reproduce results on Area5 for instance segmentation

[wxinlong]

reproduce results on Area5 for instance segmentation

[WXinlong]

Hi, your results are weird. Can you help me check if the dataset including the annotations are collected and organized correctly. Or could you try again in enrironment with python2.7 and tensorflow1.3.

[FrankCAN]

Hi Xinlong,
Thanks for your response.

I can generate *.npy and *h5 files successfully by following your guidance, so do it mean that the annotations should be no problem and organized correctly?

The difference is just that I only trained data/train_hdf5_file_list_woArea5.txt file instead, but I think train_hdf5_file_list_woArea1~5.txt are totally separate, have no any connection, and they only use for CV test, am I right? Should I have to train train_hdf5_file_list_woArea1 to train_hdf5_file_list_woArea5 completely?

Thanks a lot for your help.

Best Regards
Frank

[WXinlong]

train_hdf5_file_list_woArea5.txt means the filelist of area 1,2,3,4,6.
The code was tested with Python 2.7. I suggest you use an environment with Python2.7 and TF1.3. Please refer to #12 for more help.

[FrankCAN]

Hi Xinlong,
Thanks for your help, I got expected results, and even a little bit higher than your paper, thanks.

[hu-zhiyu]

It's weird that I still got unmatched Area5 instance segmentation results when using the pretrained model. I used an environment with python 2.7 and tensorflow 1.3.0 under Ubuntu 16.04. The semantic segmentation results are all good. Any idea why?
Here below are the results that I got:
Instance Segmentation mMUCov: 0.388768637499
Instance Segmentation mMWCov: 0.41931708045
Instance Segmentation mPrecision: 0.49950009677
Instance Segmentation mRecall: 0.357493869746

Semantic Segmentation oAcc: 0.869736688706
Semantic Segmentation mAcc: 0.609961164943
Semantic Segmentation mIoU: 0.534575881062