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License: MIT License
The database does not exist anymore, maybe you can share some sample files?
Currently I want to visit the project website: http://irc.cs.sdu.edu.cn/Deep3DPose/, but I can't connect the site, so would you repair it?
Tried to run demo_skel2RR.m file after copying the .mat generated in the first step and I got the following error
>> demo_skel2RR
1
Error using svd
Input to SVD must not contain NaN or Inf.
Error in myscript_5_calculate_RR_W (line 32)
[U, S, V] = svd(S0);
Error in skel2RR (line 20)
[ R, ~, ~ ] = myscript_5_calculate_RR_W( hip_points_wangchuyu2, hip_points_scape, weights );
Error in demo_skel2RR (line 40)
[ RR, R ] = skel2RR( skel, skel_scape );
I printed the values, and found it has a nan, what could be the reason, how to fix it?
skel =
1.0e+06 *
0.0000 0 0
0.0000 0.0000 0.0000
0 0.0000 0.0000
0.0000 0.0000 0.0000
0.0000 0.0000 NaN
0.0000 0.0000 0.0000
0.0000 0.0000 0.0000
0.0000 0.0000 0.0000
-0.2052 0.2239 -0.1732
0.9907 0.1787 -0.1732
1.0224 0.0280 -0.1732
1.6550 -0.1944 0.3118
0.9785 0.1787 -0.1732
1.4086 -0.5319 -0.6151
1.5216 -0.1191 -0.6151
Where should I set these parameters , which all files?
I did it in all the prototxt files, I am not sure if it is correct. I am still getting errors.
What should the value of these parameters?
errors(No grl and fc interval parameters!) from:
AdaGradSolverTest/2
NesterovSolverTest/1.
SGDSolverTest/2,
and a different error from:
MultinomialLogisticLossLayerTest/1.TestGradientCPU
F0206 17:19:14.692884 12446 multinomial_logistic_loss_layer.cpp:61] Check failed: bottom[1]->channels() == bottom[0]->channels() (1 vs. 5)
It would have been easier to visualize the result, if the order of joints output from caffe is known. When tested with real-images, results are not very convincing. Could you please mention the order of joints in the 15x3 result ?
I have spent some time in understanding your paper. I have some questions on domain adaptation
point 1:
After 1st stage of training for several iterations for a good classifier and regressor, you change the dataset to change the labels to 0.5 , freeze the domain mixer/classifier layers , by keeping the lr_mult: =0. train again(stage 2) for several iterations ? Please spare some time to correct me if I am wrong
point 2:
Note that we train the network in a circular way, stage1
is alternate with stage2. This is because domain classifier is
based on current feature extractor. If we modify the extractor
in stage2, then we need to refine new classifier in stage1.
So it is a circular process
After 2 stages of training you have already got the pose regressor without any gap between syn and real data. Then why do we need to do it circularly again? Could you please explain that? " This is because domain classifier is based on current feature extractor" , but feature extractor changes in every iterations anyway? I didn't understand this point ! Thanks in advance .
Is there any demo file, of how it works for this application, steps from data preparation, model selection? If not, could you please provide one? Where is the data located? How to pass it via arguments
Itried,
ppl4hi@HI-Z0FH9:~/CODES/Deep3DPose-master/5-caffe$ ./examples/adaptation/scripts/prepare_experiments.sh
Downloading AlexNet reference model...
Downloading ImageNet aux data...
Preparing datasets...
Preparing directories for experiments...
ppl4hi@HI-Z0FH9:~/CODES/Deep3DPose-master/5-caffe$
But, the folder /5-caffe/examples/adaptation/datasets/ is empty, so it gives me error when training. What could be the reason?
May be because of this, when running train.sh script, i get error
ppl4hi@HI-Z0FH9:~/CODES/Deep3DPose-master/5-caffe$ ./examples/adaptation/experiments/amazon_to_webcam/scripts/train.sh
I0131 15:40:19.995388 22027 caffe.cpp:113] Use GPU with device ID 0
I0131 15:40:21.525190 22027 caffe.cpp:121] Starting Optimization
I0131 15:40:21.525326 22027 solver.cpp:34] Initializing solver from parameters:
test_iter: 795
test_interval: 10000
base_lr: 0.001
display: 100
max_iter: 50000
lr_policy: "inv"
gamma: 0.001
power: 0.75
momentum: 0.9
snapshot: 10000
snapshot_prefix: "/home/ppl4hi/CODES/Deep3DPose-master/5-caffe/examples/adaptation/experiments/amazon_to_webcam/snapshots/train"
solver_mode: GPU
net: "/home/ppl4hi/CODES/Deep3DPose-master/5-caffe/examples/adaptation/experiments/amazon_to_webcam/protos/train_val.prototxt"
I0131 15:40:21.525411 22027 solver.cpp:87] Creating training net from net file: /home/ppl4hi/CODES/Deep3DPose-master/5-caffe/examples/adaptation/experiments/amazon_to_webcam/protos/train_val.prototxt
I0131 15:40:21.526595 22027 net.cpp:257] The NetState phase (0) differed from the phase (1) specified by a rule in layer target_data
I0131 15:40:21.526620 22027 net.cpp:257] The NetState phase (0) differed from the phase (1) specified by a rule in layer target_domain_labels
I0131 15:40:21.526648 22027 net.cpp:257] The NetState phase (0) differed from the phase (1) specified by a rule in layer bottleneck_alias
I0131 15:40:21.526660 22027 net.cpp:257] The NetState phase (0) differed from the phase (1) specified by a rule in layer lp_accuracy
I0131 15:40:21.526957 22027 net.cpp:42] Initializing net from parameters:
name: "AlexNet for Office"
state {
phase: TRAIN
.
.
.
.
The following is the error,
I0131 15:40:21.528966 22027 layer_factory.hpp:73] Creating layer source_data
I0131 15:40:21.529003 22027 net.cpp:84] Creating Layer source_data
I0131 15:40:21.529016 22027 net.cpp:338] source_data -> source_data
I0131 15:40:21.529047 22027 net.cpp:338] source_data -> lp_labels
I0131 15:40:21.529063 22027 net.cpp:113] Setting up source_data
F0131 15:40:21.529134 22027 db.hpp:116] Check failed: mdb_status == 0 (2 vs. 0) No such file or directory
*** Check failure stack trace: ***
@ 0x7fbb3dedadaa (unknown)
@ 0x7fbb3dedace4 (unknown)
@ 0x7fbb3deda6e6 (unknown)
@ 0x7fbb3dedd687 (unknown)
@ 0x7fbb3e23370e caffe::db::LMDB::Open()
@ 0x7fbb3e2d1a78 caffe::DataLayer<>::DataLayerSetUp()
@ 0x7fbb3e2fbe36 caffe::BaseDataLayer<>::LayerSetUp()
@ 0x7fbb3e2fbf39 caffe::BasePrefetchingDataLayer<>::LayerSetUp()
@ 0x7fbb3e251302 caffe::Net<>::Init()
@ 0x7fbb3e252dc2 caffe::Net<>::Net()
@ 0x7fbb3e25f5f0 caffe::Solver<>::InitTrainNet()
@ 0x7fbb3e26082e caffe::Solver<>::Init()
@ 0x7fbb3e260b26 caffe::Solver<>::Solver()
@ 0x40d410 caffe::GetSolver<>()
@ 0x4075a3 train()
@ 0x405bb1 main
@ 0x7fbb3d3ecf45 (unknown)
@ 0x40615d (unknown)
@ (nil) (unknown)
Aborted (core dumped)
Thanks in advance.
I have tested an image from the data you have provided in the project website.
Thank you
I tried to make the code: It gives me the following error:
`$ make runtest
.build_release/tools/caffe
caffe: command line brew
usage: caffe
commands:
train train or finetune a model
test score a model
device_query show GPU diagnostic information
time benchmark model execution time
Flags from tools/caffe.cpp:
-gpu (Run in GPU mode on given device ID.) type: int32 default: -1
-iterations (The number of iterations to run.) type: int32 default: 50
-model (The model definition protocol buffer text file..) type: string
default: ""
-snapshot (Optional; the snapshot solver state to resume training.)
type: string default: ""
-solver (The solver definition protocol buffer text file.) type: string
default: ""
-weights (Optional; the pretrained weights to initialize finetuning. Cannot
be set simultaneously with snapshot.) type: string default: ""
.build_release/test/test_all.testbin 0 --gtest_shuffle
Cuda number of devices: 8
Setting to use device 0
Current device id: 0
Note: Randomizing tests' orders with a seed of 10499 .
[==========] Running 1092 tests from 198 test cases.
[----------] Global test environment set-up.
[----------] 6 tests from NesterovSolverTest/3, where TypeParam = caffe::DoubleG PU
[ RUN ] NesterovSolverTest/3.TestNesterovLeastSquaresUpdate
F0130 14:06:28.077040 39193 solver.cpp:60] No grl and fc interval parameters!
*** Check failure stack trace: ***
@ 0x2b06c60c4daa (unknown)
@ 0x2b06c60c4ce4 (unknown)
@ 0x2b06c60c46e6 (unknown)
@ 0x2b06c60c7687 (unknown)
@ 0x2b06c7a006eb caffe::Solver<>::Init()
@ 0x2b06c7a00856 caffe::Solver<>::Solver()
@ 0x4f9302 caffe::NesterovSolverTest<>::InitSolver()
@ 0x4f9bcb caffe::GradientBasedSolverTest<>::InitSolverFromProtoS tring()
@ 0x4ede9a caffe::GradientBasedSolverTest<>::RunLeastSquaresSolve r()
@ 0x4f1613 caffe::NesterovSolverTest_TestNesterovLeastSquaresUpda te_Test<>::TestBody()
@ 0x703dc3 testing::internal::HandleExceptionsInMethodIfSupported <>()
@ 0x6faa07 testing::Test::Run()
@ 0x6faaae testing::TestInfo::Run()
@ 0x6fabb5 testing::TestCase::Run()
@ 0x6fdef8 testing::internal::UnitTestImpl::RunAllTests()
@ 0x6fe187 testing::UnitTest::Run()
@ 0x442eda main
@ 0x2b06c86ccf45 (unknown)
@ 0x447f69 (unknown)
@ (nil) (unknown)
make: *** [runtest] Aborted (core dumped)
$
`
What could be the error? Please help
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