1996scarlet / dense-head-pose-estimation Goto Github PK
View Code? Open in Web Editor NEW[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.
License: MIT License
[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.
License: MIT License
What would need to be changed to use the FLAME 3DMM instead of the BFM?
hi @1996scarlet
Is it expected that the model uses around 18GB of video RAM?
Or does it maximises the RAM available to help with speed? (I got a 24GB ram GPU, and usage goes up to 22.2GB while inferencing)
Thanks for this amazing MIT license repo btw.
thanks
In the original 3DDFA_v2, one can choose to use MobileNet or Resnet. Resnet is slower, but gives better tracking results.
I can’t find anything in the code about that. Has that functionality been replaced with something different and/or better?
It worked well with:
$ python3 demo_video.py -m pose -f ./re.mp4
$ python3 demo_video.py -m sparse -f ./re.mp4
$ python3 demo_video.py -m dense -f ./re.mp4
but with mesh
not as you see here:
$python3 demo_video.py -m mesh -f ./re.mp4
2022-12-05 17:03:03.713207: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
Traceback (most recent call last):
File "demo_video.py", line 55, in
main(args)
File "demo_video.py", line 21, in main
color = service.TrianglesMeshRender("asset/render.so", "asset/triangles.npy")
File "/home/redhwan/2/HPE/tensorflow/Dense-Head-Pose-Estimation-main/service/CtypesMeshRender.py", line 17, in init
self._clibs = ctypes.CDLL(clibs)
File "/usr/lib/python3.8/ctypes/init.py", line 373, in init
self._handle = _dlopen(self._name, mode)
OSError: asset/render.so: cannot open shared object file: No such file or directory
While running "python3 demo_video.py -m mesh -f
I receive the following ERROR:
File "demo_video.py", line 53, in
main(args)
File "demo_video.py", line 16, in main
fa = service.DenseFaceReconstruction("weights/dense_face.tflite")
File "/home/happy/PycharmProjects/Dense-Head-Pose-Estimation/service/TFLiteFaceAlignment.py", line 11, in init
num_threads=num_threads)
TypeError: init() got an unexpected keyword argument 'num_threads'
A splendid job! My work is about to make use of the head pose(R and T). So how to print the result.
hi,
I want to get information about the depth of the face, how do I calculate it?
i don't need rendering but only need depth map.
like
https://github.kakaocorp.com/data-sci/3DDFA_V2_tf2/blob/master/utils/depth.py
thank you in advance!
@1996scarlet I am currently using the tflite model from your repo. I am running inference on a mac so I would like to convert the model into coreml (for Apple M1/M2) . Can you provide me the source model so that I can convert this into coreml format or suggest some ways to convert tflite to coreml ?
Does anyone have a problem with accuracy of landmarks around the eyes, like if i have my eyes fully open or fully closed, the landmarks wont change.
Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
File "demo_video.py", line 53, in
main(args)
File "demo_video.py", line 18, in main
color = service.TrianglesMeshRender("asset/render.so",
File "/home/xuhao/workspace/Dense-Head-Pose-Estimation-main/service/CtypesMeshRender.py", line 17, in init
self._clibs = ctypes.CDLL(clibs)
While running "python3 demo_video.py -m mesh -f
I receive the following ERROR
OSError: asset/render.so: cannot open shared object file: No such file or directory
I can successfully run the other three modes (sparse, dense, pose)
Thanks, it is a great job! Could you please release your training code?
Thank you for your code.
I'd like to know how can I get 3D landmark coordinates? Like (x,y,z)
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