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Filename: cdeep3m/view_cdeep3m_result_display.php

Line Number: 60

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File: /var/www/html/application/views/cdeep3m/view_cdeep3m_result_display.php
Line: 60
Function: _error_handler

File: /var/www/html/application/controllers/Cdeep3m_result.php
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Function: view

File: /var/www/html/index.php
Line: 315
Function: require_once

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Go to CDeep3M homepage

Launch CDeep3M using Docker



Step 1) Install Docker
https://docs.docker.com/install/

Step 2) Pull the CDeep3M image
docker pull ncmir/cdeep3m

Step 3) Launch the docker container
docker run -it --network=host --gpus all --entrypoint /bin/bash ncmir/cdeep3m

Step 4) Download image:
wget https://cildata.crbs.ucsd.edu/media/images/50451/50451_bin1.mrc

Step 5) Create the input image folder:
mkdir tifs

Step 6) Convert the mrc file to TIFF images:
mrc2tif 50451_bin1.mrc tifs/image

Step 7) Download the trained model file:
wget https://doi.org/10.7295/W9CDEEP3M3

Step 8) Untar the model file:
tar -xvf $MODEL_FILE

Step 9) Run the prediction process
runprediction.sh --augspeed 1 --models 1fm $MODEL_FOLDER $IMAGE_FOLDER ~/predictions
Launch CDeep3M using Singularity

Step 1) Install Singularity
https://sylabs.io/docs/

Step 2) Download Singularity image file
wget https://doi.org/10.7295/W9CDEEP3M_SINGULARITY

Step 3) Launch the Singularity container
singularity shell --nv cdeep3m-docker.simg

Step 4) Download image:
wget https://cildata.crbs.ucsd.edu/media/images/50451/50451_bin1.mrc

Step 5) Create the input image folder:
mkdir tifs

Step 6) Convert the mrc file to TIFF images:
mrc2tif 50451_bin1.mrc tifs/image

Step 7) Download the trained model file:
wget https://doi.org/10.7295/W9CDEEP3M3

Step 8) Untar the model file:
tar -xvf $MODEL_FILE

Step 9) Run the prediction process
runprediction.sh --augspeed 1 --models 1fm $MODEL_FOLDER $IMAGE_FOLDER ~/predictions
Launch CDeep3M on the AWS cloud
Launch Deep3m AWS CloudFormation link

Step 1) Launch the docker container on AWS
docker run -it --network=host --gpus all --entrypoint /bin/bash ncmir/cdeep3m

Step 2) Download the trained model file:
wget https://doi.org/10.7295/W9CDEEP3M3

Step 3) Untar the model file:
tar -xvf $MODEL_FILE

Step 4) Download image:
wget https://cildata.crbs.ucsd.edu/media/images/50451/50451_bin1.mrc

Step 5) Create the input image folder:
mkdir tifs

Step 6) Convert the mrc file to TIFF images:
mrc2tif 50451_bin1.mrc tifs/image

Step 7) Run the prediction process
runprediction.sh --augspeed 1 --models 1fm $MODEL_FOLDER $IMAGE_FOLDER ~/predictions
CDeep3M-Colab Prediction GUI
Run CDeep3M predictions with a graphical user interface (GUI) on Google Colab's free GPUs.

CDeep3M-Colab CLI
If you are comfortable using a command line interface, this provides the most flexible way to use all functionality of CDeep3M while using Googles free GPUs. It performs the complete CDeep3M installation and sets you up with the CDeep3M CLI on colab.