valgur

import numpy as np
import taichi as ti
from skimage.io import imread, imsave

ti.init(arch=ti.cuda)


@ti.kernel
def normals_from_depth_kernel(f: ti.f32, cx: ti.f32, cy: ti.f32, window_size: ti.u16, max_rel_depth_diff: ti.f32):
    height, width = ti_depth.shape()

valgur

#!/bin/bash

mv "$1" "${1%.*}"-$(sha256sum "$1" | cut -c1-8).pt

valgur

# x - easting, y - northing

def grid20k(x, y):
    x = int(x) // 1000 - 200
    y = int(y) // 1000 - 5900
    idx = (y // 100) * 1000 + (y // 10 % 10) * 10
    idx += (x // 100) * 100 + (x // 10 % 10)
    return idx

def grid10k(x, y):

valgur

valgur

valgur

valgur

import av

# packets = [H.264 packets as byte arrays]
codec = av.CodecContext.create('h264', 'r')
for packet in packets:
    for avpacket in codec.parse(packet):
        frames = codec.decode(avpacket)
        print(frames)
        
# Or, can also simply do

valgur

% Matlab sample code to read calibration data from sensor output.

fileFilter = '*.pcap';
[File_name, Directory] = uigetfile(fileFilter, 'Open a .pcap file');
Filename = [Directory File_name];
fid = fopen(Filename);
ttc = fread(fid, 40);
ttc = fread(fid, 42);
ttc = fread(fid, inf, '1206*uint8=>uint8', 58);
fclose(fid);

valgur

# Defines the following helper functions:
# - print_target_properties()
# - print_vars()
# - get_all_targets()

# Adapted from https://stackoverflow.com/a/68881024/2997179

# Print all properties of CMake target.
function(print_target_properties target)
  if(NOT TARGET ${target})

valgur

#!/bin/bash
set -eu -o pipefail

name=$1
version=$2
template=${3:-"cmake_package"}

echo Copying sources...
root=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
pkg_dir=$root/recipes/$name