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Final output and raw output are always same no matter what input images are given #17

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l53ma opened this issue Sep 18, 2019 · 1 comment
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@l53ma
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l53ma commented Sep 18, 2019

@Cheng-Lin-Li Thank you for your nice work!

I have one confusing question, I can successfully run the codes (both Train and Test on segcapsr3) using both MSCOCO17 and my own grey images. However, I found the final output and raw output images (stored in the folder of ../SegCaps/data/results/segcapsr3/split_0) are always the same, no matter what input images are given?

Any suggestions will be appreciated. The following is my testing code.

python3 ./main.py --test --Kfold 2 --net segcapsr3 --data_root_dir=data --loglevel 2 --which_gpus=-2 --gpus=0 --dataset mscoco17 --weights_path saved_models/segcapsr3/split-0_batch-1_shuff-1_aug-1_loss-dice_slic-1_sub--1_strid-1_lr-0.1_recon-131.072_model_20190918-151252.hdf5

@Cheng-Lin-Li Cheng-Lin-Li added the help wanted Extra attention is needed label Oct 12, 2019
@Cheng-Lin-Li
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Hi,

Please refer the readme 5.3
https://github.com/Cheng-Lin-Li/SegCaps#5-3-test-your-model

The program will convert all image files into numpy format and store training/testing images into ./data/np_files and testing (and training) file lists under ./data/split_list folders. You need to remove these two folders every time if you want to replace your training image and mask files. The program will only read data from np_files folders.

Hope this will help.

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