Comments (9)
Which package did you install? If you have no cuda libraries you will need the CPU-only variant caffe_unet_package_16.04_cpu.tar.gz otherwise caffe will depend on the availability of cuda functions even if the GPU is not used.
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Hi Thorsten,
I think I missed this part.. How can I install the .tar.gz file?
Thank you!
Brian
from unet-segmentation.
Simply download and unpack it with tar xfvz caffe_unet_package_16.04_cpu.tar.gz
. You can then safely remove the other folder and rename the unpacked folder caffe_unet_package_16.04_cpu to u-net and it should work as expected.
from unet-segmentation.
So the following steps should do (assuming you are currently in your home folder:
wget https://lmb.informatik.uni-freiburg.de/resources/opensource/unet/caffe_unet_package_16.04_cpu.tar.gz
tar xfvz caffe_unet_package_16.04_cpu.tar.gz
rm -rf u-net
mv caffe_unet_package_16.04_cpu u-net
from unet-segmentation.
If any of the above fails you maybe need to install missing packages using apt-get install wget tar
from unet-segmentation.
Thank you for your detailed explanation. I tried installing caffe_unet_package_16.04_cpu.tar.gz just now with the code, but the problem still exists. I wonder if I need to completely remove the u-net folder before installing the caffe_unet_package_16.04_cpu.tar.gz, because I had an existing folder which was previously obtained using the following code?:
wget https://lmb.informatik.uni-freiburg.de/resources/opensource/unet/caffe_unet_package_16.04_gpu_no_cuDNN.zip
unzip caffe_unet_package_16.04_cpu.zip
Thanks!
Brian
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Hmz, the rm -rf u-net
line should have done exactly this. Your error message indicates that when trying to run caffe
the binary /home/username/u-net/bin/caffe
is selected, so the PATH seems to be fine. Can you provide additional info: First, your virtual machine is 64Bit, yes? The ImageJ-linux32 makes me a little nervous.
Trying to run the 64Bit caffe executable on a a 32Bit machine would explain the cannot execute binary file: Exer format error
. To verify the used architecture, please check the output of
uname -a
it should read similar to
Linux unethost 4.15.0-47-generic #50-Ubuntu SMP Wed Mar 13 10:44:52 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux
If it prints i686 instead of x86_64 you are running a 32Bit version of Ubuntu and you should definitely install a 64Bit version instead (if your machine is 64Bit, which should be the case if it is from after 2000). Otherwise you will be restricted to at most 4GB of RAM (including OS, Windowing system, ImageJ, ...) which will hardly suffice to run segmentations in reasonable time. If the machine indeed has only 32Bit hardware, you can still try to build caffe_unet, but then the CPU must be so old that you won't have fun with it.
from unet-segmentation.
Hi Thorsten,
My virtual machine is a 32bit. I ran uname -a
,
the output is Linux username-VirutalBox 4.15.0-45-generic #48~16.04.1-Ubuntu SMP Tue Jan 29 18:03:19 UTC 2019 i686 i686 i686 GNU/Linux
I will try install a 64bit version now and let you know the result!
Thank you very much!
Brian
from unet-segmentation.
Hi Thorsten,
After some hours on reconfigurating my desktop for installing ubuntu, I have finally got it to work with a 64-bit Ubuntu 16.04. Thank you very much for your kind help! I will now try segment some images with cells embedded in a 3D collagen matrix.
Thanks!
Brian
from unet-segmentation.
Related Issues (20)
- Exception in thread "Thread-5" java.lang.IllegalArgumentException HOT 1
- Where to obtain test data?
- Tiling makes tens of thousands of images HOT 3
- Use the weights available at https://lmb.informatik.uni-freiburg.de/resources/opensource/unet/ for Tensorflow 2 (Keras) HOT 6
- Invalid Private Key, RSA HOT 4
- CUDA 11 support HOT 3
- How to change binary path if I am using EC2? HOT 2
- output very weird HOT 5
- CUDA 10.1 support HOT 3
- U-net installation HOT 6
- Finetuning does not 'train' ,aborts HOT 6
- Segmentation does not have good separation between multiple instances of cells
- Writing a macro script to run the Finetune model
- caffe_unet not found HOT 1
- Model/weight check failed
- client loop: send disconnect: broken pipe; SFTP Failure 4 HOT 1
- caffe or caffe_unet issues HOT 7
- MacOs installation issue HOT 1
- Exporting the environment
- Installation Roadblock HOT 1
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