guissalustiano

def convolution(img: np.ndarray, filt: np.ndarray):
    iw, ih = img.shape
    kw, kh = filt.shape
    assert(kw % 2 == 1 and kh % 2 == 1) # Garante que o filtro tenha um centro
    kcx, kcy = kw//2, kh//2 # Calcula a posição central
    out = np.zeros(img.shape)
    for x, y in np.ndindex(*out.shape):
         #Pega os pixels que serão usados na operação com o filtro
        sub_img = img[max(0, x-kcx): min(iw, x-kcx + (kw)),
                      max(0, y-kcy): min(ih, y-kcy + (kh))]

guissalustiano

def gaussian_kernel(size, sigma=1):
  center = size//2
  x, y = np.mgrid[-center:center+1, -center:center+1]
  return np.exp(-((x**2 + y**2) / (2*sigma**2)))

guissalustiano

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm

def rgbToGray(img):
    # Baseado em https://pillow.readthedocs.io/en/3.2.x/reference/Image.html#PIL.Image.Image.convert
    return np.matmul(img, [0.2989, 0.5870, 0.1140]).astype(np.uint())

def convolution(img: np.ndarray, filt: np.ndarray):
    iw, ih = img.shape

guissalustiano

import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np

img = cv.imread('passarinho.jpg',0)
sobel = cv.Sobel(img, -1, 1, 1)

fig, ax = plt.subplots(ncols=2,figsize=(15,5))
ax[0].imshow(img, cmap = 'gray')
ax[0].set_title('Original')

guissalustiano

######################################################
# Por: Guilherme S Salustiano                        #
# Eng da Computação 2020                             #
######################################################

using Measurements

temperatura_da_agua_graus = 30 ± 0.5
distancia_tubos_pilot_centros = 5.4e-3
distancia_tubos_pilot_parede_centro = distancia_tubos_pilot_centros/2

guissalustiano

import requests
import re
from functools import cache

MOODLE_SESSION = ''
FILENAME = 'readme.md'


@cache
def file_content():

guissalustiano

from typing import Dict, Any
def flatten_dict(root: Dict[str, Any], separator: str = '.') -> Dict[str, Any]:
   """
   Tranforma dicionarios aninhados em um dicionario plano
   Exemplo:
   >>> flatten_dict({'a': 1, 'b': {'c': 2, 'd': 3}})
   >>> {'a': 1, 'b.c': 2, 'b.d': 3}
   """
   flatten_root = {}
   for root_key, root_value in root.items():

guissalustiano

from util import flatten_dict
 
def test_flatten_dict_nivel_1():
   assert flatten_dict({'a': 1, 'b': 2}) == {'a': 1, 'b': 2}
 
def test_flatten_dict_nivel_3():
   assert flatten_dict({'a': 1, 'b': {'c': 2, 'd': 3}}) == \
       {'a': 1, 'b.c': 2, 'b.d': 3}
 
def test_flatten_dict_nivel_4():

guissalustiano

$ pytest
========================= test session starts =========================
platform linux -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-0.13.1
rootdir: /home/guiss/Projetos/Turing/Talks/Logs
collected 4 items
 
util_test.py ....                                               [100%]
 
======================== 4 passed in 0.01s ============================

guissalustiano

-                 flatten_root_key = separator.join([root_key, item_key])
+                 flatten_root_key = '.'.join([root_key, item_key])