Salman Maqbool salmanmaq

Ubuntu 22.04 for Deep Learning

In the name of God

This gist contains steps to setup Ubuntu 22.04 for deep learning.

Install Ubuntu 22.04

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

Intro

This is a comparison of packaging with python vs with npm.

TLDR

Python packaging is 3x as complex as javascript packaging. See the conclusion for more detail (but less than the whole document).

Categories examined:

[script creation](script creation)
[conversion to a package](conversion to a package)

	extension Array where Element == OCRCandidate {

	func sortCandidates() -> [OCRCandidate] {
	self.sorted { (currentCandidate, nextCandidate) -> Bool in
	let currentCandidateBottomY = currentCandidate.boundingPoints.avgBottomY
	let nextCandidateBottomY = nextCandidate.boundingPoints.avgBottomY

	if currentCandidateBottomY < nextCandidateBottomY {
	// Rounding item for discrepancies with Y positions.
	let difference = (currentCandidateBottomY - nextCandidateBottomY).roundTo2dp

	private func ocrRequestHandler(request: VNRequest, error: Error?) {
	guard let observations = request.results as? [VNRecognizedTextObservation] else { return }

	var ocrCandidates: [OCRCandidate] = []
	for observation in observations {
	guard let topCandidate = observation.topCandidates(1).first else { return }

	// Vision algorithms use a coordinate system with lower left origin.
	// Converting to upper left so the y values are increasing as the bounding box for observation
	// goes down the list as to how humans read english text.

	#!/bin/bash
	#Jason T. 2-6-2018

	# Check specifically for the run command
	if [[ $# -ge 2 && $1 == "run" ]]; then
	# Tell docker to share the following folders with the base system
	# This allows the docker containers to find CUDA, cuDNN, TensorRT
	LIB_MAPS="/usr/lib/aarch64-linux-gnu \
	/usr/local/cuda \
	/usr/local/cuda/lib64"

	<section id="cd-timeline" class="cd-container">
	<div class="cd-timeline-block">
	<div class="cd-timeline-img cd-picture">
	</div>

	<div class="cd-timeline-content">
	<h2>Penta Consulting</h2>
	<div class="timeline-content-info">
	<span class="timeline-content-info-title">
	<i class="fa fa-certificate" aria-hidden="true"></i>

	using System.Collections.Generic;
	using System.IO;
	using System.Collections;
	using UnityEditor;
	using UnityEngine;
	using System;
	using System.Threading;

	public class Utilities : EditorWindow
	{

	import numpy as np

	def computeIoU(y_pred_batch, y_true_batch):
	return np.mean(np.asarray([pixelAccuracy(y_pred_batch[i], y_true_batch[i]) for i in range(len(y_true_batch))]))

	def pixelAccuracy(y_pred, y_true):
	y_pred = np.argmax(np.reshape(y_pred,[N_CLASSES_PASCAL,img_rows,img_cols]),axis=0)
	y_true = np.argmax(np.reshape(y_true,[N_CLASSES_PASCAL,img_rows,img_cols]),axis=0)
	y_pred = y_pred * (y_true>0)

	#!/usr/bin/env python
	# -- coding: utf-8 --

	# Copyright 2016 Massachusetts Institute of Technology

	"""Extract images from a rosbag.
	"""

	import os
	import argparse