cryolo_reference_example

This version (2020/05/08 14:29) was approved by twagner.The Previously approved version (2019/09/23 09:28) is available.

# crYOLO reference example

Here we provide quick run through example for training and picking with crYOLO. The main purpose is to check if your setup is running as expected. I will not provide detailed explanations in this text. Please note that there is a detailed tutorial.

We run this example on a machine with the following specification:

• Titan V
• Intel Core i9 7920X @ 2.90 Ghz
• SSD Harddrive
• crYOLO 1.5.0

You can download the reference data (TcdA1) here:

Then unzip the data:

unzip toxin_reference.zip -d toxin_reference/
cd toxin_reference

The toxin_reference directory contains multiple folders / files:

• train_image: Folder with 12 training images
• train_annot: Folder with 12 box files for the training images
• config_phosnet.json: Configuration file for crYOLO
• reference_model.h5: Model that I've trained on my machine using the commands below.
• reference_results: Picked particles using my machine and the reference model.

Before you start training / picking please activate your environment:

source activate cryolo

The training is done with this command:

cryolo_train.py -c config_phosnet.json -w 5 -e 5 -g 0

crYOLO needs 5 minutes 50 seconds to converge (5 warmup + 10 “normal” epochs). The best validation loss was 0.03042. These numbers might be a little bit different on your case.

cryolo_predict.py -c config_phosnet.json -w model.h5 -i unseen_examples/ -o my_results

It picked 1617 particles on 12 micrographs in 3 seconds. Including filtering the image and loading the model the command needed 38 seconds.

cryolo_boxmanager.py -i unseen_examples/ -b my_results/CBOX/
• cryolo_reference_example.txt