alexlib

alexlib

import cv2
import numpy as np

def minMaxFilter(img, filterSize, minContrast):
    """
    After R.Adrian, J.Westerweel, "Particle image velocimetry", Cambridge
    university press, 2011. See ch.6.1.2, p.248-250.
    Parameters: img (cv2.imread) - image to be filtered
                filterSize (nd.array) - a 1x2 numpy array of the filter height
                                        and width correspondingly

alexlib

def customDeen(frame0,
               frame1,
               algorithmType = 'basic',
               cliplimit = 2.0,
               tileGridSize = (4, 4)
              ):
    """
    This is the custom implementation of the image processing alogrithm for PIV
    after Deen, Willems, Annaland, Kuipers, Lammertink, Kemperman, Wessling,
    Meer, "On image preprocessing for PIV of single and two phase flows over

alexlib

alexlib

## Follow this link for further updates to Github Desktop for Ubuntu https://github.com/shiftkey/desktop/releases/latest
# UPDATE (2021-10-18): Thanks to Amin Yahyaabadi's message, the updated code is as follows

sudo wget https://github.com/shiftkey/desktop/releases/download/release-2.9.3-linux3/GitHubDesktop-linux-2.9.3-linux3.deb
### Uncomment below line if you have not installed gdebi-core before
# sudo apt-get install gdebi-core 
sudo gdebi GitHubDesktop-linux-2.9.3-linux3.deb

# UPDATE (2021-03-05): Thanks to PaoloRanzi81's comment, the updated code is as follows https://gist.github.com/PaoloRanzi81

alexlib

def align_vectorised(a: np.ndarray, b: np.ndarray):
    """
    Find array of rotation matrices r such that r @ a = b when a and b are arrays of normalised vectors
    implementation designed to avoid trig calls
    based on https://iquilezles.org/www/articles/noacos/noacos.htm
    :param a: normalised vector(s) of length 3
    :param b: normalised vector(s) of length 3
    :return: rotation matrix
    """
    # setup

alexlib

def random_uniform_rotation(size=1):
    """
    Return uniform rotation vectors sampled on a sphere
    Args:
        size : int 
          The number of vectors
    Returns:
        vector: np.ndarray
          The rotation vectors
    """

alexlib

from time import sleep

import napari
import numpy as np
from napari.qt.threading import thread_worker

viewer = napari.Viewer()
bbox_layer = viewer.add_points(
    [[-1, -1], [-1, 1], [1, -1], [1, 1]], face_color='green')
points_layer = viewer.add_points([0, 0], face_color='magenta')

alexlib

from time import sleep
from enum import Enum

import napari
import numpy as np
import psygnal
from napari.qt.threading import thread_worker

BOARD_SIZE = 14
INITIAL_SNAKE_LENGTH = 4

alexlib