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pipeline:window:cryolo [2018/12/24 11:21] twagner [Configuration] |
pipeline:window:cryolo [2019/02/13 17:46] twagner [Data preparation] |
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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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" | " | ||
" | " | ||
+ | } | ||
} | } | ||
</ | </ | ||
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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/ |
</ | </ | ||