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@vibragiel
vibragiel / screenshare
Last active September 9, 2015 11:13
Script to grab a screenshot, put it in a Dropbox directory and copy its public link into the clipboard. Modified from https://gist.github.com/Saicheg/4231551
#!/bin/bash
# Usage: screenshare [-m <window|area|desktop>] [-d <integer>] [-p]
# -m window Grab active window
# -m area Grab an area selected with the mouse
# -m desktop Grab whole desktop
# -d <integer> Grab after the specified delay in seconds
# -p Include mouse pointer in the screenshot
# Description: Take a screenshot, store it in Dropbox and copy public link
# into the clipboard
# Author: Gabriel Rodríguez Alberich
@alimuldal
alimuldal / dunn.py
Last active October 5, 2023 06:04
Implementation of Dunn's multiple comparison test, following a Kruskal-Wallis 1-way ANOVA
import numpy as np
from scipy import stats
from itertools import combinations
from statsmodels.stats.multitest import multipletests
from statsmodels.stats.libqsturng import psturng
import warnings
def kw_dunn(groups, to_compare=None, alpha=0.05, method='bonf'):
"""
@alimuldal
alimuldal / nemenyi.py
Last active May 25, 2020 09:39
Implementation of Nemenyi's multiple comparison test, following a Kruskal-Wallis 1-way ANOVA
import numpy as np
from scipy import stats
from itertools import combinations
from statsmodels.stats.multitest import multipletests
from statsmodels.stats.libqsturng import psturng
import warnings
def kw_nemenyi(groups, to_compare=None, alpha=0.05, method='tukey'):
"""
@karpathy
karpathy / min-char-rnn.py
Last active April 1, 2025 06:02
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
@thoolihan
thoolihan / install_tensorflow_centos7.sh
Last active January 28, 2019 06:17
Install TensorFlow on CentOS7
sudo yum -y install epel-release
sudo yum -y install gcc gcc-c++ python-pip python-devel atlas atlas-devel gcc-gfortran openssl-devel libffi-devel
# use pip or pip3 as you prefer for python or python3
pip install --upgrade virtualenv
virtualenv --system-site-packages ~/venvs/tensorflow
source ~/venvs/tensorflow/bin/activate
pip install --upgrade numpy scipy wheel cryptography #optional
pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0rc0-cp35-cp35m-linux_x86_64.whl
# or below if you want gpu, support, but cuda and cudnn are required, see docs for more install instructions
pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0rc0-cp35-cp35m-linux_x86_64.whl
from click import command, option, Option, UsageError
class MutuallyExclusiveOption(Option):
mutex_groups = {}
def __init__(self, *args, **kwargs):
opts_list = kwargs.pop('mutex_group', "")
self.mutex_group_key = ','.join(opts_list)
self.mutex_groups[self.mutex_group_key] = 0
help = kwargs.get('help', '')
@giannisp
giannisp / gist:ebaca117ac9e44231421f04e7796d5ca
Last active July 14, 2024 18:27
Upgrade PostgreSQL 9.6.5 to 10.0 using Homebrew (macOS)
After automatically updating Postgres to 10.0 via Homebrew, the pg_ctl start command didn't work.
The error was "The data directory was initialized by PostgreSQL version 9.6, which is not compatible with this version 10.0."
Database files have to be updated before starting the server, here are the steps that had to be followed:
# need to have both 9.6.x and latest 10.0 installed, and keep 10.0 as default
brew unlink postgresql
brew install [email protected]
brew unlink [email protected]
brew link postgresql
#! /usr/bin/env python3
import cv2
import numpy as np
from pathlib import Path
import argparse
###############################################################################
# CONSTANTS
DEBUG = False
@emillykkejensen
emillykkejensen / MultiLabel_MultiClass_TextClassification_with_BERT_Transformer_and_Keras.py
Created August 21, 2020 10:23
Multi-Label, Multi-Class Text Classification with BERT, Transformer and Keras
#######################################
### -------- Load libraries ------- ###
# Load Huggingface transformers
from transformers import TFBertModel, BertConfig, BertTokenizerFast
# Then what you need from tensorflow.keras
from tensorflow.keras.layers import Input, Dropout, Dense
from tensorflow.keras.models import Model
from tensorflow.keras.optimizers import Adam
#pip install git+https://github.com/huggingface/transformers.git
import datetime
import sys
from transformers import pipeline
from transformers.pipelines.audio_utils import ffmpeg_microphone_live
pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=0)
sampling_rate = pipe.feature_extractor.sampling_rate