User Tools

Site Tools


downloads:cryolo_1

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
Next revision Both sides next revision
downloads:cryolo_1 [2019/12/18 10:25]
twagner [crYOLO]
downloads:cryolo_1 [2020/02/13 14:01]
twagner [Installation]
Line 139: Line 139:
 </note> </note>
  
- +{{page>pipeline:window:cryolo:issues}}
-<note important> +
-**Known issues** +
- +
-  * Issue 0Training on multiple GPUs sometimes lead to worse performance (higher loss). We currently recommend to train on single gpus. +
-  * Issue 17On the fly filtering (%%--%%otf) is slower than using it not, as the filtering is not parallelized in this case.  +
- +
- +
- +
-<hidden Closed issues> +
-  * <del>  Issue 1: crYOLO sometimes not exit properly after training finished. Has to be killed manually.</del> +
-  * <del>Issue 2: If you use automatic filtering with .tif files, you get an error like "OSError: cannot identify image file 'filtered_folder/another_folder/my_image.tif'". It will be fixed in the next release.</del> +
-  * <del>Issue 3: (Boxmanager) The visualization only shows the first filament when loading eman1 helical box files (start end coordinates). Will be fixed in the next release.</del> +
-  * <del>Issue 4: The filament mode will crash if crYOLO cannot identify a single particle in the image. Will be fixed in 1.2.2</del> +
-  * <del>Issue 5: If movies were aligned with cisTEM and picked with crYOLO, the box position are vertically flipped. Will be fixed in 1.2.2</del> +
-  * <del>Issue 6: crYOLO does overwrite the environmental variable "CUDA_VISIBLE_DEVICES" with 0 if no gpu is specified by the -g parameter. This leads to the behavior that crYOLO ignores previous settings in CUDA_VISIBLE_DEVICES. Will be fixed in 1.2.2</del> +
-  * <del>Issue 7: On K3 images crYOLO seems to add a offset toward the longer axis of the input image.</del> +
-  * <del>Issue 8: There is a logical error in filament tracing, which sometimes connects two parallel filaments.</del> +
-  * <del>Issue 9: Some people report an error when running cryolo prediction/training"ImportError: numpy.core.multiarray failed to import". It will be fixed in 1.2.3.</del> +
-  * <del>Issue 10: On machines with many cores (e.g 64) an error during filtering might pop up: "[ERROR:0] 53: Can't spawn new thread"</del> +
-  * <del>Issue 11: If the -g parameter is not provided, crYOLO will use the memory of all GPUs. Will be fixed in 1.2.3.</del> +
-  * <del>Issue 12: The LineEnhancer depdenceny of crYOLO is still dependent from opencv. Workaround: In the crYOLO environment: conda install opencv</del> +
-  * <del>Issue 13: After picking it can happen that some of the boxes are not fully immersed in the image. Will be fixed in 1.2.4.</del> +
-  * <del>Issue 14: Parallelization in filament mode is broken. Will be fixed in 1.2.4.</del> +
-  * <del>Issue 15: If the %%--%%gpu_fraction is used, crYOLO always uses GPU 0. Will be fixed in 1.3.1.</del>  +
-  * <del>Issue 16: %%--%%gpu_fraction only works for prediction, not for training. Will be fixed in 1.3.2.</del> +
-  * <del>Issue 18: Prediction is broken in 1.3.2. It removes all particles as it claim they are not fully immersed in the image.</del> +
-  * <del>Issue 19: Filtering does not work if target image directory is absolute path.</del> +
-  * <del>Issue 20: crYOLO 1.3.4 has a normalization bug. During training the images are normalized seperately, but during prediction is done batch wise. Workaround: Use -pbs 1 during prediction. It will be fixed in 1.3.5.</del> +
-  * <del>Issue 21: The search range for filament tracing is too low for many datasets. To check if you are affected: Use your trained model and pick without the filament options. Check if your filaments a nicely picked (many consecutive boxes on a filament). In the next version, the search range will be increased and added as an optional parameter.</del> +
-  * <del>Issue 22: If absolute paths are used in the field "train_image" in your configuration file, filtering is skipped.</del> +
-  * <del>Issue 23: Since crYOLO 1.4.0 it sometimes take long until it starts picking. The reason seems to be the tensorflow update.<del> +
-  * <del>Issue 24: Fine-tune mode does not start (cannot find layer model_3). Will be fixed in 1.4.1.<del> +
-  * <del>Issue 25: When using GUI, prediction behaves differently than using command line. The reason is, that it uses a different multiprocessing start method. Will be fixed with 1.5.1</del> +
-  * <del>Issue 26: If you select filtering "None" crYOLO does not train properly.</del> +
-</hidden> +
-</note> +
 **That's it!** **That's it!**
  
downloads/cryolo_1.txt · Last modified: 2021/02/19 09:43 by twagner