How to display reasonable output from a RCNN in JS
Kevin Mader kmader
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| from glob import glob | |
| import os | |
| cur_glob = '/Volumes/NO NAME/*seg.nii' | |
| files_to_process = glob(cur_glob) | |
| print('Processing', len(files_to_process), 'files') | |
| def process_file(in_path): | |
| slicer.mrmlScene.Clear(0) | |
| [success, loadedVolumeNode] = slicer.util.loadVolume(in_path, returnNode=True) | |
| outputLabelMap = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLLabelMapVolumeNode') | |
| vol_logic = slicer.modules.volumes.logic() |
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| <html> | |
| <head> | |
| <meta HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=UTF-8"> | |
| <title>Thebe Lab examples</title> | |
| <link rel="stylesheet" type="text/css" href="index.css" /> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"> | |
| </script> | |
| <!-- Configure and load Thebe !--> |
kmader
/ ImageEnhancementPlayground.ipynb
Created
March 7, 2018 11:24
Using IPywidgets and Matplotlib Together
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kmader
/ AnalysisSubmitTool.ipynb
Created
October 20, 2017 10:12
A simple Dash and Luigi Job Submission Tool
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kmader
/ R Snippet for reading dicom headers
Created
August 17, 2017 13:00
Read Dicom Headers in KNIME
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| library(tidyverse) | |
| library(oro.dicom) | |
| knime.in$Location %>% | |
| plyr::ldply(function(in_path) { | |
| readDICOMFile(as.character(in_path), pixelData = F)$hdr %>% | |
| group_by(name) %>% summarize_all(funs(first)) %>% # remove duplicate names | |
| select(name, value) %>% spread(name, value) %>% # reformat as a table | |
| head(1) | |
| } | |
| ) -> all_header |
kmader
/ material_switch.css
Last active
July 26, 2017 10:20
Here is a collection of useful CSS files that I 'host' on gist for use in dash-apps
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| .material-switch > input[type="checkbox"] { | |
| display: none; | |
| } | |
| .material-switch > label { | |
| cursor: pointer; | |
| height: 0px; | |
| position: relative; | |
| width: 40px; | |
| } |
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Often it is important to change a core configuration setting in pyspark before running (like a serializer, PYTHONHASHSEED for python3 users, or
from pyspark import SparkContext
from pyspark.serializers import PickleSerializer
new_conf = sc._conf.setExecutorEnv('PYTHONHASHSEED', '1234')
sc.stop()
sc = pyspark.SparkContext(conf = new_conf, serializer = PickleSerializer())