SerhiiPoklonskyi
4 hours ago




$begingroup$
will do it soon. Thank you again
$endgroup$
– SerhiiPoklonskyi
4 hours ago










1 Answer
1






active

oldest

votes


















2












$begingroup$

short answer: as @cegaton has pointed out, save your image with 16 bits depth. If you are baking like me, this has to be done before bake, because resaving later does not generate information lost while baking.
Go to 'Save as' dialog, there in the lower left corner choose 16 bits depth.



A (not so) technical explanation: if you are not familiar, depth is the number of bits used to store the pixel color. With 8 bits, you store 2^8 = 256 color values at maximum, with 16 bits that's 2^16 = 65536 possible colors. What was happening in my case is the following: for the different height values in the geometry that I was baking, an approximation was generated to store the height. In other words, for heights x-0.01, x, x+0.01s, it would simply put x, because it has no bits to store all the three. Hence the flat areas in your image, where the color gets 'simplified'. For my 8 bits image, I did for learning purposes:



len(set(bpy.data.images['My8BitImg.png'].pixels))


This has returned 256, while



len(set(bpy.data.images['My16BitImg.png'].pixels))


has returned 42891 in my case.






share|improve this answer









$endgroup$












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    1 Answer
    1






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    active

    oldest

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    active

    oldest

    votes









    2












    $begingroup$

    short answer: as @cegaton has pointed out, save your image with 16 bits depth. If you are baking like me, this has to be done before bake, because resaving later does not generate information lost while baking.
    Go to 'Save as' dialog, there in the lower left corner choose 16 bits depth.



    A (not so) technical explanation: if you are not familiar, depth is the number of bits used to store the pixel color. With 8 bits, you store 2^8 = 256 color values at maximum, with 16 bits that's 2^16 = 65536 possible colors. What was happening in my case is the following: for the different height values in the geometry that I was baking, an approximation was generated to store the height. In other words, for heights x-0.01, x, x+0.01s, it would simply put x, because it has no bits to store all the three. Hence the flat areas in your image, where the color gets 'simplified'. For my 8 bits image, I did for learning purposes:



    len(set(bpy.data.images['My8BitImg.png'].pixels))


    This has returned 256, while



    len(set(bpy.data.images['My16BitImg.png'].pixels))


    has returned 42891 in my case.






    share|improve this answer









    $endgroup$

















      2












      $begingroup$

      short answer: as @cegaton has pointed out, save your image with 16 bits depth. If you are baking like me, this has to be done before bake, because resaving later does not generate information lost while baking.
      Go to 'Save as' dialog, there in the lower left corner choose 16 bits depth.



      A (not so) technical explanation: if you are not familiar, depth is the number of bits used to store the pixel color. With 8 bits, you store 2^8 = 256 color values at maximum, with 16 bits that's 2^16 = 65536 possible colors. What was happening in my case is the following: for the different height values in the geometry that I was baking, an approximation was generated to store the height. In other words, for heights x-0.01, x, x+0.01s, it would simply put x, because it has no bits to store all the three. Hence the flat areas in your image, where the color gets 'simplified'. For my 8 bits image, I did for learning purposes:



      len(set(bpy.data.images['My8BitImg.png'].pixels))


      This has returned 256, while



      len(set(bpy.data.images['My16BitImg.png'].pixels))


      has returned 42891 in my case.






      share|improve this answer









      $endgroup$















        2












        2








        2





        $begingroup$

        short answer: as @cegaton has pointed out, save your image with 16 bits depth. If you are baking like me, this has to be done before bake, because resaving later does not generate information lost while baking.
        Go to 'Save as' dialog, there in the lower left corner choose 16 bits depth.



        A (not so) technical explanation: if you are not familiar, depth is the number of bits used to store the pixel color. With 8 bits, you store 2^8 = 256 color values at maximum, with 16 bits that's 2^16 = 65536 possible colors. What was happening in my case is the following: for the different height values in the geometry that I was baking, an approximation was generated to store the height. In other words, for heights x-0.01, x, x+0.01s, it would simply put x, because it has no bits to store all the three. Hence the flat areas in your image, where the color gets 'simplified'. For my 8 bits image, I did for learning purposes:



        len(set(bpy.data.images['My8BitImg.png'].pixels))


        This has returned 256, while



        len(set(bpy.data.images['My16BitImg.png'].pixels))


        has returned 42891 in my case.






        share|improve this answer









        $endgroup$



        short answer: as @cegaton has pointed out, save your image with 16 bits depth. If you are baking like me, this has to be done before bake, because resaving later does not generate information lost while baking.
        Go to 'Save as' dialog, there in the lower left corner choose 16 bits depth.



        A (not so) technical explanation: if you are not familiar, depth is the number of bits used to store the pixel color. With 8 bits, you store 2^8 = 256 color values at maximum, with 16 bits that's 2^16 = 65536 possible colors. What was happening in my case is the following: for the different height values in the geometry that I was baking, an approximation was generated to store the height. In other words, for heights x-0.01, x, x+0.01s, it would simply put x, because it has no bits to store all the three. Hence the flat areas in your image, where the color gets 'simplified'. For my 8 bits image, I did for learning purposes:



        len(set(bpy.data.images['My8BitImg.png'].pixels))


        This has returned 256, while



        len(set(bpy.data.images['My16BitImg.png'].pixels))


        has returned 42891 in my case.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered 3 hours ago









        SerhiiPoklonskyiSerhiiPoklonskyi

        464




        464



























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