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pipeline:window:cryolo [2019/09/13 09:49] twagner [Installation] |
pipeline:window:cryolo [2019/09/14 10:22] twagner [Picking] |
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You can find the download and installation instructions here: [[howto: | You can find the download and installation instructions here: [[howto: | ||
- | ===== General description | + | ===== Tutorials |
+ | |||
+ | Depending what you want to do, you can follow one of these Tutorials: | ||
+ | |||
+ | - I would like to train a model from scratch for picking my particles | ||
+ | - I would like to train a model from scratch for picking filaments. | ||
+ | - I would like to refine a general model for my particles. | ||
+ | |||
+ | The **first and the second tutorial** are the most common use cases and well tested. The **third tutorial** is still experimental but might give you better results in less time or less training data. | ||
+ | |||
+ | |||
===== Picking particles - Using a model trained for your data ===== | ===== Picking particles - Using a model trained for your data ===== | ||
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One may ask how many micrographs have to be picked? It depends! Typically 10 micrographs are a good start. However, that number may increase / decrease due to several factors: | One may ask how many micrographs have to be picked? It depends! Typically 10 micrographs are a good start. However, that number may increase / decrease due to several factors: | ||
* A very heterogenous background could make it necessary to pick more micrographs. | * A very heterogenous background could make it necessary to pick more micrographs. | ||
+ | * When you refine a general model, you might need to pick less micrographs. | ||
* If your micrograph is only sparsely decorated, you may need to pick more micrographs. | * If your micrograph is only sparsely decorated, you may need to pick more micrographs. | ||
- | We recommend that you start with 10 micrographs, | + | |
+ | We recommend that you start with 10 micrographs, | ||
{{: | {{: | ||
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Now create a third folder with the name '' | Now create a third folder with the name '' | ||
+ | |||
+ | ==== Start crYOLO ==== | ||
+ | {{page> | ||
==== Configuration ==== | ==== Configuration ==== | ||
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**Alternative: | **Alternative: | ||
- | Since crYOLO 1.4 you can also use neural network denoising with [[: | + | Since crYOLO 1.4 you can also use neural network denoising with [[: |
To use JANNI' | To use JANNI' | ||
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to the training command. | to the training command. | ||
==== Picking ==== | ==== Picking ==== | ||
- | You can now use the model weights saved in '' | + | {{page>pipeline: |
- | < | + | |
- | cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ | + | |
- | </code> | + | |
- | 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: | ||
- | < | ||
- | cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ -t 0.2 | ||
- | </ | ||
- | However, it is much easier to select the best threshold after picking using the '' | ||
==== Visualize the results ==== | ==== Visualize the results ==== | ||
- | + | {{page>pipeline: | |
- | To visualize your results you can use the box manager: | + | |
- | < | + | |
- | cryolo_boxmanager.py | + | |
- | </ | + | |
- | Now press //File -> Open image// folder and the select the '' | + | |
- | + | ||
- | Since version 1.3.0 crYOLO writes cbox files in a separate '' | + | |
- | + | ||
- | [{{ :pipeline: | + | |
- | + | ||
- | <note warning> | + | |
- | Right now, **this filtering does not yet work for filaments**. | + | |
- | </ | + | |
- | + | ||
- | + | ||
===== 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: [[: | 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: [[: | ||
Our general models can be found and downloaded here: [[howto: | Our general models can be found and downloaded here: [[howto: | ||
+ | |||
+ | ==== Start crYOLO ==== | ||
+ | {{page> | ||
+ | |||
==== 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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==== Picking ==== | ==== Picking ==== | ||
- | Just follow the description given [[pipeline: | + | {{page>pipeline: |
- | + | ||
- | As for a direct trained model, you might want to play around with the confidence threshold, either by using the '' | + | |
+ | ==== Visualize the results ==== | ||
+ | {{page> | ||
===== Picking particles - Using the general model refined for your data ===== | ===== Picking particles - Using the general model refined for your data ===== | ||
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</ | </ | ||
==== Picking ==== | ==== Picking ==== | ||
- | Picking is identical as with a model trained from scratch, so we will skip it here. Just follow the description given [[pipeline: | + | {{page>pipeline: |
==== Training on CPU ==== | ==== Training on CPU ==== |