One Paragraph of project description goes here
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
def load_dcm(img_path): | |
dcm = pydicom.read_file(img_path) | |
RescaleIntercept = int(dcm.data_element('RescaleIntercept').value) | |
return np.array(dcm.pixel_array,dtype=np.int16)+RescaleIntercept |
#!/bin/bash | |
### steps #### | |
# Verify the system has a cuda-capable gpu | |
# Download and install the nvidia cuda toolkit and cudnn | |
# Setup environmental variables | |
# Verify the installation | |
### | |
### to verify your gpu is cuda enable check |
// Get all users | |
var url = "http://localhost:8080/api/v1/users"; | |
var xhr = new XMLHttpRequest() | |
xhr.open('GET', url, true) | |
xhr.onload = function () { | |
var users = JSON.parse(xhr.responseText); | |
if (xhr.readyState == 4 && xhr.status == "200") { | |
console.table(users); | |
} else { | |
console.error(users); |
import pandas as pd | |
df = pd.DataFrame({'text': [str(i % 1000) for i in range(1000000)], | |
'numbers': range(1000000)}) | |
import pickle | |
import cPickle | |
import json | |
from functools import partial | |
from time import time |
People
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😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |