stefsmeets

stefsmeets

stefsmeets

from skimage.segmentation import _watershed, _watershed_cy

from skimage.morphology._util import (_validate_connectivity,
                                _offsets_to_raveled_neighbors)

def watershed_pbc(image, markers=None, connectivity=1, offset=None, mask=None,
              compactness=0, watershed_line=False):
    """https://github.com/scikit-image/scikit-image/blob/main/skimage/segmentation/_watershed.py"""
    image, markers, mask = _watershed._validate_inputs(image, markers, mask, connectivity)
    connectivity, offset = _watershed._validate_connectivity(image.ndim, connectivity,

stefsmeets

import atexit
import subprocess as sp
import os

from PySide2 import QtCore, QtWebEngineWidgets, QtWidgets

def kill_server(p):
    if os.name == 'nt':
        # p.kill is not adequate
        sp.call(['taskkill', '/F', '/T', '/PID', str(p.pid)])

stefsmeets

import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
import streamlit as st

st.title('Normal distribution')

mu_in = st.slider('Mean', value=5, min_value=-10, max_value=10)
std_in = st.slider('Standard deviation', value=5.0, min_value=0.0, max_value=10.0)
size = st.slider('Number of samples', value=100, max_value=500)

stefsmeets

import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt

mu_in = 5
std_in = 5.0
size = 100

def norm_dist(mu, std, size=100):
	"""Generate normal distribution."""

stefsmeets

stefsmeets

stefsmeets

stefsmeets