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chengjie-cjwang avatar lijiannuist avatar linchuming avatar

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actiondetection-dbg's Issues

How to use C3D extracted features?

Thank you for your open source work. Optical flow feature extraction is too slow and does not have engineering significance. I want to try the features extracted by C3D. Your paper mentioned this. What are the details?

proposal

Can someone give me a proposal.txt or proposal.json of DBG?My Laboratory Conditions can't make it. If you can generate proposal,can you send me one? Thanks.
My email is [email protected]

run error

Thanks for your work. But I met an error when I run this code:python pytorch/test.py config/config_pretrained.yaml .The error :
Traceback (most recent call last):
File "pytorch/test.py", line 11, in
from model import DBG
File "/mnt/songyan/10519_xuminhuang/ActionDetection-DBG-master/pytorch/model.py", line 4, in
from custom_op.prop_tcfg_op import PropTcfg
File "/mnt/songyan/10519_xuminhuang/ActionDetection-DBG-master/pytorch/custom_op/prop_tcfg_op.py", line 4, in
import prop_tcfg_cuda
ImportError: /mnt/songyan/10519_xuminhuang/anaconda3/lib/python3.7/site-packages/prop_tcfg_cuda-0.0.0-py3.7-linux-x86_64.egg/prop_tcfg_cuda.cpython-37m-x86_64-linux-gnu.so: undefined symbol: __cudaRegisterFatBinaryEnd

my tool:
pytorch1.1
cuda9
python3.7
gcc5.4
Can someone help me solve this problem?thanks

THUMOS14

Thank you a lot. Recently, our research group is following your work. If you can share the code and files of THUMOS14 with us, it will be convenient for us to do comparative experiments

Segmentation fault when define the whole model with PFG layer compiled

I have compiled the PFG layer to prop_tcfg.so. After that, i'm going to train a new network in which T == 500, for long videos. However, when i define the model, "Segmentation fault" breakouted, and this is the all error description.
Could u please tell what the problem is? Thanks!

error:
WARNING:tensorflow:From ***************/DBG/model.py:19: conv1d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.keras.layers.Conv1D instead.
WARNING:tensorflow:From ****************/lib/python3.6/site-packages/tensorflow/python/ops/init_ops.py:1251: calling VarianceScaling.init (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
Segmentation fault

THUMOS14 code can you share ?

I admire your experiment very much,but I have encountered some troubles when trying to implement the algorithm related to Thumos14.
can you send me your code and the features on Thumos14?
my email address : [email protected]

features csv different from provided

thanks for ur great work!

we used tools/run.sh to get videos' rgb and flow feature csvs,
and then used tools/data_process.py to join then together
but we found the joined csvs are different from the data u provided
any suggestion ? thanks!

the zip file contains three csvs
*_t.csv temporal
*_s.csv spatial
*_a.csv joined
ca.zip

[run error] No OpKernel was registered to support Op 'PropTcfg' with these attrs

Hi,
I had follow the instructions to installed tf1.9.0 and python3.6, and compiled "Proposal Feature Generation Layer" successfully, which generate "prop_tcfg.so". but when run "bash auto_run.sh", following errors were occured:

loading config file: ./config.yaml
loading config file: ./config.yaml
2019-11-23 17:13:54.840138: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-11-23 17:13:54.841548: I tensorflow/core/common_runtime/process_util.cc:69] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
Runing DBG model ...
0%| | 0/296 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/anaconda2/envs/tf19/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1322, in _do_call
return fn(*args)
File "/home/anaconda2/envs/tf19/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1307, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/anaconda2/envs/tf19/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1409, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: No OpKernel was registered to support Op 'PropTcfg' with these attrs. Registered devices: [CPU], Registered kernels:
device='GPU'; T in [DT_FLOAT]

 [[Node: model/PropTcfg = PropTcfg[T=DT_FLOAT, center_num=16, end_num=8, mode=0, start_num=8](model/strided_slice)]]

It seems like the Op 'PropTcfg' was not registered correctly, but How can I fix it? Thank you!

About the provided features!!

Thank you for your work. The features of ActivityNet are also provided in the BSN code. Is there any difference between the features you provide?

Can you release the THUMOS14 features?

Hello! Thanks for your work, I have been looking for the features extracted from THUMOS14 dataset. While I haven't seen anyone released it. I wanna kown if you can release the features, which will help me a lot.

Thumos code

Hello! Thanks for your work.could you send me your code on Thumos14 please?
it will help me a lot. thank you very much!!!
my email address : [email protected]

Extracting Feature Error

Hi, I just downloaded the feature from Google Drive.

And when use tar to extract features, it looks like:
tar: This does not look like a tar archive

Do you know there is something wrong with the feature?

I downloaded twice from the Google Drive.

Question about PFG layer

Brilliant work and thanks for the open source code.

I'm now reading the paper and code about the DBG model and I have a question about the PFG layer.

According to the paper and the code, the parameter w_l and w_r for the the PFG layer's output at location (t_s, t_e, n, c), which corresponding to the w, h, t, c in the code if I have understood correctly, can be directly calculated under the formula (1)(2)(3)(4) in the "Proposal feature generation layer" section. But both the paper and code shows that this layer is a trainable layer. So will the w_l and w_r be updated during the backward? Since it looks like a variable that don't need to be trained rather than a trainable parameter to me and I'm confused about this. Could you please explain this? Thank you very much!

When will train.py be released?

Thanks for sharing the project!
Recently, I was learning DBG papers and codes, really want to try training with my own dataset. May i ask the time schedule of releasing the traing codes (train.py)?

Was my result correct?

After I downloaded the 14.2 GB ActivityNet features (Very hard, must use Tencent Weiyun VIP in my network environment), I ran the auto_run.sh and get the following results:

 [INIT] Loaded annotations from validation subset. 
 processoNumber of ground truth instances: 7292
 processoNumber of proposals: 472700 
Fixed threshold for tiou score: [0.5  0.55 0.6  0.65 0.7  0.75 0.8  0.85 0.9  0.95] 
[RESULTS] Performance on ActivityNet proposal task.
        Area Under the AR vs AN curve: 47.82460230389468%
AR@1 is          0.27855183763027974
AR@5 is          0.3704470652770159
AR@10 is         0.4054306088864509
AR@100 is        0.5950630828304992

@lijiannuist
I wonder if the result i got above is correct....?Why does it look like that the result is not good? Thanks...

Awesome project! Question about rescale the feature length.

Thanks for sharing!
The inference speed is extremely faster with a better result.
I'm thinking about how to reproduce the result on other datasets.
Could you share some detail or insight about how to use linear interpolation to rescale the feature length of all videos to same length 100 ?

Any method function, reference papers or codes will be thankful.

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