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pipeline:window:cryolo [2018/12/24 11:21] twagner [Configuration] |
pipeline:window:cryolo [2019/02/26 08:13] twagner [Configuration] |
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For this tutorial, we assume that you have either a single GPU or want to use GPU 0. Therefore we add '-g 0' after each command below. However, if you have multiple (e.g GPU 0 and GPU 1) you could also use both by adding '-g 0 1' after each command. | For this tutorial, we assume that you have either a single GPU or want to use GPU 0. Therefore we add '-g 0' after each command below. However, if you have multiple (e.g GPU 0 and GPU 1) you could also use both by adding '-g 0 1' after each command. | ||
- | Navigate to the folder with config.json file, train_image folder, etc. | + | Navigate to the folder with '' |
**1. Warm up your network** | **1. Warm up your network** | ||
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to the training command. | to the training command. | ||
==== Picking ==== | ==== Picking ==== | ||
- | You can now use the model weights saved in '' | + | You can now use the model weights saved in '' |
< | < | ||
cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ | cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ | ||
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cryolo_boxmanager.py | cryolo_boxmanager.py | ||
</ | </ | ||
- | Now press //File -> Open image// folder and the select the '' | + | Now press //File -> Open image// folder and the select the '' |
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Open the file with your preferred editor. | Open the file with your preferred editor. | ||
- | For the general **[[: | + | There are two general **[[: |
+ | === CryoEM images === | ||
+ | For the general **[[: | ||
<code json config.json> | <code json config.json> | ||
{ | { | ||
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" | " | ||
" | " | ||
+ | } | ||
+ | } | ||
+ | </ | ||
+ | Please set the value in the //" | ||
+ | |||
+ | === Negative stain images === | ||
+ | For the general model for **negative stain data** please use: | ||
+ | <code json config.json> | ||
+ | { | ||
+ | " | ||
+ | " | ||
+ | " | ||
+ | " | ||
+ | " | ||
+ | " | ||
+ | } | ||
} | } | ||
</ | </ | ||
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After this is done, you have to prepare training data for your model. | After this is done, you have to prepare training data for your model. | ||
- | Right now, you have to use the e2helixboxer.py to generate the training data: | + | Right now, you have to use the sxhelixboxer.py to generate the training data: |
< | < | ||
- | e2helixboxer.py --gui my_images/ | + | sxhelixboxer.py --gui my_images/ |
</ | </ | ||
- | After tracing your training data in e2helixboxer, export them using //File -> Save//. Make sure that you export particle coordinates as this the only format supported right now (see screenshot). In the following example, it is expected that you exported into a folder called " | + | After tracing your training data in sxhelixboxer, export them using //File -> Save//. Make sure that you export particle coordinates as this the only format supported right now (see screenshot). In the following example, it is expected that you exported into a folder called " |
==== Configuration ==== | ==== Configuration ==== |