Loader Container

Contains imageLoader and uAIMDataLoader for loading images and markups into caMicroscope.

Building

docker build -t camicroscope_loader .

Running

mkdir img
export CAMIC_IMAGES_DIR=$(echo $(pwd)/img)

export CAMIC_KUE_PORT=6000
export CAMIC_MARKUPLOADER_PORT=6001
export CAMIC_DATALOADER_PORT=6002

export dataloader_host=127.0.0.1 #IP address of data container
export annotations_host=127.0.0.1 #IP address of data container
export mongo_host=127.0.0.1 #IP address of data container
export mongo_port=27017

docker run -itd -p $CAMIC_KUE_PORT:3000 -p $CAMIC_MARKUPLOADER_PORT:3001 -p $CAMIC_DATALOADER_PORT:3002 -v $CAMIC_IMAGES_DIR:/data/images -e "dataloader_host=$(echo $dataloader_host)" -e "annotations_host=$(echo $annotations_host)" -e "mongo_host=$(echo $mongo_host)" -e "mongo_port=$(echo $mongo_port)"  camicroscope_loader

Dataloader API

Following examples assume <API_PORT>==32799

POST /submitData

curl -v -F id=TCGA-02-0001 -F upload=@TCGA-02-0001-01Z-00-DX1.83fce43e-42ac-4dcd-b156-2908e75f2e47.svs http://localhost:32799/submitData Return type: json On success returns: {"status":"success"}

GET /subjectIdExists

curl localhost:32799/subjectIdExists?SubjectUID=TCGA-02-0001 Returns an array with subjectID and file path. Empty array if subject Id doesnt exist

GET /getMD5ForImage

curl localhost:32799/getMD5ForImage?imageFileName=TCGA-02-0001-01Z-00-DX1.83fce43e-42ac-4dcd-b156-2908e75f2e47.svs Returns an array with MD5 of the image [{"md5sum":"418a0724b0a2113bcd2956bacae105b7"}]