Host juwels
HostName juwels.fz-juelich.de
User salaj1
IdentityFile ~/.ssh/id_rsa_juwels.pub
To connect simply ssh juwels
.
import os | |
import cv2 | |
dir_files = os.listdir('raw_data') | |
extensions = [filename[-4:] for filename in dir_files] | |
for ext in extensions: | |
assert ext == '.jpg' | |
max_width = 0 |
import json | |
import sys | |
import os | |
folders = [] | |
files = [] | |
RESULT_KEY = 'test_per' | |
data = { | |
'subdir1': [], | |
'subdir2': [], |
#!/usr/bin/python | |
#!/usr/bin/python | |
# Answer to this: | |
# https://stackoverflow.com/questions/53442614/conways-game-of-life-in-python-3-with-matplotlib-problem-with-displaying-a-fo#53442614 | |
# call with: python3 cgl.py 10 500 1 1 | |
import os | |
import argparse | |
import numpy as np |
import nltk | |
from nltk.parse.generate import generate | |
# Define Reber grammar | |
# http://christianherta.de/lehre/dataScience/machineLearning/neuralNetworks/pics/embeddedReberGrammar.png | |
grammarStr = ''' | |
START -> 'B' 'T' REBER 'T' 'E' | 'B' 'P' REBER 'P' 'E' | |
REBER -> 'B' E1 | |
E1 -> 'T' E2 | 'P' E3 |
import cv2 | |
import numpy as np | |
print(cv2.__version__) | |
vidcap = cv2.VideoCapture('vid.mp4') | |
success,image = vidcap.read() | |
count = 0 | |
success = True | |
frames = [] | |
while success: | |
frames.append(image) |
# install Anaconda to control the environment: https://www.anaconda.com/distribution/#linux | |
wget https://repo.anaconda.com/archive/Anaconda3-2018.12-Linux-x86_64.sh | |
chmod +x Anaconda3-2018.12-Linux-x86_64.sh | |
./Anaconda3-2018.12-Linux-x86_64.sh | |
# answer to the installation prompts | |
# activate environment and install the required libraries | |
conda create -n vid2frame | |
conda activate vid2frame | |
conda install opencv scipy |
# # First create and activate conda python3 environment: | |
# conda create -n video python=3.6 | |
# conda activate video | |
# # Then install the requirements: | |
# conda install ffmpeg | |
# conda install tensorflow-gpu==1.13.1 | |
# pip install tensorflow_datasets | |
# # The bellow code would still produce an error because of the missing file ("ucf101_labels.txt") | |
# # So manually download the "ucf101_labels.txt" and put it in place: | |
# cd "/home/$USER/anaconda3/envs/video/lib/python3.6/site-packages/tensorflow_datasets/video/" |
def find_onset_offset(y, threshold): | |
""" | |
Given the input signal `y` with samples, | |
find the indices where `y` increases and descreases through the value `threshold`. | |
Return stacked binary arrays of shape `y` indicating onset and offset threshold crossings. | |
`y` must be 1-D numpy arrays. | |
""" | |
if threshold == 1: | |
equal = y == threshold | |
transition_touch = np.where(equal)[0] |
# Steps for setting up python jupyter notebook for editing over SSH | |
# this is not a runnable script as different commands need to be executed on different machines | |
# ON REMOTE MACHINE | |
ssh username@remotepc123 | |
# make sure the jupyter is installed | |
pip install jupyter | |
# start jupyter on specified port and no-browser mode | |
jupyter notebook --no-browser --port=8080 | |
# copy the url with token that looks something like this: |