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pipeline:window:cryolo [2019/03/18 14:58] twagner [Picking particles - Without training using a general model] |
pipeline:window:cryolo [2019/07/09 21:00] twagner [Data preparation] |
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* crYOLO makes picking **smart** -- The network learns the context of particles (e.g. not to pick particles on carbon or within ice contamination ) | * crYOLO makes picking **smart** -- The network learns the context of particles (e.g. not to pick particles on carbon or within ice contamination ) | ||
* crYOLO makes training **easy** -- You might use a general network model and skip training completely. However, if the general model doesn' | * crYOLO makes training **easy** -- You might use a general network model and skip training completely. However, if the general model doesn' | ||
- | * crYOLO makes training **lenient** -- Don't worry if you miss quite a lot particles during creation of your training set. [[: | + | * crYOLO makes training **tolerant** -- Don't worry if you miss quite a lot particles during creation of your training set. [[: |
In this tutorial we explain our recommended configurations for single particle and filament projects. You can find more information about supported networks and about the config file in the following articles: | In this tutorial we explain our recommended configurations for single particle and filament projects. You can find more information about supported networks and about the config file in the following articles: | ||
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==== Data preparation ==== | ==== Data preparation ==== | ||
CrYOLO supports MRC, TIF and JPG files. It can work with 32 bit data, 8 bit data and 16 bit data. | CrYOLO supports MRC, TIF and JPG files. It can work with 32 bit data, 8 bit data and 16 bit data. | ||
- | It will work on original MRC files, but it will probably improve when the data are filtered. Therefore you should low-pass filter them to a reasonable level. Since Version 1.2 crYOLO can automatically do that for you. You just have to add | + | It will work on original MRC files, but it will probably improve when the data are denoised. Therefore you should low-pass filter them to a reasonable level. Since Version 1.2 crYOLO can automatically do that for you. You just have to add |
< | < | ||
" | " | ||
</ | </ | ||
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to the model section in your config file to filter your images down to an absolute frequency of 0.1. The filtered images are saved in folder '' | to the model section in your config file to filter your images down to an absolute frequency of 0.1. The filtered images are saved in folder '' | ||
+ | |||
+ | <hidden Alternative: | ||
+ | < | ||
+ | " | ||
+ | </ | ||
+ | </ | ||
+ | |||
If you followed the installation instructions, | If you followed the installation instructions, | ||
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Create a new directory called '' | Create a new directory called '' | ||
- | Now create a third folder with the name '' | + | Now create a third folder with the name '' |
==== Configuration ==== | ==== Configuration ==== | ||
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" | " | ||
" | " | ||
- | " | + | " |
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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/ | ||
</ | </ | ||
- | You will find the picked particles in the directory '' | + | You will find the picked particles in the directory '' |
If you want to pick less conservatively or more conservatively you might want to change the selection threshold from the default of 0.3 to a less conservative value like 0.2 or more conservative value like 0.4 using the //-t// parameter: | If you want to pick less conservatively or more conservatively you might want to change the selection threshold from the default of 0.3 to a less conservative value like 0.2 or more conservative value like 0.4 using the //-t// parameter: | ||
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===== Picking particles - Without training using a general model ===== | ===== Picking particles - Without training using a general model ===== | ||
+ | Here you can find how to apply the general models we trained for you. If you would like to train your own general model, please see our extra wiki page: [[: | ||
- | The general models can be found and downloaded here: [[howto: | + | Our general models can be found and downloaded here: [[howto: |
==== Configuration==== | ==== Configuration==== | ||
The next step is to create a configuration file. Type: | The next step is to create a configuration file. Type: | ||
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==== Training ==== | ==== Training ==== | ||
- | In comparision to the training from scratch, you can skip the warm up training. Moreover you have to add the // | + | In comparision to the training from scratch, you can skip the warm up training. Moreover you have to add the //%%--%%fine_tune// flag: |
< | < | ||
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==== Configuration ==== | ==== Configuration ==== | ||
- | You can configure it the same way as for a " | + | You can configure it the same way as for a " |
<code json config.json> | <code json config.json> | ||
{ | { | ||
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}, | }, | ||
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} | } | ||
</ | </ | ||
+ | |||
// | // | ||
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* // | * // | ||
* // | * // | ||
+ | * //-sr SEARCH_RANGE_FACTOR//: | ||
===== Help ===== | ===== Help ===== |