macieklad

import {
  Children,
  FunctionComponent,
  isValidElement,
  PropsWithChildren,
  ReactElement,
  useMemo,
} from "react";

// Match util simplifies conditional code in your application

macieklad

// replace all occurences of abs(content) with |content| inside a string
function changeAbs(str) {
 let out = str
 let size = str.length
 let buf = ''
 let pos = 0
 let parens = 0
 let marker = 0
 
 while (pos < size) {

macieklad

classdef myDataSourceCam < handle
    % Klasa realizująca odczyt danych z kamery
    % - SZABLON DO UZUPELNIENIA
    % WERSJA: 17.09.2020, R2020a
    % Przykład użycia (użyj tego kodu do testów poprawności działania klasy): 
    %{
         parametryImportu=[];
         parametryImportu.nr     = 1; 
         vid1    = myDataSourceCam(parametryImportu);
         IM      = vid1.pobierzDane;

macieklad

- name: assignment
- variables:
        c00 >= 0
        c01 >= 0
        c02 >= 0
        c10 >= 0
        c11 >= 0
        c12 >= 0
        c20 >= 0
        c21 >= 0

macieklad

`ifndef MAPPED
	`include "simple_gates.v"
`else
	`include "impl1/simple_gates_impl1_mapvo.vo"
	//`include "impl1/simple_gates_impl1_vo.vo"
	//`define sdf_path "impl1/simple_gates_impl1_mapvo.sdf"
`endif


`timescale 1ns / 1ps

macieklad

def gradient(img, kernel_size = 5):
    sx = cv2.Sobel(img, cv2.CV_64F, 1, 0, ksize=kernel_size)
    sy = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=kernel_size)

    # Siła i kierunek gradientu
    G = np.hypot(sx, sy).astype(np.float32)
    G = G / G.max() * 255
    theta = np.arctan2(sy, sx)

    return G, theta

macieklad

// ==UserScript==
// @name         Moodel
// @namespace    http://tampermonkey.net/
// @version      0.1
// @description  try to take over the world!
// @author       You
// @match        https://upel2.cel.agh.edu.pl/*
// @grant        none
// ==/UserScript==

macieklad

head() {
    if ((this as any).singlePost) {
      return {
        title:
          (this as any).singlePost.title ||
          (this as any).singlePost.description ||
          'MEDizzy - Free medical cases, photos, videos and more',
        meta: [
          {
            hid: 'description',

macieklad

import cv2
import os
from matplotlib import pyplot as plt

import numpy as np

if not os.path.exists('ainvert.py') :
    !wget https://raw.githubusercontent.com/vision-agh/poc_sw/master/05_Resolution/ainvert.py --no-check-certificate

import ainvert

macieklad

coins = np.squeeze(cv2.imread("coins.png", cv2.IMREAD_GRAYSCALE))

def get_treshold_iteratively(image: np.ndarray, min_diff: float = .5) -> float:
    # Load image and separate pixels of each brightness level to its bin
    # bins=256 gets us buckets for values 0-1, 1-2, 2-3 ... 255-256.
    hist, _ = np.histogram(image, bins=256)
    
    # This next two lines give us vector of P(k) values
    # First we count all occurences of given brigthness level, then
    # we divide each by the ammount of pixels in the image.