topaz preprocess --scale 8 --num-workers ## --pixel-sampling 200 --niters 100 --seed 1 --verbose -o /path/to/output/preprocessed/images/ /path/to/input/images/*.mrc
Create commands for pre-processing images (downsampling and normalization) for use in this Topaz picking GUI and for use in Topaz training.
Fill in parameters and run the resulting command         
topaz preprocess --scale 8 --num-workers ## --pixel-sampling 200 --niters 100 --seed 1 --verbose -o /path/to/output/preprocessed/images/ /path/to/input/images/*.mrc
"./"
indicates that the folder containing the topaz.html
application file also contains the images in this project. For example: /datasets/VOC2012/JPEGImages/
or C:\Documents\data\
(note the trailing /
and \
)Filename:
We recommend that you update the default path in
to the folder which contains this image.A temporary fix is to use
to manually locate and add this file. We do not recommend this approach because it requires you to repeat this process every time your load this project in the VIA application.topaz preprocess /full/path/to/mrcs/*.mrc -s [binning] -o /full/path/to/input/images/ -t [number_of_CPU_threads]
Topaz Version 0.0.0                                                             VIA Version 2.0.5
Topaz is a pipeline for particle detection in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples. The original research can be found here.
Topaz GUI uses VGG Image Annotator (VIA), which is an image annotation tool that can be used to define regions in an image and create textual descriptions of those regions. VIA is an open source project developed at the Visual Geometry Group and released under the BSD-2 clause license.
Here is a list of some salient features of the Topaz GUI version of VIA:
For more Topaz details, visit https://github.com/tbepler/topaz/.
For more VIA details, visit http://www.robots.ox.ac.uk/~vgg/software/via/.
VIA is Copyright © 2016-2018, Abhishek Dutta,Visual Geometry Group, Oxford University and VIA Contributors.
Quickstart Guide
1) To start picking,
• and regularly. You may later to continue.
• For further help, see the page.
1)
your Topaz particle picks as a CSV file and review the picks.Citation: Bepler, T., Morin, A., Brasch, J., Shapiro, L., Noble, A.J., Berger, B. (2018). Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. arXiv.
Create a command for training a network using particle picks.
Values you may want to change are bolded. Values you need to change are underlined. Values you may want to optimize are bold-italicized.
Scale factor: | |
Number of CPUs: | |
Pixel sampling: | |
Number of iterations: | |
Random seed: | |
Output folder: | |
Input micrographs: |
topaz train --train-images /path/to/preprocessed/images/ --train-targets /path/to/training_particles.csv --k-fold 5 --fold 0 --cross-validation-seed 42 --radius 4 --model resnet8 --units 32 --dropout 0.0 --bn on --pooling none --unit-scaling 1 --ngf 32 --method GE-binomial --autoencoder 0 --pi 0.035 --l2 0 --learning-rate 0.001 --minibatch-size 256 --minibatch-balance 1/16 --epoch-size 5000 --num-epochs 10 --num-workers ## --test-batch-size 1 --device 0 --save-prefix /path/to/model --output /path/to/unique/output/model.txt
Create commands for cross-validating parameters for optimization. This is an optional Topaz step.
Values you may want to change are bolded. Values you need to change are underlined. Values you may want to optimize are bold-italicized
Scale factor: | |
Number of CPUs: | |
Pixel sampling: | |
Number of iterations: | |
Random seed: | |
Output folder: | |
Input micrographs: |
topaz preprocess --scale 8 --num-workers ## --pixel-sampling 200 --niters 100 --seed 1 --verbose -o /path/to/output/preprocessed/images/ /path/to/input/images/*.mrc
Create commands for extracting picks.
Values you may want to change are bolded. Values you need to change are underlined.
Scale factor: | |
Number of CPUs: | |
Pixel sampling: | |
Number of iterations: | |
Random seed: | |
Output folder: | |
Input micrographs: |
topaz preprocess --scale 8 --num-workers ## --pixel-sampling 200 --niters 100 --seed 1 --verbose -o /path/to/output/preprocessed/images/ /path/to/input/images/*.mrc