Open ajay311517104001 opened 3 years ago
I have the same problem
I am also getting the same problem.
In the collab where inference is made, use that dependencies, this solved my issue. !pip install torch==1.4.0+cu100 torchvision==0.5.0+cu100 -f https://download.pytorch.org/whl/torch_stable.html !pip install -q mmcv terminaltables !git clone --branch v1.2.0 'https://github.com/open-mmlab/mmdetection.git' %cd "mmdetection" !pip install -r "/content/mmdetection/requirements/optional.txt" !python setup.py install !python setup.py develop !pip install -r {"requirements.txt"} !pip install pillow==6.2.1 [SOLVED]
I assume you are using MMDetection Version 2.*, if yes then change the config file i.e from cascade_mask_rcnn_hrnetv2p_w32_20e.py to cascade_mask_rcnn_hrnetv2p_w32_20e_v2.py You can find the config files in the below link https://github.com/DevashishPrasad/CascadeTabNet/tree/master/Config
I hope this will resolve your issue.
Just use config file: cascade_mask_rcnn_hrnetv2p_w32_20e_v2.py. and then update checkpoints file with Tools/upgrade_model_version.py. done!
fixed by updating config_file
to cascade_mask_rcnn_hrnetv2p_w32_20e_v2.py
. and then upgrading the version of the model by running !python /content/CascadeTabNet/Tools/upgrade_model_version.py /content/epoch_36.pth /content/new_epoch_36.pth
, and set checkpoint_file
to /content/new_epoch_36.pth
.
oh its useful for me! I have try many version of torch, cuda, mmdet, mmcv
@np-n
fixed by updating
config_file
tocascade_mask_rcnn_hrnetv2p_w32_20e_v2.py
. and then upgrading the version of the model by running!python /content/CascadeTabNet/Tools/upgrade_model_version.py /content/epoch_36.pth /content/new_epoch_36.pth
, and setcheckpoint_file
to/content/new_epoch_36.pth
.
Based on the above method, the issue got fixed. But while plotting its throwing the below error
How can I fix this??
@Pravin770 , you have to change the argument of the show_result_pyplot()
from show_result_pyplot(img, result,('Bordered', 'cell', 'Borderless'), score_thr=0.85)
to show_result_pyplot(model, img, result, score_thr=0.85)
.
getting this TypeError