Comments (27)
1.3.8
from consnet.
It seems that the dependencies of full version are not installed correctly. Did you install consnet
from PyPI? If so, please uninstall it and re-install it from source following this part. The PyPI version is only designed for HICO-DET APIs but not for training or testing the models.
from consnet.
Also, <path-to-checkpoint>
should be a complete path to the object detetor's .pth
file, e.g. checkpoints/faster_rcnn_r50_fpn_3x_coco-26df6f6b.pth
.
from consnet.
Closing this issue due to lack of activity. Please feel free to re-open it if you have any further questions.
from consnet.
Hi, I also meet this problem, and I install consnet from source. When I move code from nncore.engine import load_checkpoint, set_random_seed
in models/builder.py from try except module, this problem will be solved; but I meet another problem,
from consnet.
May I ask that which pytorch, mmdet and nncore version are you using?
from consnet.
consnet 1.0.5 /home/jh/code/CosNet
torch 1.8.1
mmdet 2.11.0
nncore 0.2.6
from consnet.
nncore 0.2.6 is not tested for this repo, the version we used is 0.2.4. Also, if you meet some problem when from nncore.engine import load_checkpoint, set_random_seed
is in the try except module, it seems that there's something wrong in your mmcv/mmdet.
from consnet.
Hi. Thanks for the docs. I am getting the same error as faced by two others - NameError: name 'load_checkpoint' is not defined. I did install consnet from the source and didn't do pip install consnet. Also, I checked the versions of pytorch, mmdet and nncore - they are 1.8.1+cu102, 2.11.0 and 0.2.4 respectively. Could you please help?
from consnet.
Hi. Thanks for the docs. I am getting the same error as faced by two others - NameError: name 'load_checkpoint' is not defined. I did install consnet from the source and didn't do pip install consnet. Also, I checked the versions of pytorch, mmdet and nncore - they are 1.8.1+cu102, 2.11.0 and 0.2.4 respectively. Could you please help?
Thanks for your feedback. May I ask that did you install consnet from source using pip install -e .[full]
ranther than pip install -e .
? You may also try to modify the code here by moving the imports out of try...except to see which line raises the error.
from consnet.
Hi. Thank you @yeliudev for the reply.
I installed consnet from the source using the first command you mentioned - pip install -e .[full]
I tried removing the try-except block, but I was facing another error. I will send here the screenshot of the error in some time, as currently I am not having access to that computer.
from consnet.
ModuleNotFoundError: No module named 'mmcv._ext'
This is the error which I am facing after removing the try except block.
PFA the traceback below.
from consnet.
Also @yeliudev may I ask that what is the object detection mAP (not the HOI mAP using the complete model) on the HICO-DET test set of the two object detectors which you used - first one pretrained on COCO and the other one finetuned on HICO-DET?
from consnet.
ModuleNotFoundError: No module named 'mmcv._ext' This is the error which I am facing after removing the try except block. PFA the traceback below.
This means that you are using mmcv
instead of mmcv-full
. So that the CUDA extensions are not compiled. You may try to re-install this package.
from consnet.
Also @yeliudev may I ask that what is the object detection mAP (not the HOI mAP using the complete model) on the HICO-DET test set of the two object detectors which you used - first one pretrained on COCO and the other one finetuned on HICO-DET?
I'm not pretty sure since this project was finished years ago. I remember that the mAP of COCO detector was about 13, and the HICO-DET finetuned one shall be about 20.
from consnet.
Also @yeliudev may I ask that what is the object detection mAP (not the HOI mAP using the complete model) on the HICO-DET test set of the two object detectors which you used - first one pretrained on COCO and the other one finetuned on HICO-DET?
I'm not pretty sure since this project was finished years ago. I remember that the mAP of COCO detector was about 13, and the HICO-DET finetuned one shall be about 20.
Thanks for your response @yeliudev.
from consnet.
ModuleNotFoundError: No module named 'mmcv._ext' This is the error which I am facing after removing the try except block. PFA the traceback below.
![]()
This means that you are using
mmcv
instead ofmmcv-full
. So that the CUDA extensions are not compiled. You may try to re-install this package.
But, I installed it using the pip install command given in your docs. Also, I tried to uninstall mmcv but upon doing that it says mmcv not found, which means that mmcv-full was installed. Would you please help?
Also, what version of cudatoolkit-dev did you use in your conda environment? Here https://anaconda.org/conda-forge/cudatoolkit-dev/files?page=2 it shows that cudatoolkit-dev version 10.2 doesn't exists.
from consnet.
There are two versions of mmcv, one is called mmcv
and the other shall be mmcv-full
. You may try to manually install it by using pip install mmcv-full
and see if the CUDA extensions are compiled correctly. We did not use cudatoolkit-dev in our env. We installed CUDA from scratch in our system.
from consnet.
Thanks for the reply. Would you please check and share the exact version of your mmcv-full?
from consnet.
Thanks for sharing the version. I will check by installing this version on the system. Also, will the CUDA version matter? I don't have 10.2 in my system. Is the issue coming because of that?
from consnet.
I don't think the CUDA version matters. Compiling mmcv-full
using your own CUDA shall be fine. Please feel free to leave a message here if you meet any other problems.
from consnet.
Would you please clarify the meaning of "compiling" mmcv-full using your own CUDA? Is compiling a separate step to be done after installing mmcv-full? If yes, would you please share the command for doing so.
from consnet.
Simply running pip install mmcv-full==1.3.8
should compile it automatically. Please be check that if there is any error during the installation.
from consnet.
Thanks for your quick responses @yeliudev.
from consnet.
Hi. I was able to resolve the mmcv error. But, now I am encountering another error. I installed the packages as follows -
- pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
- pip install -U openmim
mim install mmcv-full==1.3.8
pip install mmdet==2.11.0 - pip install nncore==0.2.4
With the above 3 steps, the command of python tools/build_dataset.py started executing correctly and the hdf5 files were making up (i.e. the detection step and extraction of features). But allennlp wasn't installed. So, once I understood that mmcv is working fine, I interrupted the above execution. Then, I installed allenlp using -
- pip install allennlp==2.2.0
After this, I again ran the same command (python tools/build_dataset.py), but it errored out. Attaching the traceback below.
Will the above command (python tools/build_dataset.py) work even without installing allennlp? Or will it require allennlp to be installed? I assume that build_graph function in the file won't work without allennlp. Is it right?
from consnet.
It seems that the version of package transformers
is not correct. Could you install transformers==0.11
and try it again?
from consnet.
It seems that the version of package
transformers
is not correct. Could you installtransformers==0.11
and try it again?
Getting this when trying to install it. :(
from consnet.
Related Issues (17)
- the hico-det python API is not working HOT 1
- Consistency graph is built based on both training and test dataset? wondering if it is the main reason the method works well for unseen scenarios? HOT 1
- build_mlp HOT 4
- Lists of unseen objects and unseen actions HOT 2
- model for hico-det HOT 2
- regarding config file - build.py HOT 1
- feature extraction for bounding boxes - a minor confusion HOT 1
- consistency_graph.pkl HOT 3
- zero-shot setting
- Given an image name from HICO_DET, how can I retreive its HOI_idx using ConsNet API? HOT 10
- does ConsNet API visualize the bouding boxes? HOT 4
- build_dataset.py HOT 10
- the build_dataset function in build_dataset.py file HOT 8
- Could not download the checkpoint files HOT 3
- How to use code to infer in my own data set? My own data set is not labeled, just want to see the actual application effect of HOI algorithm HOT 1
- where is consistency_graph.pkl? Cannot find it HOT 2
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