pangyuteng

  Dell Poweredge R720
  Nvidia Tesla P40 24GB 
  GPU pass-through via Proxmox

psu

? am using only one 1100w psu, the other 1100w is not plugged in.

  script:
    - echo hello cicd
  rules:
    - if: "($CI_PIPELINE_SOURCE == 'pipeline' || $CI_PIPELINE_SOURCE == 'web') && $CI_COMMIT_TAG != null && $CI_COMMIT_BRANCH == 'main' "

since above rule with CI_COMMIT_TAG is only triggered when tag is pushed to gitlab, one can use the below

if you want to submit parallel jobs with condor_submit:

condor.sub

universe = docker
docker_image = {{docker_url}}
docker_pull_policy = always
executable = {{bash_filename}}
should_transfer_files = YES
transfer_input_files = {{bash_filename}}

So how do you split multi frame to single frame dicom images?


First you should google the current top results in google
keywords I used: "split dicom multiframe to single frame"
If you don't like the results you can check the below related links:

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<style>

	div.lazy {
	width: 700px;
	height: 467px;
	background: #f2dede;
	color: #a94442;

	FROM python:3.8-slim-buster

	RUN apt-get update && apt-get -y install cron

	# Copy hello-cron file to the cron.d directory
	COPY hello-cron /etc/cron.d/hello-cron

	# Give execution rights on the cron job
	RUN chmod 0644 /etc/cron.d/hello-cron

	#
	# gattia commented on Apr 6, 2018
	# https://github.com/keras-team/keras/issues/9395#issuecomment-379276452
	#

	import tensorflow as tf
	from tensorflow import keras
	import tensorflow.keras.backend as K

	def dice_coef(y_true, y_pred, smooth=1e-7):

	keras_model.h5
	tf_model
	model.onnx
	updated_tf_model
	updated_keras_model.h5

	FROM ubuntu:latest
	RUN apt-get update;apt-get install acl -yq

	FROM python:3.8-bullseye
	COPY requirements.txt /tmp/requirements.txt
	RUN pip install -r /tmp/requirements.txt