ebraminio

# Sample toolchain file for building for Windows from an Ubuntu Linux system.
#
# Typical usage:
#    *) install cross compiler: `sudo apt-get install mingw-w64` or `brew install mingw-w64` on macOS
#    *) cmake -DCMAKE_TOOLCHAIN_FILE=~/mingw-w64-x86_64.cmake -G Ninja -B build -S .
#    *) ninja -C build


set(CMAKE_SYSTEM_NAME Windows)
set(TOOLCHAIN_PREFIX x86_64-w64-mingw32)

andelf

from PIL import Image, ImageDraw, ImageFont, ImageFilter

im = Image.open("./blue30.png")

POS = (1, 4)

X = POS[0] * 80
Y = POS[1] * 80

im1 = im.crop((X, Y, X + 30, Y + 30))

travishsu

import os
import json
import subprocess
import numpy as np
import pandas as pd
from skimage.measure import find_contours


class CocoDatasetHandler:
    def __init__(self, jsonpath, imgpath):

rikumi

# See https://github.com/rikumi/iconsur
yarn global add iconsur

sudo iconsur set /Applications/Android\ File\ Transfer.app -k Airdroid
sudo iconsur set /Applications/Android\ Studio.app/ -l -c 7a5 -s 0.8
sudo iconsur set /Applications/DaisyDisk.app/ -l
sudo iconsur set /Applications/Decompressor.app/ -l
sudo iconsur set /Applications/Discord.app/
sudo iconsur set /Applications/Google\ Chrome.app/
sudo iconsur set /Applications/IINA.app/ -l -c 161d22

shubhamwagh

Steps to create Textured Mesh from Point Cloud using Meshlab

Get your PointCloud into MeshLab

• Import the pointcloud file in ".ply" file format in Meshlab. Before importing make sure you do some pre-processing / cleaning on point cloud so as to ease the process of meshing.

Point Cloud Simplification and Normals Computation

• Next we need to reduce the number of point samples for smooth meshing.
  • So go to Filters -> Point Set -> Point Cloud Simplification. Enter Number of samples circa 5% of original number of points. Make sure Best Sample Heuristic is checked.
• After point cloud simplification, make sure to select Simplified point cloud in the Show Layer Dialog on the right hand side. If not visible, it can be opened by navigating to View -> Show Layer Dialog. Now we need to compute normals for point set.
• So go to Filters -> Point Set -> Compute normals for point sets . Enter Neighbour num between 10 - 100. Initially try with 10 and

mrnkr

import UIKit

class Semaphore {
    var n: Int
    
    init(n: Int) {
        self.n = n
    }
    
    func P() {

WesThorburn

Linux: Compile C++ to WebAssembly and JavaScript using Emscripten and CMake

Download and Install Emscripten

• My preferred installation location is /home/user
• Get the latest sdk: git clone https://github.com/emscripten-core/emsdk.git
• Enter the cloned directory: cd emsdk
• Checkout main: git checkout main
• Install the lastest sdk tools: ./emsdk install latest
• Activate the latest sdk tools: ./emsdk activate latest
• Activate path variables: source ./emsdk_env.sh

ihipop

This Version Allow run as nobody AND ports below 1024

/etc/systemd/system/frps.service

Systems that has AmbientCapabilities support (usually kernel >= linux4.3)

[Unit]
Description=FRP Server Daemon

assafrabin

"""
Simple script to convert ply to obj models
"""
import os
from argparse import ArgumentParser

from plyfile import PlyData


def parse_args():

parekhnish

import bpy
import bmesh
import numpy as np
import time
import os
import colorsys
import random
import yaml
import sys