Malaria Classification Pipeline Of Microscopy Slides
Malaria Classification model execution in Nvidia Clara deploy
This is not for clinical use and should NOT be used for diagnostics purposes.
I will be using the Nvidia Clara Deploy to run a Nvidia GPU Cloud(NGC) model for classification of malaria in microscopy slides converted into png files.
The docker container for the model is in https://ngc.nvidia.com/catalog/containers/nvidia:clara:ai-malaria
As per above url, The network architecture used to train this model is based on the 2015 academic publication “Deep Residual Learning for Image Recognition” by He et. al.
I will be following this link to run a clara pipeline to classify microscopy slides. https://ngc.nvidia.com/catalog/resources/nvidia:clara:clara_ai_malaria_pipeline
I will use a clara deploy SDK running on AWS g4dn.xlarge instance. The description of how to install clara deploy on an AWS instance is in another post.
My running clara instance as shown by the running helm charts
Create a pipeline directory if you don’t have it already
mkdir -p ~/.clara/pipelines
Make sure you are connected to nvcr.io
Pull the malaria classification pipeline
Inspect the directory and unzip the input file to get the input images
This will create an input directory containing the png images to be classified
Unzip the model and related files in a common model directory. Create the /clara/common/models directory if you don’t have it created already
Create a pipeline utilizing the pipeline yaml file given. Inspect the pipeline yaml file, which builds a docker container as given in https://ngc.nvidia.com/catalog/containers/nvidia:clara:ai-malaria
Create a pipeline job for the pipeline we just created utilizing the input images to be classified as input
clara create jobs -n malaria-test -p 8f315a0453c6416bbca18bdff457ee26 -f ~/.clara/pipelines/clara_ai_malaria_pipeline/input/png
Start the job
Check the job status in Clara console using localhost:32002
You may download the output to look at the classified images locally. A stamp on the left corner of the classified out images will indicate a true (`T’) or false (`F`) classification for malaria.
You may also use Clara download to download the output in a directory
clara download 602d2d58adbe4476918d9fd73daa7768:/operators/ai-app-malaria/* /etc/clara/experiments/covidtest
Use `eog` to look at the output inference files
There you have it malaria inference using Clara deploy pipeline