vijay-prema

Ubuntu on Asus ROG Zephyrus G14 2021 (Setup guide)

Here is a way to do a robust install of Ubuntu (+ optional Windows 11 dual boot and LUKS encryption) on an Asus laptop, with minimal usable hardware support, without a significant amount of tinkering that may break in future or require frequent technical attention.

In summary, the key thing is to have an up to date kernel, which usually means disabling secure-boot and installing the latest stable (6.0+) using mainline or xanmod, and as well as making sure the latest nvidia driver and dkms is installed.

Specs:

• Model Asus G14 2021 (GA401QC)
• AMD R7 5800 8 core 16 thread (onboard Radeon graphics)
• NVIDIA RTX 3050 4GB (60W +15W boost)

davidfoster

using System.Collections.Generic;

/// <summary>A Kalman filter implementation for <c>float</c> values.</summary>
public class KalmanFilterFloat {

	//-----------------------------------------------------------------------------------------
	// Constants:
	//-----------------------------------------------------------------------------------------

	public const float DEFAULT_Q = 0.000001f;

hereismari

Setting up a MSI laptop with GPU (gtx1060)

Installing Ubuntu 18.04, CUDA, CDNN, Pytorch and TensorFlow

Installing Ubuntu 18.04

Get Image

https://tutorials.ubuntu.com/tutorial/tutorial-create-a-usb-stick-on-ubuntu#0

Install (solving issues)

steven2358

FFmpeg cheat sheet

A list of useful commands for the FFmpeg command line tool.

Download FFmpeg: https://www.ffmpeg.org/download.html

Full documentation: https://www.ffmpeg.org/ffmpeg.html

Basic conversion

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

rspeer

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

wiseodd

import numpy as np
from sklearn.datasets import make_moons
from sklearn.cross_validation import train_test_split


n_feature = 2
n_class = 2


def make_network(n_hidden=100):

ericandrewlewis

C++ Pointer Tutorial

Because pointers can be ugh

"Regular" variables (not pointers)

To understand a pointer, let's review "regular" variables first. If you're familiar with a programming language without pointers like JavaScript, this is what you think when you hear "variable".

When declaring a variable by identifier (or name), the variable is synonymous with its value.

patriciogonzalezvivo

VisualSFM by Changchang Wu

Probably the most straight forward way to start generating Point Clouds from a set of pictures.

VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM). The reconstruction system integrates several of my previous projects: SIFT on GPU(SiftGPU), Multicore Bundle Adjustment, and Towards Linear-time Incremental Structure from Motion. VisualSFM runs fast by exploiting multicore parallelism for feature detection, feature matching, and bundle adjustment.

For dense reconstruction, this program supports Yasutaka Furukawa's PMVS/CMVS tool chain, and can prepare data for Michal Jancosek's CMP-MVS. In addition, the output of VisualSFM is natively supported by Mathias Rothermel and Konrad Wenzel's [SURE]