External Email - Use Caution

Dear R, Yes, I have tried to run "samseg_run" from the command line (I've repeated my syntax below).  I have looked both under the directory where the command ran that produced the “Illegal instruction” error.  No crash file (a logfile?) or a "core" file were written.  I also looked /var/crash but that folder was empty too.

As I mentioned, I'm a LINUX novice.  I'm even more of a novice with regard to Python. However, I did take a quick at the code looking for any mention of tensorflow, and have copied the python script text as it exists below.  I have highlighted the only mention of tensorflow below.  Does this look like you expect it? Has tensorflow actually been incorporated into the VM?   Note that I have been able to successfully run Samseg without the --lesion flag and the process works just fine (about 20min runtime, aseg looks just fine in Freeview) Again, thanks for any guidance you can provide. -Randy xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

#!/usr/bin/env python import osimport sysimport jsonimport scipy.ioimport freesurfer as fsimport freesurfer.samseg as samseg

# ------ Parse Command Line Arguments ------ parser = fs.utils.ArgumentParser() default_threads = int(os.environ.get('OMP_NUM_THREADS', 1)) # requiredparser.add_argument('-o', '--output', metavar='DIR', dest='outputDirectory', help='Output directory.', required=True)parser.add_argument('-i', '--input', nargs='+', action='extend', metavar='FILE', dest='inputFileNames', help='Input image(s).', required=True)# optional processing optionsparser.add_argument('-m', '--mode', nargs='+', help='Output basenames for the input image mode.')parser.add_argument('--threads', type=int, default=default_threads, help='Number of threads to use. Defaults to current OMP_NUM_THREADS or 1.')parser.add_argument('--reg-only', action='store_true', default=False, help='Only perform initial affine registration.')parser.add_argument('-r', '--reg', metavar='FILE', help='Skip initial affine registration and read transform from file.')parser.add_argument('--init-reg', metavar='FILE', help='Initial affine registration.')parser.add_argument('-a', '--atlas', metavar='DIR', help='Point to an alternative atlas directory.')parser.add_argument('--gmm', metavar='FILE', help='Point to an alternative GMM file.')parser.add_argument('--ignore-unknown', action='store_true', help='Ignore final priors corresponding to unknown class.')parser.add_argument('--options', metavar='FILE', help='Override advanced options via a json file.')parser.add_argument('--pallidum-separate', action='store_true', default=False, help='Move pallidum outside of global white matter class. Use this flag when T2/flair is used.')# optional lesion optionsparser.add_argument('--lesion', action='store_true', default=False, help='Enable lesion segmentation (requires tensorflow).')parser.add_argument('--threshold', type=float, default=0.3, help='Lesion threshold for final segmentation. Lesion segmentation must be enabled.')parser.add_argument('--samples', type=int, default=50, help='Number of samples for lesion segmentation. Lesion segmentation must be enabled.')parser.add_argument('--burnin', type=int, default=50, help='Number of burn-in samples for lesion segmentation. Lesion segmentation must be enabled.')parser.add_argument('--lesion-pseudo-samples', nargs=2, type=float, default=[500, 500], help='Lesion pseudo samples mean and variance.')parser.add_argument('--lesion-rho', type=float, default=50, help='Lesion ratio.')parser.add_argument('--lesion-mask-structure', default='Cortex', help='Intensity mask brain structure. Lesion segmentation must be enabled.')parser.add_argument('--lesion-mask-pattern', type=int, nargs='+', help='Lesion mask list (set value for each input volume): -1 below lesion mask structure mean, +1 above, 0 no mask. Lesion segmentation must be enabled.')# optional debugging optionsparser.add_argument('--history', action='store_true', default=False, help='Save history.')parser.add_argument('--save-posteriors', nargs='*', help='Save posterior volumes to the "posteriors" subdirectory.')parser.add_argument('--save-probabilities', action='store_true', help='Save final modal class probabilities to "probabilities" subdirectory.')parser.add_argument('--showfigs', action='store_true', default=False, help='Show figures during run.')parser.add_argument('--save-mesh', action='store_true', help='Save the final mesh in template space.')parser.add_argument('--save-warp', action='store_true', help='Save the image->template warp field.')parser.add_argument('--movie', action='store_true', default=False, help='Show history as arrow key controlled time sequence.') args = parser.parse_args() # ------ Initial Setup ------ # Make sure freesurfer has been sourcedif not fs.fshome():    fs.fatal('FREESURFER_HOME must be set') # Start the process timertimer = fs.utils.Timer() # Create the output folderos.makedirs(args.outputDirectory, exist_ok=True) # Specify the maximum number of threads the GEMS code will usesamseg.setGlobalDefaultNumberOfThreads(args.threads) # Remove previous cost logcostfile = os.path.join(args.outputDirectory, 'cost.txt')if os.path.exists( costfile ):    os.remove( costfile )  # Get the atlas directoryatlasDir = os.environ.get('SAMSEG_DATA_DIR')if args.atlas:    atlasDir = args.atlasif not atlasDir:    # Altas defaults    if args.lesion:        defaultAtlas = '20Subjects_smoothing2_down2_smoothingForAffine2_lesion'    else:        defaultAtlas = '20Subjects_smoothing2_down2_smoothingForAffine2'    atlasDir = os.path.join(fs.fshome(), 'average', 'samseg', defaultAtlas) # Setup the visualization toolvisualizer = samseg.initVisualizer(args.showfigs, args.movie) # ------ Prepare Samseg Parameters ------ # Load user options from a JSON fileuserModelSpecifications = {}userOptimizationOptions = {}if args.options:    with open(args.options) as f:        userOptions = json.load(f)    if userOptions.get('modelSpecifications') is not None:         userModelSpecifications = userOptions.get('modelSpecifications')    if userOptions.get('optimizationOptions') is not None:         userOptimizationOptions = userOptions.get('optimizationOptions') # Check if --save-posteriors was specified without any structure search stringif args.save_posteriors is not None and len(args.save_posteriors) == 0:    savePosteriors = Trueelse:    savePosteriors = args.save_posteriors # ------ Run Samseg ------ samseg_kwargs = dict(    imageFileNames=args.inputFileNames,    atlasDir=atlasDir,    savePath=args.outputDirectory,    userModelSpecifications=userModelSpecifications,    userOptimizationOptions=userOptimizationOptions,    targetIntensity=110,    targetSearchStrings=[ 'Cerebral-White-Matter' ],    visualizer=visualizer,    saveHistory=args.history,    saveMesh=args.save_mesh,    savePosteriors=savePosteriors,    saveWarp=args.save_warp,    modeNames=args.mode,    pallidumAsWM=(not args.pallidum_separate),    saveModelProbabilities=args.save_probabilities,    gmmFileName=args.gmm,    ignoreUnknownPriors=args.ignore_unknown,) if args.lesion:     # If lesion mask pattern is not specified, assume inputs are T1-contrast    lesion_mask_pattern = args.lesion_mask_pattern    if lesion_mask_pattern is None:        lesion_mask_pattern = [0] * len(args.inputFileNames)        print('Defaulting lesion mask pattern to %s' % str(lesion_mask_pattern))     # Delay import until here so that tensorflow doesn't get loaded unless needed    from freesurfer.samseg.SamsegLesion import SamsegLesion    samseg = SamsegLesion(**samseg_kwargs,        numberOfPseudoSamplesMean=args.lesion_pseudo_samples[0],        numberOfPseudoSamplesVariance=args.lesion_pseudo_samples[1],        rho=args.lesion_rho,        intensityMaskingSearchString=args.lesion_mask_structure,        intensityMaskingPattern=lesion_mask_pattern,        numberOfBurnInSteps=args.burnin,        numberOfSamplingSteps=args.samples,        threshold=args.threshold    ) else:    samseg = samseg.Samseg(**samseg_kwargs) _, _, _, optimizationSummary = samseg.segment(    costfile=costfile,    timer=timer,    transformFile=args.reg,    initTransformFile=args.init_reg,    reg_only=args.reg_only) # Save a summary of the optimization processwith open(costfile, 'a') as file:    for multiResolutionLevel, item in enumerate(optimizationSummary):        file.write('atlasRegistrationLevel%d %d %f\n' % (multiResolutionLevel, item['numberOfIterations'], item['perVoxelCost'])) timer.mark('run_samseg complete') xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx PS. Repeating the syntax from below. run_samseg --input /home/developer/subjects_new/o_ADNI_002_S_4654__MRI-m072__LMCI-LMCI__20180522__T30-acc_orig__S689126_I1001975.nii /home/developer/subjects_new/rT1_o_ADNI_002_S_4654__MRI-m072__LMCI-LMCI__20180522__T2-FLAIR__S689135_I1001984.nii --pallidum-separate --lesion --lesion-mask-pattern 0 1 --output /home/developer/subjects_new/Lesion-test/

-----Original Message----- From: fsbuild fsbuild@contbay.com To: freesurfer@nmr.mgh.harvard.edu Cc: daedalus39@aol.com Sent: Thu, Feb 24, 2022 5:15 pm Subject: Re: [Freesurfer] SAMSEG "lesion" (Illegal instruction) ~ running VM_67

Hello Randy, I think the expectation is for users to run “samseg” from the command line.  (The samseg script is a front-end you run with command line options, e.g., —help, which calls samseg_run that in turn runs the samseg python scripts in the freesurfer python distribution which includes the tensorflow code). I can’t speak to the validity of the command + options causing the crash, but I would look too see if a “core” file was written in the directory where the command ran that produced the “Illegal instruction” error and subsequent crash.  The core file might also be under /var/crash.  If you have the core file you could name it something unique and try uploading it to https://secure-web.cisco.com/1_8ugcIT497YTUyY1vRRMjZbWfONaiAbR1P1Zg9-6zNbgUF... someone to look at. - R.

On Feb 24, 2022, at 11:58, daedalus39@aol.com wrote:         External Email - Use Caution         Following up on yesterday's email: I looked up the help text for SAMSEG on the VM (“run_samseg –help”).  The flag for --lesion indicates that Tensorflow is required.     --lesion        Enable lesion segmentation (requires tensorflow). I'm not sure is tensorflow is installed in VM_67, but "which tensorflow" returned nothing.  While my question only reported the “core dump” and a request to check the syntax, I did ask if the “lesion” flag was implemented in the VM.   If it's not installed in VM_67, would you be able to offer some guidance as to where the safest download site is and some suggestions as to how to install it?

Sincerely, -Randy

-----Original Message----- From: daedalus39@aol.com To: freesurfer@nmr.mgh.harvard.edu freesurfer@nmr.mgh.harvard.edu Sent: Wed, Feb 23, 2022 1:19 pm Subject: SAMSEG "lesion" (Illegal instruction) ~ running VM_67

Dear Experts, I am trying to test SAMSEG "lesion" on VM_67 and after I entered: run_samseg --input /home/developer/subjects_new/o_ADNI_002_S_4654__MRI-m072__LMCI-LMCI__20180522__T30-acc_orig__S689126_I1001975.nii /home/developer/subjects_new/rT1_o_ADNI_002_S_4654__MRI-m072__LMCI-LMCI__20180522__T2-FLAIR__S689135_I1001984.nii --pallidum-separate --lesion --lesion-mask-pattern 0 1 --output /home/developer/subjects_new/Lesion-test/

...I got the following error Illegal instruction (core dumped)

Is there anything glaringly wrong in my instruction/input phrase? Is SAMSEG "lesion" implemented in the new VM?  I was able to test the "basic" SAMSEG with a single T1 earlier this morning (it ran just fine) Thanks in advance for any help. -Randy_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://secure-web.cisco.com/1ajCHs20Ntg5vd9AD9I6GP72nyffMyNANWVvUGOngP_c0ac...