shubham0204

#!/bin/bash

# Function to check if Python is installed
check_python_installed() {
    if command -v python3 &>/dev/null; then
        echo "Python is installed"
    else
        echo "Python is not installed. Please install Python 3 and try again."
        exit 1
    fi

shubham0204

import time
import psutil
import platform
from prometheus_client import start_http_server, Gauge, Counter, Info
import logging
import sys
import argparse
from typing import Dict, Any
import socket
from datetime import datetime

shubham0204

Address

Address Area

Address Building

Address City

Address Country

shubham0204

Certifications

Amazon Web Services

Badges - Getting Started

• Intro to Cloud Computing 101
• AWS EC2
• AWS Storage / S3
• AWS VPC

shubham0204

import streamlit as st
import cv2

vid = cv2.VideoCapture( 'http://<network_ip_Address>:8080/video' )

st.title( 'Using Mobile Camera with Streamlit' )
frame_window = st.image( [] )
take_picture_button = st.button( 'Take Picture' )

while True:

shubham0204

import streamlit as st
import cv2
import numpy as np
import requests

st.title( 'Mobile Camera Preview in Streamlit' )
frame_window = st.image( [] )
take_picture_button = st.button( 'Take Picture' )

while True:

shubham0204

while True:
    # Request the image from the server
    response = requests.get(url="http://<network_ip_address>:<port>/photo.jpg")
    imgNp = np.array(bytearray(response.content), dtype=np.uint8)
    frame = cv2.imdecode(imgNp, cv2.IMREAD_UNCHANGED ) 
    # As OpenCV decodes images in BGR format, we'd convert it to the RGB format
    frame = cv2.cvtColor( frame , cv2.COLOR_BGR2RGB )

    frame_window.image(frame)

shubham0204

import streamlit as st
import cv2
import numpy as np
import requests

# Title of the app
st.title( 'Mobile Camera Preview in Streamlit' )

# An empty image container that will hold the frames we'll fetch from the server
frame_window = st.image( [] )

shubham0204

Demystifying Mathematics - Shubham Panchal

• Kernels: Everything You Need to Know
• Principal Component Analysis: Everything You Need To Know
• Demystifying Monte Carlo Integration
• Demystifying Linear Independence
• Demystifying Probability Distributions ( 1 / 3 )
• Demystifying Probability Distributions ( 2 / 3 )
• [Demystifying Probability Distributions ( 3 / 3 )](https://www.canto

shubham0204

import random 

a = 0
b = 1
N = 1000

def f( x ):
    return 2 * x**5

def uniform():