zabir-nabil

import cv2
import numpy as np
import sys

img = cv2.imread('1.jpg')
print(sys.getsizeof(img))
img_encoded = cv2.imencode('.jpg', img)[1]
print(sys.getsizeof(img_encoded))

img_bytes = img_encoded.tobytes()  # bytes class

zabir-nabil

# author: github.com/zabir-nabil

import librosa
from pydub import AudioSegment
import pydub
import os

def segment_aud_eq(audio_segment, k):
    # k denotes, seconds * 1000
    a_segs = [audio_segment[i*k:min((i+1)*k, len(audio_segment)-1)] for i in range(len(audio_segment)//k)]

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from selenium import webdriver
from bs4 import BeautifulSoup
from selenium.webdriver.chrome.options import Options
chrome_options = Options()
chrome_options.add_argument("--headless")
chrome_options.add_argument('--no-sandbox')
driver = webdriver.Chrome('/usr/bin/chromedriver', options=chrome_options)

ips = open("ip.txt", "r")
keywords = ["login", "denied", "username", "password", "Apache2"]

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Deploying free email server, web hosting panel with CyberPanel on subdomain
Summary:
Let's say we have a domain "test.com". We want to install an email server for our domain, we want it free.

First make sure the droplet has no app running on port 80, 443 (or nginx, apache websites).

Install CyberPanel,
on DO, https://marketplace.digitalocean.com/apps/cyberpanel
sh <(curl https://cyberpanel.net/install.sh || wget -O - https://cyberpanel.net/install.sh)

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Location,Country,Country_Code_Alpha_2,Lat,Long
A Cañiza,Spain,ES,42.216671,-8.26667
A Coruña,Spain,ES,43.371349,-8.396
A Coruña,Spain,ES,43.371262,-8.4188
A Dos Cunhados,Portugal,PT,39.156479,-9.32206
A Dos Francos,Portugal,PT,39.314468,-9.04547
A Estrada,Spain,ES,42.683331,-8.48333
A Guarda,Spain,ES,41.90131,-8.87423
A Guarda,Spain,ES,41.90403,-8.87225
A Mezquita,Spain,ES,42.013142,-7.04675

zabir-nabil

from model_ecapatdnn import ECAPAModel
import soundfile as sf
import torch

# load your pytorch model (+ weights) here
model_1 = ECAPAModel.ECAPAModel(lr = 0.001, lr_decay = 0.97, C = 1024, n_class = 18505, m = 0.2, s = 30, test_step = 3, gpu = -1)
model_1.load_parameters("/ecapatdnn/exps/finetuned/model/model_0028.model")

model = model_1.speaker_encoder # module with forward implemented
# if your forward function contains any arguments other than the input tensors, make sure to add default values

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# python triton client

import numpy as np
import sys

import tritonclient.grpc as grpcclient


try:
    keepalive_options = grpcclient.KeepAliveOptions(

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do-release-upgrade

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# Speaker Experiments and MLflow

Speaker experiments take relatively long time to finish. For tracking the experiment progress, we can utilize MLflow.

### What is MLflow?

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are:

 * MLflow Tracking: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.
 * MLflow Projects: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others.

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MetaMap Installation Tutorial

MetaMap is a tool developed by the National Library of Medicine for analyzing biomedical texts. Follow these steps to install and set up MetaMap on a Linux system.

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Prerequisites

1. Java Installation:
   • Ensure Java is installed: