Runtime Error

[hanssssssss]

Hi! Thanks for sharing your great work. I installed your pt_mesh_render and tested it successfully. But when I used it to render the mesh ,something went wrong. The errors are below, Do you konw what cauesd these errors ?

Traceback (most recent call last): File "E:/PycharmProjects/pytorch_face/Render_test.py", line 77, in im_rgba = Render_block(face_shape,face_norm,face_color,camera_scale,f_scale,facemodel,1) File "E:/PycharmProjects/pytorch_face/Render_test.py", line 59, in Render_block far_clip=50.0) File "E:\PycharmProjects\pytorch_face\pt_mesh_renderer\mesh_renderer.py", line 355, in mesh_renderer image_width, image_height, [-1] * vertex_attributes.shape[2]) File "E:\PycharmProjects\pytorch_face\pt_mesh_renderer\rasterizer.py", line 112, in rasterize_clip_space image_width, image_height) File "E:\PycharmProjects\pytorch_face\pt_mesh_renderer\RasterizeTriangles.py", line 66, in forward barycentric, triangle_ids, z_buffer = forward_function(vertices, triangles, image_width, image_height) RuntimeError

[hanssssssss]

These are my codes, I wanted to use it to render a human face. ` def Render_block(face_shape , face_norm , face_color , camera_scale , f_scale ,facemodel,batchsize =1, is_train = None ):

# render reconstruction images
n_vex = int(facemodel.idBase.shape[0]/3)
fov_y = 2*torch.atan(torch.tensor(112./(1015*f_scale)))*180./m.pi
fov_y = torch.reshape(fov_y , [batchsize])

# full face region [batch_size, vertex_count, 3]
face_shape = torch.reshape(face_shape,[batchsize,n_vex,3])
face_norm = torch.reshape(face_norm,[batchsize,n_vex,3])
face_color = torch.reshape(face_color,[batchsize,n_vex,3])

# setting camera settings
camera_position = torch.tensor([[0,0,10.0]],dtype=torch.float32)*torch.reshape(camera_scale,[-1,1])
camera_lookat = torch.tensor([0,0,0.0],dtype=torch.float32)
camera_up = torch.tensor([0,1.0,0],dtype=torch.float32)

# setting light source position
#(intensities are set to 0 because we have computed the vertex color)
light_position = torch.tensor([0,0,1e5],dtype=torch.float32)
light_position = (torch.reshape(light_position,[1,1,3])).repeat([batchsize,1,1])
light_intensities = torch.tensor([0.0,0.0,0.0],dtype=torch.float32)
light_intensities = (torch.reshape(light_intensities, [1, 1, 3])).repeat([batchsize, 1, 1])
ambient_color = torch.tensor([1.0, 1, 1], dtype=torch.float32)
ambient_color = (torch.reshape(ambient_color, [1,3])).repeat([batchsize,1])

face_shape  =face_shape.cuda()
face_norm = face_norm.cuda()
face_color = face_color.cuda()
camera_position = camera_position.cuda()
camera_lookat = camera_lookat.cuda()
camera_up = camera_up.cuda()
light_position = light_position.cuda()
light_intensities = light_intensities.cuda()
ambient_color = ambient_color.cuda()
fov_y = fov_y.cuda()

img_rgba = mesh_renderer.mesh_renderer(vertices = face_shape,
                                       triangles = (facemodel.face_buf-1).int().cuda(),
                                       normals = face_norm,
                                       diffuse_colors = face_color,
                                       camera_position = camera_position,
                                       camera_lookat = camera_lookat,
                                       camera_up= camera_up,
                                       light_positions = light_position,
                                       light_intensities = light_intensities,
                                       image_width = 224,
                                       image_height =224,
                                       fov_y = fov_y,
                                       ambient_color= ambient_color,
                                       far_clip=50.0)

img_rgba = torch.clamp(img_rgba, 0, 255).float()

if name == 'main':

face = loadmat('./output/000002.mat')

face_shape = torch.from_numpy(face['faceshape'])

face_color = torch.from_numpy(face['face_color_'])
face_texture = torch.from_numpy(face['face_texture_'])
face_norm = torch.from_numpy(face['face_norm_'])
camera_scale = torch.from_numpy(face['camera_scale'])
f_scale = torch.from_numpy(face['f_scale'])

facemodel = BFM()
im_rgba = Render_block(face_shape,face_norm,face_color,camera_scale,f_scale,facemodel,1)
plt.imshow(im_rgba)
plt.show()`

[shty32]

Hi, I'm sorry for this delay response.

I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

[hanssssssss]

Hi, I'm sorry for this delay response.

I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

[shty32]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

[hanssssssss]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

[shty32]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

[hanssssssss]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help.

This is the demo and related information. render_test.zip

[shty32]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help.

This is the demo and related information. render_test.zip

Hi, I may solve your problem, which may be caused by a weird memory discontinuity. You can add .contiguous() on your face_buf. For example: face_buf = torch.from_numpy(face_buf_reader['face_buf']).contiguous()

[hanssssssss]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help. This is the demo and related information. render_test.zip

Hi, I may solve your problem, which may be caused by a weird memory discontinuity. You can add .contiguous() on your face_buf. For example: face_buf = torch.from_numpy(face_buf_reader['face_buf']).contiguous()

Thanks for your patience and your help!!!!! I will try it.

[hanssssssss]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help. This is the demo and related information. render_test.zip

Hi, I may solve your problem, which may be caused by a weird memory discontinuity. You can add .contiguous() on your face_buf. For example: face_buf = torch.from_numpy(face_buf_reader['face_buf']).contiguous()

I followed your instruction and finally solved this problem. Thanks! I have another question.When I get the output of the mesh_render(a rgba image). I used clamp(0-255) to and slice to get a RGB image,but what I get is a image with color of black and white. Is this a normal situation?

[shty32]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help. This is the demo and related information. render_test.zip

Hi, I may solve your problem, which may be caused by a weird memory discontinuity. You can add .contiguous() on your face_buf. For example: face_buf = torch.from_numpy(face_buf_reader['face_buf']).contiguous()

I followed your instruction and finally solved this problem. Thanks! I have another question.When I get the output of the mesh_render(a rgba image). I used clamp(0-255) to and slice to get a RGB image,but what I get is a image with color of black and white. Is this a normal situation?

This is a common issue for plt.imshow. You may use 0-1 in float or 0-255 in uint8, while clamp function does not change the type of image. For your case, you may use plt.imshow(img.astype("uint8")) to solve this problem.

[hanssssssss]

Hi, I'm sorry for this delay response. I hope you have solved your problem. If not, you may check the value and size of vertices and triangles. In my experience, the index in triangles should start from 0 rather than 1, where the later one may cause your issue.

Hi! Thanks for your reply. I did use triangles = (facemodel.face_buf-1).int().cuda(), to make suret the indexs start from 0. But the issue is still there. Do you have any other idea about this? Thanks a lot.

Hi, perhaps you may convert triangles to a LongTensor? I think this part is type-sensitive.

I have tried your method, but the error still there. I have no idea why this Runtime error show up.😥

Could you please upload a demo? Maybe I can debug it on my PC.

Thanks!!!! I really appreciate your help. This is the demo and related information. render_test.zip

Hi, I may solve your problem, which may be caused by a weird memory discontinuity. You can add .contiguous() on your face_buf. For example: face_buf = torch.from_numpy(face_buf_reader['face_buf']).contiguous()

I followed your instruction and finally solved this problem. Thanks! I have another question.When I get the output of the mesh_render(a rgba image). I used clamp(0-255) to and slice to get a RGB image,but what I get is a image with color of black and white. Is this a normal situation?

This is a common issue for plt.imshow. You may use 0-1 in float or 0-255 in uint8, while clamp function does not change the type of image. For your case, you may use plt.imshow(img.astype("uint8")) to solve this problem.

Okay!!! Thanks for your help and your great work!!!!!!!!