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> 54 workspace = run_pipeline(pipeline_filename, images)ġ743 ldr = static_call('java/lang/ClassLoader', 'getSystemClassLoader', JavaExceptionTraceback (most recent call last) It saves potential problems with direct calling individual cellprofiler functions from different modules. This works excellently, because pipelines could be well tested beforehand using GUI mode. So I just output to command lines using n function from subprocess package in python. CELLPROFILER YOU MUST SPECIFY A PIPELINE FILENAME TO RUN WINDOWSCellprofiler works well in headless mode using command lines in windows CMD prompt. While searching for solutions, I did find a way to get around this problem. The error message is pasted at the end of my reply. I added your javabridge command and got a different error message this time. CELLPROFILER YOU MUST SPECIFY A PIPELINE FILENAME TO RUN INSTALLInstalled through "pip install cellprofiler".Any work-around?ĭesktop (please complete the following information): No resolution seems having been reported. I noticed that several others have also reported issues with this function in the past. So, it seems that the execution was jammed at "javabridge.class_for_name()". > 910 klass = env.find_class(class_name)ĩ12 jexception = get_env().exception_occurred()ĪttributeError: 'NoneType' object has no attribute 'find_class' > 939 fn = make_static_call(class_name, method_name, sig)ĩ40 args_sig = split_sig(sig)Ĭ:\users\fermispm\appdata\local\programs\python\python38\lib\site-packages\javabridge\jutil.py in make_static_call(class_name, method_name, sig) > 1743 ldr = static_call('java/lang/ClassLoader', 'getSystemClassLoader',ġ745 return static_call('java/lang/Class', 'forName',Ĭ:\users\fermispm\appdata\local\programs\python\python38\lib\site-packages\javabridge\jutil.py in static_call(class_name, method_name, sig, *args) > 336 ifcls = javabridge.class_for_name("")ģ37 scls = env.find_class("java/lang/String")Ĭ:\users\fermispm\appdata\local\programs\python\python38\lib\site-packages\javabridge\jutil.py in class_for_name(classname, ldr) In run_pipeline(pipeline_filename, image_dict)Ĭ:\users\fermispm\appdata\local\programs\python\python38\lib\site-packages\cellprofiler_core\modules\images.py in prepare_run(self, workspace) > 51 workspace = run_pipeline(pipeline_filename, images) Workspace = run_pipeline(pipeline_filename, images)ĪttributeErrorTraceback (most recent call last) Image_set.add(image_name, cellprofiler_(input_pixels)) Image_set = image_set_list.get_image_set(0)įor image_name, input_pixels in image_ems(): # Create the image set, and add the image data ![]() CELLPROFILER YOU MUST SPECIFY A PIPELINE FILENAME TO RUN MOVIEThere’s no significant processing speedup that I can think of running headless, other than not having the GUI on, so if you’re really after speed, you may want to look into batch processing, ie sending every movie off to a different computer.Pipeline = cellprofiler_() m file to execute all the modules, passing handles back and forth, like you would in a pipeline. Once the handles are set in Matlab, I would just write an. ![]()
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