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// Find the video element that is supposed to play the stream
const videoElement = document.querySelector('video');

if (videoElement) {
  const stream = videoElement.srcObject;

  // Check if the stream is available and active
  if (stream instanceof MediaStream && stream.active) {
    // Get video tracks from the stream
    const videoTracks = stream.getVideoTracks();

imneonizer

AI Application Development Specialisation in Computer Vision

This course navigates students through the exciting realm of AI, spotlighting Computer Vision applications. Starting from Python programming and Git, it smoothly transitions into developing AI applications using Docker and OpenCV. Assignments each week provide hands-on experience, cementing the key learnings.

Week 1: Grasping the Basics- Python and Git

Topics

• Python Programming: Understand syntax, variables, loops, conditionals, lists, tuples, and dictionaries
• Starting with Git: Learn to clone, commit, branch, and merge

imneonizer

{
  "editor.formatOnSave": true,
  "python.formatting.provider": "black",
  "python.formatting.blackPath": "<path-to-black-formatter>"
}

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version: "3.8"

services:
  app:
    image: nvidia/cuda:11.6.2-base-ubuntu20.04
    command: nvidia-smi
    deploy:
      resources:
        reservations:
          devices:

imneonizer

import asyncio
import fractions
import logging
import threading
import time
from typing import Optional, Set, Tuple
import av
from av import AudioFrame, VideoFrame

from aiortc.mediastreams import AUDIO_PTIME, MediaStreamError, MediaStreamTrack

imneonizer

Install aria2c:

sudo apt install aria2 -y

Use below command to utilize full bandwidth:

aria2c --file-allocation=none -c -x 10 -s 10 -d "mydir" URL --check-certificate=false

-c allows continuation of download if it gets interrupted, -x 10 and -s 10 allow up to 10 connections per server, and -d "mydir" outputs file to directory mydir.

imneonizer

import torch
import torchvision
from torchvision import transforms
from torch.utils.data import DataLoader

data_path = './Archive_jpg/'

transform_img = transforms.Compose([
    transforms.Resize((480, 640)),
    # transforms.CenterCrop(256),

imneonizer

import redis
import fakeredis
import ujson
from contextlib import suppress


class RedisClient:
    def __init__(self, host=None, port=6379, db=0, prefix='libtorrent'):
        self.prefix = prefix
        self.host = host

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from google.colab.output import eval_js
print(eval_js("google.colab.kernel.proxyPort(8000)"))

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#include <Wire.h>
#include <ESP8266WiFi.h>

const int MPU_addr = 0x68; // I2C address of the MPU-6050
int16_t AcX, AcY, AcZ, Tmp, GyX, GyY, GyZ;
float ax = 0, ay = 0, az = 0, gx = 0, gy = 0, gz = 0, Amp=0;

// SCL -> D1
// SDA -> D2