Comments (3)
Hi Avassadi,
It looks like the program treats the input as 2D images rather than 3D.
May I know what parameters you use for the program?
from segcaps.
Thank you for the quick response. these are my parameters:
--data_root_dir my/path/to/data
--test --net segcapsr3 --save_raw 1 --save_seg 1
from segcaps.
Hi Avassadi,
You may try to add '--dataset luna16' to try for 3D images.
By the way, did you complete training without error? The '--test' flag is for testing on pre-trained model.
from segcaps.
Related Issues (20)
- Creating MSCOCO dataset HOT 2
- What does num_atom mean?
- Instruction for running the code from .jpg files HOT 3
- TypeError: deconv_length() missing 1 required positional argument: 'output_padding' HOT 13
- bad mask HOT 1
- RuntimeError: Exception thrown in SimpleITK ReadImage: /opt/miniconda2/conda-bld/simpleitk_1546539363356/work/Code/IO/src/sitkImageReaderBase.cxx:107: sitk::ERROR: Unable to determine ImageIO reader for "data/imgs/train470.png"
- Can not load images and masks HOT 3
- Final output and raw output are always same no matter what input images are given HOT 1
- Why transformation matrix shared by different child capsule types?
- Training image and mask error HOT 4
- Did you realize the Experiments Results stated in paper of Capsules for Object Segmentation?
- RGB images with binary masks
- dependencies version
- Value Error
- ValueError: No gradients provided for any variable HOT 1
- ValueError: Dimension 0 in both shapes must be equal, but are 3 and 16.
- Proplem with deconv_length from keras.utils.conv_utils
- Where/how to display the qualitative result HOT 2
- Training Performance Do Not Improve HOT 4
- expected out_recon shape (512, 512, 1) HOT 2
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from segcaps.