austinbhale

import os
import re
import subprocess

def get_blur_values(video_path, start_time, duration):
    command = [
        "ffmpeg",
        "-i", video_path,
        "-vf", f"blurdetect=block_width=32:block_height=32,metadata=print:file=-",
        "-ss", str(start_time),

austinbhale

public class Program
{
    private static void Main(string[] _)
    {
        // Initialize StereoKit
        SKSettings settings = new()
        {
            appName = "ModelScaleSK",
            assetsFolder = "Assets",
        };

austinbhale

namespace SKAudioGraph
{
    using StereoKit;
    using System;
    using System.Linq;
    using System.Runtime.InteropServices;
    using System.Threading;
    using System.Threading.Tasks;
    using Windows.Foundation;
    using Windows.Media;

austinbhale

namespace SKAudioGraph
{
    using StereoKit;
    using System;
    using System.Runtime.InteropServices;
    using System.Threading.Tasks;
    using Windows.Foundation;
    using Windows.Media;
    using Windows.Media.Audio;
    using Windows.Media.MediaProperties;

austinbhale

// <copyright file="Program.cs" company="Nakamir, Inc.">
// Copyright (c) Nakamir, Inc. All rights reserved.
// </copyright>
namespace SK.AudioCapture.UWP;

using StereoKit;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.InteropServices;

austinbhale

import cv2
import numpy as np

logo_name = "original-logo.png"
logo = cv2.imread(logo_name, cv2.IMREAD_UNCHANGED)
assert(logo.any())

h, w, s = logo.shape
if w > h:
    out_img = np.zeros((w, w, s)) 

austinbhale

import cv2
import numpy as np

def psycho(img, trippy_factor=1./3):
    ris = img.astype(np.float32)
    ris += cv2.randn(img.copy(), 0, 10)

    kernel = np.zeros((3,3), dtype=np.float32)
    kernel.fill(trippy_factor)

austinbhale

import cv2 as cv
import numpy as np

dictionary = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_50)

num_markers_x = 4
num_markers_y = 4
marker_length = 0.04
marker_separation = 0.01