Comments (8)
Hi! thank you for releasing the code for your amazing research! When I evaluate my model (pre_model also be evaluated) in NoW challenge, I also follow the guide from https://github.com/soubhiksanyal/now_evaluation.
python check_predictions.py <predicted_mesh_path>
this code exports the input mesh to predicted_mesh_export.obj
. when I open the mesh in MeshLab, I find it not a face shape. it just like that:
I find the page said: "The used mesh loader is unable to load OBJ files with vertex colors appended to the vertices. I.e. if the OBJ contains lines of the following format v vx vy vz cr cg cb\n, export the meshes without vertex colors."
I wonder if the reason is the obj file outputed by test obtained the vertex colors.
Again, thank you for your attention!
from deep3dfacerecon_pytorch.
Hi! thank you for releasing the code for your amazing research! When I evaluate my model (pre_model also be evaluated) in NoW challenge, I also follow the guide from https://github.com/soubhiksanyal/now_evaluation.
python check_predictions.py <predicted_mesh_path>
this code exports the input mesh topredicted_mesh_export.obj
. when I open the mesh in MeshLab, I find it not a face shape. it just like that:I find the page said: "The used mesh loader is unable to load OBJ files with vertex colors appended to the vertices. I.e. if the OBJ contains lines of the following format v vx vy vz cr cg cb\n, export the meshes without vertex colors."
I wonder if the reason is the obj file outputed by test obtained the vertex colors.
Again, thank you for your attention!
Hi~ I meet the same issue in the first time with default test.py. On the 66 line in test.py , it save the .obj file using save_mesh()function, and you can edit the function in 215 line in facerecon_model.py, just remove the
vertex_colors=np.clip(255. * recon_color, 0, 255).astype(np.uint8)
In this way, I can get the correct .obj file after executing check_predictions.py.
By the way, did you get 3d coordinates of 7 key points? I'm still a little confused about that.. Thanks for your attention.
from deep3dfacerecon_pytorch.
Hi, we first select 7 vertices on the template mesh (mean shape) as keypoints indicated by NoW, Then we automatically calculate the 3D coordinates of 7 keypoints for each subjects from their reconstructed meshes.
from deep3dfacerecon_pytorch.
Hi! thank you for releasing the code for your amazing research! When I evaluate my model (pre_model also be evaluated) in NoW challenge, I also follow the guide from https://github.com/soubhiksanyal/now_evaluation.
python check_predictions.py <predicted_mesh_path>
this code exports the input mesh topredicted_mesh_export.obj
. when I open the mesh in MeshLab, I find it not a face shape. it just like that:
I find the page said: "The used mesh loader is unable to load OBJ files with vertex colors appended to the vertices. I.e. if the OBJ contains lines of the following format v vx vy vz cr cg cb\n, export the meshes without vertex colors."
I wonder if the reason is the obj file outputed by test obtained the vertex colors.
Again, thank you for your attention!Hi~ I meet the same issue in the first time with default test.py. On the 66 line in test.py , it save the .obj file using save_mesh()function, and you can edit the function in 215 line in facerecon_model.py, just remove the
vertex_colors=np.clip(255. * recon_color, 0, 255).astype(np.uint8)
In this way, I can get the correct .obj file after executing check_predictions.py.
By the way, did you get 3d coordinates of 7 key points? I'm still a little confused about that.. Thanks for your attention.
sorry, I just saw your answer. This solved my problem, Thank you!
For the question about getting 3d coordinates of 7 key points, I guess we need to get 3d coordinates of 7 key points in the BFM model(Maybe in the function save_mesh of facerecon_model.py) In 68 landmarks, We could use the landmarks with indices [36,39,42,45,33,48,54] , But I don't know if it works on the problem. Thanks for your attention.
from deep3dfacerecon_pytorch.
Hi @YuDeng,
For computing, the 7 3D locations for the NoW benchmark is the following procedure correct?
- Use the 7 landmark points from the
similarity_Lm3D_all.mat
and find the index of the nearest vertices for those in the mean shape. - Use the same indices in the final shape to get the 3D landmark points
from deep3dfacerecon_pytorch.
I found that just selecting 7 key landmarks by the array that you mentioned, the result of distance calculated by now_evaluate was very large.
from deep3dfacerecon_pytorch.
Hi @YuDeng,
For computing, the 7 3D locations for the NoW benchmark is the following procedure correct?
- Use the 7 landmark points from the
similarity_Lm3D_all.mat
and find the index of the nearest vertices for those in the mean shape.- Use the same indices in the final shape to get the 3D landmark points
Hi have you found the correct indices of these 7 landmarks?
from deep3dfacerecon_pytorch.
Hi! thank you for releasing the code for your amazing research! When I evaluate my model (pre_model also be evaluated) in NoW challenge, I also follow the guide from https://github.com/soubhiksanyal/now_evaluation.
python check_predictions.py <predicted_mesh_path>
this code exports the input mesh topredicted_mesh_export.obj
. when I open the mesh in MeshLab, I find it not a face shape. it just like that:
I find the page said: "The used mesh loader is unable to load OBJ files with vertex colors appended to the vertices. I.e. if the OBJ contains lines of the following format v vx vy vz cr cg cb\n, export the meshes without vertex colors."
I wonder if the reason is the obj file outputed by test obtained the vertex colors.
Again, thank you for your attention!Hi~ I meet the same issue in the first time with default test.py. On the 66 line in test.py , it save the .obj file using save_mesh()function, and you can edit the function in 215 line in facerecon_model.py, just remove the
vertex_colors=np.clip(255. * recon_color, 0, 255).astype(np.uint8)
In this way, I can get the correct .obj file after executing check_predictions.py.
By the way, did you get 3d coordinates of 7 key points? I'm still a little confused about that.. Thanks for your attention.
thanks a lot for your contribution
from deep3dfacerecon_pytorch.
Related Issues (20)
- visualize the face mesh without texture and color HOT 2
- RuntimeError: Cuda error: 304[cudaGraphicsGLRegisterBuffer(&s.cudaPosBuffer, s.glPosBuffer, cudaGraphicsRegisterFlagsWriteDiscard);] HOT 1
- ValueError: Unknown CUDA arch (8.9) or GPU not supported
- On the issue of differences in training visualization and testing effectiveness
- False error in training
- FileNotFoundError: [Errno 2] No such file or directory: './checkpoints/face_recon/epoch_latest.pth'
- Use this project with recent GPU ? HOT 6
- Open mouth HOT 2
- A little confusion about mask used for computing feat loss HOT 1
- Pretrained model
- No module named 'models.arcface_torch' HOT 1
- RuntimeError: CUDA error: no kernel image is available for execution on the device
- ImportError: DLL load failed HOT 2
- RuntimeError: Error building extension 'nvdiffrast_plugin_gl': ninja: error: build.ninja:3: lexing error HOT 1
- What does align_img do in test.py? HOT 1
- error while running HOT 1
- UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd3 in position 1454: invalid continuation byte
- ImportError: libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive HOT 5
- resnet50-0676ba61.pth
- Thank you for your work. There is no result showing in preprocess_in_th_wild.py
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from deep3dfacerecon_pytorch.