shreyashampali / honnotate Goto Github PK
View Code? Open in Web Editor NEWCVPR2020. HOnnotate: A method for 3D Annotation of Hand and Object Poses
Home Page: https://www.tugraz.at/index.php?id=40231
License: GNU General Public License v3.0
CVPR2020. HOnnotate: A method for 3D Annotation of Hand and Object Poses
Home Page: https://www.tugraz.at/index.php?id=40231
License: GNU General Public License v3.0
As the title.
Thanks for your terrific job!
I am confused about the loss between the point cloud and the vertex. You said in your paper that for each point of the point cloud, you look for the closest vertex on the corresponding mesh. But i don't quite understand the corresponding part computing the loss in your code. Could you please spare a time to explain it?
Thanks again!
Thank you for your excellent work!
Can the code in the repository estimate hand-object 3D pose from a first-person perspective?
If so, what additional work is required?
Hello, when I run
python objectTrackingSingleFrame.py --seq 'test'
for '1.1. Object pose initialization' from the ReadMe I get an OutOfRangeError exception at what appears to be the very end of the run:.
maskPC for Image test/0/02294 is 0.036168
[Loading New frame ][0/02294]
'runOptimization' 63.31 ms
0.0034784062
0.0529846
0.026492303
'runOptimization' 561.64 ms
maskPC for Image test/0/02297 is 0.035820
[Loading New frame ][0/02297]
'runOptimization' 78.96 ms
0.003642647
0.060919605
0.03045981
'runOptimization' 1479.31 ms
Traceback (most recent call last):
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1356, in _do_call
return fn(*args)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1341, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1429, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.OutOfRangeError: 2 root error(s) found.
(0) Out of range: End of sequence
[[{{node cond/IteratorGetNext}}]]
[[cond/IteratorGetNext/_15]]
(1) Out of range: End of sequence
[[{{node cond/IteratorGetNext}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "objectTrackingSingleFrame.py", line 329, in <module>
objectTracker(w, h, paramInit, camProp, mesh, out_dir, configData)
File "objectTrackingSingleFrame.py", line 142, in objectTracker
opti1.runOptimization(session, 1, {loadData:True})
File ".../HOnnotate/HOnnotate/optimization/ghope/utils.py", line 159, in timed
result = method(*args, **kw)
File ".../HOnnotate/HOnnotate/optimization/ghope/optimization.py", line 69, in runOptimization
session.run(self.optOp, feed_dict=feedDict)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 950, in run
run_metadata_ptr)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1350, in _do_run
run_metadata)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: 2 root error(s) found.
(0) Out of range: End of sequence
[[node cond/IteratorGetNext (defined at .../HOnnotate/HOnnotate/optimization/ghope/loss.py:227) ]]
[[cond/IteratorGetNext/_15]]
(1) Out of range: End of sequence
[[node cond/IteratorGetNext (defined at .../HOnnotate/HOnnotate/optimization/ghope/loss.py:227) ]]
0 successful operations.
0 derived errors ignored.
Original stack trace for 'cond/IteratorGetNext':
File "objectTrackingSingleFrame.py", line 329, in <module>
objectTracker(w, h, paramInit, camProp, mesh, out_dir, configData)
File "objectTrackingSingleFrame.py", line 62, in objectTracker
frameCntInt, loadData, realObservs = LossObservs.getRealObservables(ds, numFrames, w, h)
File ".../HOnnotate/HOnnotate/optimization/ghope/loss.py", line 242, in getRealObservables
lambda: dummyFunc(fidV, segV, depthV, colV, maskV, frameCntIntV))
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 1977, in cond
orig_res_t, res_t = context_t.BuildCondBranch(true_fn)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 1814, in BuildCondBranch
original_result = fn()
File ".../HOnnotate/HOnnotate/optimization/ghope/loss.py", line 241, in <lambda>
frameID, seg, depth, col, mask, frameCntInt = tf.cond(loadRealObservs, lambda: loadVars(fidV, segV, depthV, colV, maskV, frameCntIntV),
File ".../HOnnotate/HOnnotate/optimization/ghope/loss.py", line 227, in loadVars
frameID, seg, depth, col, mask = dataset.make_one_shot_iterator().get_next()
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/data/ops/iterator_ops.py", line 426, in get_next
output_shapes=self._structure._flat_shapes, name=name)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/ops/gen_dataset_ops.py", line 1947, in iterator_get_next
output_shapes=output_shapes, name=name)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File ".../.conda/envs/HOnnotate/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()
I'm wondering if this is expected/intended as the way for the script to bail out of the while(True) loop in objectTracker(...) in objectTrackingSingleFrame.py? If I add a try/except around session.run(self.optOp, feed_dict=feedDict) in runOptimization(...) the script never ends (due to the while(True) in objectTracker(...).
try:
session.run(self.optOp, feed_dict=feedDict)
except tf.errors.OutOfRangeError:
break # break the while(True)
Should I instead, put the try/except around the call site for objectTracker so that the while(True) will bail out? Is there a better method? Thanks.
try:
objectTracker(w, h, paramInit, camProp, mesh, out_dir, configData)
except tf.errors.OutOfRangeError:
pass # We're done
Thanks a lot.
Python: 3.6.12
HOnnotate git hash: d94f6b7
dirt git hash: 571addc359201b668d9dc450086c6dce6c18d0b6
CUDA: 11
tensorflow: 1.14
GCC: 8.3.1
Hi, thx for the nice Ho3d dataset. However I find that handJoints3D in annotation seems not right, thus I can not calculate hand bbox from it. Does anyone else counter this problem?
I found the 3D hand joints from the MANO layer is not aligned with the annotation: annotations['handJoints3D']
gt_mano_pose = torch.tensor(annotations['handPose'][None])
gt_mano_shape = torch.tensor(annotations['handBeta'][None])
gt_mano_trans = torch.tensor(annotations['handTrans'])[None]
gt_verts, gt_joints = mano_layer(th_pose_coeffs=gt_mano_pose, th_betas=gt_mano_shape, th_trans=gt_mano_trans)
I just checked the annotations['handJoints3D']
projected to image is aligned with hand but gt_joints
do not.
Could you please explain why? Thanks in advance!
Hi,Hampali.
Thanks for this great work!
I have some confusions about pose constraints:
2.As u said in the paper , L2 regularizer function is a more common method to limit joint angles. Have u compared the different effects of L2 regularizer function without PCA and your method proposed as equation 8 in paper?
Hope for your kind reply.
All best
Hao Meng
Hi, when I run python handPoseMultiframeInit.py --seq 'test
I got index out of range on projPts = utilsEval.chProjectPoints(m.J_transformed, camMat, False)[jointsMap]
I check your code and find out that you loaded the mano model, but the m.J_trandformed only has 16 joints as in the mano model, while the jointsMap has 21 joints' index
I wonder how to get 21 joints' information in your code using mano model for the loss calculation
Thanks
Hi @shreyashampali ,
Thank you for the code. I am trying to run the code with test folder you provided.
System Configuration: GTX 1050Ti 4GB RAM
WHen I run this command : "objectTrackingSingleFrame.py --seq 'test' " it is saying that GPU OutOfMemory. Is there a way to run in on 4GB graphics ?
are these any FLAGS that I could modify to lower the data ?
Thank you for your suggestions.
Thank you for your very helpful package on github. I am having trouble with an error at the object pose initialization.
I am having problems with the following commands
$ python objectTrackingSingleFrame.py --seq 'test'
Let me share a little briefly what I have been able to ascertain. Below is my execution environment. Basically, the execution environment is made of dockers. The docker recognizes the nvidia driver, and libraries around cuda are also running.
ubuntu16.04
cuda9.0
cudnn7.6.5
python3.5
tensorflow1.12
tensorflow-gpu1.12
On segmentation, I could run below command and get result like this.
$ python inference_seg.py --seq 'test'
And then, on hand 2d kyepoints, I could run below command and get result like this.
python inference_hand.py --seq 'test'
And next, on object pose initialization, if I run this command,
$ python objectTrackingSingleFrame.py --seq 'test'
An error happens like this,
"Allocator (GPU_0_bfc) ran out of memory trying to allocate 29.75GiB."
What GPU did you use with 29 GB of memory?
Hi @shreyashampali ,
The objectTracking script fails to track the object with provided Pose for the test sequence.
for mustard bottle:
"translationInit": [0.0, 0.0, -0.4],
"rotationInit": [-0.28, -1.86, -2.19], are these values correct ? The tracking fails completely. I tried to modify the parameters as suggested manually, but I failed to get the correct tracking.
If these initial values are not correct for test sequence could you please share the correct values ?
Sample image after few frames:
Thank you!
Thanks for publishing this work. I'm trying to use this work after almost 3 years of this being released now. I just wanted to check if anyone has a or is willing to provide a working docker image for this repo?
I submitted my result on the competition,but It don't give me my score.I want to know how long can I know my score .
Hi @shreyashampali
thanks for the great work. I am just testing some predictions on the codalab today , but I always encounder the same error as the following:
Execution time limit exceeded!
Would you please help to look into this.
Thanks.
Hi,
First thanks for such great work!
When I submit my result in codalab , I meet errors as follows:
WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap. /opt/conda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment. warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.') You are using pip version 9.0.1, however version 20.2.3 is available. You should consider upgrading via the 'pip install --upgrade pip' command. Traceback (most recent call last): File "/tmp/codalab/tmp3wJDBP/run/program/evaluate.py", line 400, in <module> set_name='evaluation' File "/tmp/codalab/tmp3wJDBP/run/program/evaluate.py", line 214, in main pred_file = _search_pred_file(pred_path, pred_file_name) File "/tmp/codalab/tmp3wJDBP/run/program/evaluate.py", line 200, in _search_pred_file raise Exception('Giving up, because its not clear which file to evaluate.') Exception: Giving up, because its not clear which file to evaluate.
Could you spare some time to solve it?
Thanks a lot!
Hi, it is gratefull for your works.When I use the HO3D for my hand 3d pose estimation(just the 21 joints location, not the mesh), I found that the evaluation split just has the root joint 3d anno about the wrist.
So it confuses me can I evaluate my work on the HO3D?
or how can I evaluate the 21 hand joints on HO3D?
We sincerely look forward to your reply.
Best wishes.
First,thank u for such great work!
Now I have been confused about the joint order in the dataset.
In the ho3d_v2 dataset, you mention the joint order is different from that of MANO model.
And now I take part in the competetion Ho3d_v2 Codalab competition u provide, and I get the reults which have high error in joint loacation but much lower mesh error.
So I wonder if the joint order in the evaluation dataset is also different from that of original MANO model?
Hope you could provide some suggestion,thank u!
Anaconda environment:
Python version : 3.6.1
tensorflow version : 1.12.0
tensorflow-gpu version : 1.12.0
I got this error when trying to execute the command : "python objectTrackingSingleFrame.py --seq 'test'"
I got the following error:
PROBLEM : "WARNING: failed to load librasterise.so; rasterisation functions will be unavailable:
libtensorflow_framework.so.2: cannot open shared object file: No such file or directory
"
1.I googled and saw that that one solution is to try adding the path to LD_LIBRARY_PATH
2. The python version in the anaconda virtual environment is 3.6.1
3. I executed "find . -name "libtensorflow_framework.so" -print" in the directory where anaconda is installed. I got the following output:
./anaconda3/pkgs/tensorflow-1.10.0-py36_0/lib/python3.6/site-packages/tensorflow/libtensorflow_framework.so
./anaconda3/pkgs/tensorflow-base-2.3.0-eigen_py38hb57a387_0/lib/python3.8/site-packages/tensorflow/libtensorflow_framework.so.2
./anaconda3/pkgs/tensorflow-base-1.12.0-mkl_py36h3c3e929_0/lib/python3.6/site-packages/tensorflow/libtensorflow_framework.so
./anaconda3/pkgs/tensorflow-base-1.12.0-gpu_py36had579c0_0/lib/python3.6/site-packages/tensorflow/libtensorflow_framework.so
./anaconda3/pkgs/tensorflow-base-2.2.0-gpu_py38h83e3d50_0/lib/python3.8/site-packages/tensorflow/libtensorflow_framework.so.2
./anaconda3/pkgs/tensorflow-base-1.14.0-py37h4531e10_0/lib/python3.7/site-packages/tensorflow/libtensorflow_framework.so.1
./anaconda3/envs/honnotate_tf2/lib/python3.8/site-packages/tensorflow/libtensorflow_framework.so.2
./anaconda3/envs/honnotate/lib/python3.6/site-packages/tensorflow/libtensorflow_framework.so
4. All the instances of "libtensorflow_framework.so.2" are under directories corresponging to python version 3.8 whereas the anaconda environment has python 3.6.
Hi @shreyashampali ,
I can't upload the submission to the ho3d_v2 challenge in codelab, and can't download the score either. Could you share which this would be fixed? Thanks in advance!
When I run python objectTrackingSingleFrame.py --seq 'test' --doPyRender. I found that 'self.camera.projMatrix = elements' in vis.py is useless. PerspectiveCamera can not set the Intrinsics. I change it to IntrinsicsCamera slove the problem.
In the supplementary material, the first term in the constraint of Thumb MCP is (0.00, 2.00), but in the code, this term is (-5,5). Which is right?
Hi, thanks for your sharing!
As above, If I only need to annotate the pose of object without hand, can this work get the right result?
The CodaLab Challenge of HO3Dv2 was down, could you repair it. I want to do some work based on it, but it has been down frequently. Could U public the testing dataset like FreiHAND? It's too much trouble to upload for evaluation.
Per the readme it says:
python handPoseMultiframe.py --seq 'test' --numIter 200 --showFig --doPyRender
Remove --showFig and --doPyRender flags to run faster without visualization.
If I run
python handPoseMultiframe.py --seq 'test' --numIter 200
It gets all the way through and then throws this exception:
'runOptimization' 468.36 ms
[Open3D WARNING] GLFW Error: X11: The DISPLAY environment variable is missing
[Open3D WARNING] Failed to initialize GLFW
Traceback (most recent call last):
File "handPoseMultiframe.py", line 701, in <module>
handPoseMF(w, h, objParamInitList, handParamInitList, mesh, camProp, out_dir)
File "handPoseMultiframe.py", line 431, in handPoseMF
vis.get_render_option().light_on = False
AttributeError: 'NoneType' object has no attribute 'light_on'
The issue is that its trying to bring up a window even though --showFig is not specified. I'm running this script remotely so I can't bring up any windows. So I didn't supply --showFig or --doPyRender.
It appears that the fix is simply checking if FLAGS.showFig is true before bringing up the visualizer. So something like:
if FLAGS.showFig:
vis = o3d.visualization.Visualizer()
vis.create_window(window_name='Open3D', width=640, height=480, left=0, top=0,
visible=True) # use visible=True to visualize the point cloud
vis.get_render_option().light_on = False
vis.add_geometry(finalHandMesh)
vis.add_geometry(finalObjMesh)
vis.run()
That appears to fix the problem for me.
python 3.6.12
tensor-flow 1.14.0
CUDA 11.0
HOnnotate git hash d94f6b7
Dependency libraries like DIRT support TensorFlow 2.x already. Does this code support it as well?
On ubuntu20.04, python3.6, cuda9.0, cudnn7, tensorflow1.12, tensorflow-gpu1.12 and GPU RTX3090, after following the installation and setup mentioned in readme, I ran "python inference_seg.py --seq 'test'. I used the given checkpoints, I don't think I'm missing anything in the readme, but the results are as the attached file. Could you please tell me about possible errors or mistakes.
Thanks for your great work! But I got 502 bad gateway error when I tried to download the ho3d dataset(version 2) from your website. I'd be really appreciated if you can help me!
I have applied for this competition for two months and still have not passed, can I still participate in this competition?
Hi,
The F-scores results of the HO3D-v2 Codalab Challenge are all zeros. The maintainer of the Codalab said that the organizers could fix this easily, as described here. Could you please help us to fix this problem?
Best regards,
Hao
first thanks for such great work, and i really want do some research based on such dataset.
However, when i install all the requirements as you told,and run " python inference_seg.py --seq 'test'",I got errors like that:
Traceback (most recent call last):
File "inference_seg.py", line 166, in
app.run(main)
File "/home/haomeng/anaconda3/envs/py35/lib/python3.5/site-packages/absl/app.py", line 299, in run
_run_main(main, args)
File "/home/haomeng/anaconda3/envs/py35/lib/python3.5/site-packages/absl/app.py", line 250, in _run_main
sys.exit(main(argv))
File "inference_seg.py", line 163, in main
runNetInLoop(fileListIn, numImgs)
File "inference_seg.py", line 105, in runNetInLoop
sess, g, predictions, dataPreProcDict = getNetSess(data, h, w, myG)
File "/home/haomeng/PycharmProjects/HOnnotate/utils/predictSegHandObject.py", line 69, in getNetSess
output_stride=FLAGS.output_stride)
File "/home/haomeng/PycharmProjects/HOnnotate/models/deeplab/common.py", line 240, in new
int(x) for x in FLAGS.decoder_output_stride]
TypeError: 'int' object is not iterable
And I doubt that the version of some libiraies caused it.
My virtual enviroment was like that,and could u be generous to tell me the difference?
I am really confused that i do as I see in reademe ,but meet such issues.
_libgcc_mutex 0.1 main defaults
absl-py 0.9.0 pypi_0 pypi
astor 0.8.1 pypi_0 pypi
attrs 19.3.0 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
bleach 3.1.5 pypi_0 pypi
ca-certificates 2020.6.24 0 defaults
certifi 2016.2.28 py35_0 defaults
chumpy 0.69 pypi_0 pypi
cycler 0.10.0 pypi_0 pypi
cython 0.29.20 pypi_0 pypi
decorator 4.4.2 pypi_0 pypi
defusedxml 0.6.0 pypi_0 pypi
dirt 0.3.0 pypi_0 pypi
entrypoints 0.3 pypi_0 pypi
freetype-py 2.1.0.post1 pypi_0 pypi
gast 0.3.3 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.30.0 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
imageio 2.8.0 pypi_0 pypi
importlib-metadata 1.7.0 pypi_0 pypi
ipykernel 5.3.0 pypi_0 pypi
ipython 7.9.0 pypi_0 pypi
ipython-genutils 0.2.0 pypi_0 pypi
ipywidgets 7.5.1 pypi_0 pypi
jedi 0.17.1 pypi_0 pypi
jinja2 2.11.2 pypi_0 pypi
joblib 0.14.1 pypi_0 pypi
jsonschema 3.2.0 pypi_0 pypi
jupyter-client 6.1.5 pypi_0 pypi
jupyter-core 4.6.3 pypi_0 pypi
keras-applications 1.0.8 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.1.0 pypi_0 pypi
libedit 3.1.20191231 h7b6447c_0 defaults
libffi 3.2.1 hd88cf55_4 defaults
libgcc-ng 9.1.0 hdf63c60_0 defaults
libstdcxx-ng 9.1.0 hdf63c60_0 defaults
markdown 3.2.2 pypi_0 pypi
markupsafe 1.1.1 pypi_0 pypi
matplotlib 3.0.3 pypi_0 pypi
mistune 0.8.4 pypi_0 pypi
nbconvert 5.6.1 pypi_0 pypi
nbformat 5.0.7 pypi_0 pypi
ncurses 6.2 he6710b0_1 defaults
networkx 2.4 pypi_0 pypi
notebook 6.0.3 pypi_0 pypi
numpy 1.18.5 pypi_0 pypi
open3d 0.10.0.0 pypi_0 pypi
opencv-python 4.2.0.34 pypi_0 pypi
openssl 1.0.2u h7b6447c_0 defaults
packaging 20.4 pypi_0 pypi
pandocfilters 1.4.2 pypi_0 pypi
parso 0.7.0 pypi_0 pypi
pexpect 4.8.0 pypi_0 pypi
pickleshare 0.7.5 pypi_0 pypi
pillow 7.2.0 pypi_0 pypi
pip 9.0.1 py35_1 defaults
prometheus-client 0.8.0 pypi_0 pypi
prompt-toolkit 2.0.10 pypi_0 pypi
protobuf 3.12.2 pypi_0 pypi
ptyprocess 0.6.0 pypi_0 pypi
pyglet 1.5.7 pypi_0 pypi
pygments 2.6.1 pypi_0 pypi
pyopengl 3.1.0 pypi_0 pypi
pyparsing 2.4.7 pypi_0 pypi
pypng 0.0.20 pypi_0 pypi
pyrender 0.1.43 pypi_0 pypi
pyrsistent 0.16.0 pypi_0 pypi
python 3.5.6 hc3d631a_0 defaults
python-dateutil 2.8.1 pypi_0 pypi
pywavelets 1.1.1 pypi_0 pypi
pyyaml 5.3.1 pypi_0 pypi
pyzmq 19.0.1 pypi_0 pypi
readline 7.0 h7b6447c_5 defaults
scikit-image 0.15.0 pypi_0 pypi
scikit-learn 0.22.2.post1 pypi_0 pypi
scipy 1.4.1 pypi_0 pypi
send2trash 1.5.0 pypi_0 pypi
setuptools 49.1.0 pypi_0 pypi
six 1.15.0 pypi_0 pypi
sklearn 0.0 pypi_0 pypi
sqlite 3.32.3 h62c20be_0 defaults
tensorboard 1.14.0 pypi_0 pypi
tensorflow-estimator 1.14.0 pypi_0 pypi
tensorflow-gpu 1.14.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.3 pypi_0 pypi
testpath 0.4.4 pypi_0 pypi
tf-slim 1.1.0 pypi_0 pypi
tk 8.6.10 hbc83047_0 defaults
tornado 6.0.4 pypi_0 pypi
tqdm 4.47.0 pypi_0 pypi
traitlets 4.3.3 pypi_0 pypi
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trimesh 3.7.6 pypi_0 pypi
wcwidth 0.2.5 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
werkzeug 1.0.1 pypi_0 pypi
wheel 0.29.0 py35_0 defaults
widgetsnbextension 3.5.1 pypi_0 pypi
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h7b6447c_0 defaults
zipp 1.2.0 pypi_0 pypi
zlib 1.2.11 h7b6447c_3 defaults
I noticed that the 3D coordinates in the camera coordinate system(anno['handJoints3D']) are very small. It doesn't seem like the units are in millimeters. What are the units of these landmark points?
Hi, where can I find the code of 3d hand pose estimation baseline, especially the optimization of Eq. 14. Thanks.
can we use the attached forward kinematics and model with predicted 3d points to calculate the hand vertex?
When I run handObjectRefinementMultiframe.py, I encountered this error: AttributeError: 'PerspectiveCamera' object has no attribute 'set_projection_matrix'. How to solve it?
The same issue also appears to HO3D_v3 challenge. After the fixing, it becomes:
WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap. /opt/conda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment. warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.') Execution time limit exceeded!
Could you please to kindly provide some help? Thanks!
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