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import csv

with open("tiltset_credits_unique_13908_cleaned.csv", "r") as file:
	csv_reader = csv.reader(file)

	extra_comma_counter = 0

	for i, line in enumerate(csv_reader):
		num_commas = len(line) - 1
		if (num_commas > 1):

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import torch
import onnxruntime as ort

torch.cuda.is_available() # Nvidia or AMD GPU
torch.backends.mps.is_available() # Apple GPU

ort.get_device() # any GPU

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#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

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import os

with open("names.txt", "r") as file:
    lines = file.readlines()
    
    for line in lines:
        folder_name = line.strip().replace(" ", "_")
        os.makedirs(folder_name, exist_ok=True)
        print(f"Created folder: {folder_name}")

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# https://subscription.packtpub.com/book/data/9781788474443/9/ch09lvl1sec12/restoring-a-3d-point-from-two-observations-through-triangulation

import cv2
import numpy as np

# camera projection matrices
P1 = np.eye(3, 4, dtype=np.float32)
P2 = np.eye(3, 4, dtype=np.float32)
P2[0, 3] = -1

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/**
 * Resize the image to a new width and height using nearest neigbor algorithm. To make the image scale
 * proportionally, use 0 as the value for the wide or high parameter.
 * For instance, to make the width of an image 150 pixels, and change
 * the height using the same proportion, use resize(150, 0). 
 * Otherwise same usage as the regular resize().
 * 
 * Note: Disproportionate resizing squashes the "pixels" from squares to rectangles. 
 * This works about 10 times slower than the regular resize. Any suggestions for performance increase are welcome.
 */

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/**
 * Resize the image to a new width and height using nearest neighbor algorithm.
 * To make the image scale proportionally,
 * use 0 as the value for the wide or high parameters.
 * For instance, to make the width of an image 150 pixels,
 * and change the height using the same proportion, use resize(150, 0). 
 * Otherwise same usage as the regular resize().
 * 
 * Note: Disproportionate resizing squashes "pixels" from squares to rectangles. 
 * This works about 10 times slower than the regular resize.

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# https://blenderartists.org/t/how-to-select-bone-child-objects-in-one-click/660780/16

bl_info = {
    "name": "Select Siblings",
    "author": "Stanislav Blinov",
    "version": (1, 0, 0),
    "blender": (3, 0, 0),
    "description": "Select siblings in object mode (respecting distinct bone parents)",
    "category": "Object",
}

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import numpy as np
import open3d as o3d

rgb = o3d.io.read_image("rgb_image.jpg")
depth = o3d.io.read_image("depth_image.png")
#intrinsics = o3d.io.read_pinhole_camera_intrinsic("intrinsics.json")
intrinsics = o3d.camera.PinholeCameraIntrinsic(640, 480, fx=525.0, fy=525.0, cx=319.5, cy=239.5)

rgbd = o3d.geometry.RGBDImage.create_from_color_and_depth(rgb, depth)

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javascript:(function(){
    const MY_MASTO_LOCAL_DOMAIN = 'front-end.social'; /* 👈 Change this value */
    const MY_MASTO_WEB_DOMAIN = MY_MASTO_LOCAL_DOMAIN; /* 👈 Only change this value if your Masto host is hosted an different domain than the LOCAL_DOMAIN */

    function tryAndGetUserName() {
        /* Profile with a moved banner (e.g. https://mastodon.social/@bramus): follow that link */
        const userNewProfile = document.querySelector('.moved-account-banner .button')?.getAttribute('href');
        if (userNewProfile) {
            return userNewProfile.substring(2);
        }